Search

In light of the escalating global energy imperatives, mining of challenging-to-access resources, such as steeply inclined extra-thick coal seams (SIEC), has emerged as one of the future trends within the domain of energy advancement. However, there is a risk of gas and coal spontaneous combustion coupling disasters (GCC) within the goaf of SIEC due to the complex goaf structure engendered by the unique mining methodologies of SIEC. To ensure that SIEC is mined safely and efficiently, this study conducts research on the GCC within the goaf of SIEC using field observation, theoretical analysis, and numerical modeling. The results demonstrate that the dip angle, the structural dimensions in terms of width-to-length ratio, and compressive strength of the overlying rock are the key factors contributing to the goaf instability of SIEC. The gangue was asymmetrically filled, primarily accumulating within the central and lower portions of the goaf, and the filling height increased proportionally with the advancing caving height, the expansion coefficient, and the thickness of the surrounding rock formation. The GCC occurs in the goaf of SIEC, with an air-return side range of 41 m and an air-intake side range of 14 m, at the intersection area of the “”-shaped gas concentration distribution (gas explosion). The optimal nitrogen flow rate is 1000 m3/h with an injection port situated 25 m away from the working face for the highest nitrogen diffusion efficacy and lowest risk of gas explosion, coal spontaneous combustion, and GCC. It has significant engineering applications for ensuring the safe mining of SIEC threatened by the GCC.

Microseismic source location is crucial for the early warning of rockburst risks. However, the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy. Intelligent techniques, such as the full convolutional neural network (FCNN), can capture spatial information but struggle with complex microseismic sequence. Combining the FCNN with the long short-term memory (LSTM) network enables better time-series signal classification by integrating multi-scale information and is therefore suitable for waveform location. The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction. In this study, we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus. Initially, the method of short-time-average/long-time-average (STA/LTA) arrival time picking was employed to augment spatiotemporal information. Subsequently, oversampling the on-site data was performed to address the issue of data imbalance, and finally, the performance of LSTM-FCNN was tested. Meanwhile, we compared the LSTM-FCNN model with previous deep-learning models. Our results demonstrated remarkable location capabilities with a mean absolute error (MAE) of only 7.16 m. The model can realize swift training and high accuracy, thereby significantly improving risk warning of rockbursts.

Rock failure can cause serious geological disasters, and the non-extensive statistical features of electric potential (EP) are expected to provide valuable information for disaster prediction. In this paper, the uniaxial compression experiments with EP monitoring were carried out on fine sandstone, marble and granite samples under four displacement rates. The Tsallis entropy q value of EPs is used to analyze the self-organization evolution of rock failure. Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes. A self-organized critical prediction method with q value is proposed. The results show that the probability density function (PDF) of EPs follows the q-Gaussian distribution. The displacement rate is positively correlated with q value. With the displacement rate increasing, the fracture mode changes, the damage degree intensifies, and the microcrack network becomes denser. The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode. The q value of EPs can be used as an effective prediction index for rock failure like b value of acoustic emission (AE). The results provide useful reference and method for the monitoring and early warning of geological disasters.

Abstract Fluctuations in gas emission or concentration at working face represent primary indicators of impending coal and gas outbursts, making them essential for monitoring processes. However, the direct use of original signals for predictive purposes may cause false warnings due to the inability to recognize valuable potential information. This can result in decreased prediction accuracy. Additionally, gas emission or concentration is affected by potential hazards such as sensor calibration, borehole spraying, and air duct damage, leading to complexity of their behavior and recognition process. This paper proposes an intelligent recognition method leveraging YOLOv8 neural network to discern coal and gas outburst precursors and potential hazards. By employing continuous wavelet transform (CWT) on the gas concentration signal processed by critical slowing down (CSD) method, a two-dimensional time–frequency representation is generated. This representation is then fed into YOLOv8 model to recognize the outburst precursor characteristics and potential hazards. The research results show that YOLOv8-based intelligent recognition adeptly identifies the relevant precursor characteristics and potential hazards, enhancing both coal mine safety protocols and the accuracy of early outburst warning mechanisms.

This study explores the thermal behavior of graphite-enhanced expanded polystyrene (GEPS) both with and without a rendering cover during cone calorimeter testing. We designed a sample holder with inserted thermocouples to capture temperature variations at different levels. Without a cover, the sample remained unignited under radiant intensity of 25 kW m−2, experiencing a brief temperature rise followed by stabilization. At 50 kW m−2, ignition occurred after a period of steady temperature. However, at 75 kW m−2, the temperature soared rapidly without a stable phase, leading to swift ignition. With a cover, the temperatures for all tested scenarios ultimately stabilized without ignition, even though the recorded values exceeded the ignition point under high heat fluxes. This indicates that the protective mechanism of render lies mainly in isolating mass transfer. Increasing the render's thickness from 3 mm to 5 mm delayed and slowed the initial temperature rise but had little impact on the final steady temperatures. Based on the energy conservation principles, a steady temperature prediction model for liquified GEPS and rendering cover was established. Notably, the calculated outcomes closely align with the measured temperatures. These findings provide valuable insights into the fire safety characteristics of GEPS and the protective effects of rendering covers.

In this study, some loading experiments were conducted on coal specimens using the established weak current testing system to investigate the effects of weak currents in coals. The response characteristics of weak currents during the coal deformation process were analyzed, and a quantitative relationship between weak currents and the mechanical behaviors of coal was established. The principles for predicting coal and rock dynamic disasters based on the weak current method were proposed. Furthermore, drawing upon the results obtained from on-site practical applications, a forward-looking assessment of the potential applications of this methodology is presented. The results indicate that the deformation of loaded coal generates weak currents. The fluctuations in these weak currents exhibit a notable alignment with variations in stress, with the magnitude closely tied to the coal mechanical characteristics like stress, strain, and strain rate. Notably, in the compaction and plastic deformation stages, the weak current rises in tandem with the strain rate, while in the elastic deformation stage, the weak current exhibits a linear increase in correlation with stress and strain. Under perturbation loading, the coal produces some periodic weak currents, referred to as the pulsating direct current (PDC). And the variations in the PDC align with stress changes. Furthermore, the weak current demonstrates a reliable precursor response to coal damage, with some unusual fluctuations observed during the accelerated increase process (plastic deformation stage) serving as the precursor indicators for the progressive failure of coal. Conversely, the pulse-like fluctuations observed during the attenuation process can be regarded as the precursor features for the coal's creep failure. The phenomenon of weak currents in stressed coal serves as a pivotal foundation for conducting weak current measurements in mines. The intimate correlation between weak currents and the mechanical behaviors of coal underscores a crucial prerequisite for employing the weak current technology in monitoring stress within coal and rock formations. Furthermore, the discernible precursor response of weak currents to coal damage provides a vital assurance for predicting coal and rock dynamic disasters through the utilization of weak current technology. The weak current technology possesses some advantages such as high responsiveness, clear precursor signals, and robust anti-interference capabilities. These attributes make it highly promising for some applications in the stress monitoring within coal/rock mass and the early warning for coal and rock dynamic disasters. In the future, some further researches on the fundamental theory and applied technology of weak current in stressed coal and rock are needed to provide a support for the development of precise spatiotemporal monitoring and early warning of coal rock dynamic disasters using the weak current methods.

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents (PSCs) has great potential for the understanding of dynamic disasters in underground engineering. To reveal the effect of this way, the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength combinations. The mechanism explanation of PSCs are investigated by resistivity test, atomic force microscopy (AFM) and computed tomography (CT) methods, and a PSC flow model based on progressive failure process is proposed. The influence of strength combinations on PSCs in the progressive failure process are emphasized. The results show the PSC responses between rock part, coal part and the two components are different, which are affected by multi-scale fracture characteristics and electrical properties. As the rock strength decreases, the progressive failure process changes obviously with the influence range of interface constraint effect decreasing, resulting in the different responses of PSC strength and direction in different parts to fracture behaviors. The PSC flow model is initially validated by the relationship between the accumulated charges of different parts. The results are expected to provide a new reference and method for mining design and roadway quality assessment.

Abstract Due to the complexity of the strata, it is difficult to monitor and identify the disasters induced by rock fractures in the process of mining deep coal resources. This will seriously affect the safety and sustainable mining of coal. Therefore, it is necessary to understand the failure mechanisms and acoustic emission (AE) characteristics of different rocks. In this paper, uniaxial compression tests as well as simultaneous AE monitoring were carried out on four different rocks. The four rocks include yellow sandstone, white sandstone, marble and limestone. The mechanical properties, energy evolution and AE characteristics of different rocks were analysed. It is found that the AE response of rocks is closely related to the damage and fracture process. The more brittle the rock is, the less energy is dissipated before failure, and the less obvious the AE precursor is, and the RA-AF values can effectively characterise the failure modes of different rocks. Finally, the damage models were developed from the perspectives of AE energy and dissipated energy, respectively. The damage model based on dissipated energy can better reflect the stress and damage state of the rock, and the theoretical curves of stress–strain are in good agreement with the measured curves.

Microseism, acoustic emission and electromagnetic radiation (M-A-E) data are usually used for predicting rockburst hazards. However, it is a great challenge to realize the prediction of M-A-E data. In this study, with the aid of a deep learning algorithm, a new method for the prediction of M-A-E data is proposed. In this method, an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data, and then the M-A-E data can be predicted. The predicted results are highly correlated with the real data collected in the field. Through field verification, the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.

In this study, the influence of different functional groups (carbonyl, ether, carboxyl, and hydroxyl) on microporous development and competitive adsorption for CO 2 -CH 4 was investigated using Connolly potential theory, molecular mechanics, molecular dynamics, and grand canonical Monte Carlo based on the macromolecular representation of coal vitrinite (CV). Results indicated that microporous diameter induced from the carboxyl (COOH) and hydroxyl (OH) was more sensitive to increasing temperature than carbonyl (CO) and ether (C2O). The COOH and OH could induce more micropores than the other functional groups. The adsorption capacities of OH-CV and COOH-CV were significantly higher than C2O-CV, CO-CV, and C-CV (coal vitrinite purified by carbon atoms) and they all decrease with the decreasing temperature. Both the calculation results of Locate- and Isotherm task suggested that OH and COOH have a significantly higher adsorption amount than other coal macromolecules and the others have a close adsorption amount. The adsorption selectivities of CO 2 over CH 4 ( S A/B ) for all the functional groups were higher than 1 here, indicating the adsorption preference of CO 2 over CH 4 . For the pressure dependence, the S A/B first decreases significantly for the pressure of 4 MPa with the increasing pressure, indicating that high pressure was not conductive to the replacement of CH 4 by CO 2 . For almost all the pressures here, the S A/B follows the order of COOH-CV > OH-CV≈C2O-CV≈Ori-CV≈CO-CV≈C-CV, indicating the highest adsorption preference of CO 2 over CH 4 for COOH, and OH-CV.

When extracting coal-bed methane (CBM) from deep ground, conventional hydraulic fracturing struggled to expand fractures due to both inadequate pressure and the water-lock phenomenon, while burgeoning fracturing techniques were unable to provide both high pressure and impact stress. The hydrothermal phase change impact fracturing technology can instantaneously discharge high-pressure thermal fluid and generate impact stress to volumetric fracturing. In order to research the fracturing mechanism of the new fracturing strategy, a separately designed experimental system was utilised for high-pressure thermohydraulic fracturing at different release pressures and different peripheral pressures. The experimental findings: (1) The pressurisation profile in the reactor was divided into five stages: accelerated reaction process, reaction homogeneity process, deceleration process, pressure relief shock stage and residual pressure seam formation process; (2) High-pressure hydrothermal fracture produces both radial and tearing cracks, with radial cracks being the main cracks; (3) The dimension of the fractal can be used as a damage variable to describe both the fracture morphology and the degree of damage.

Abstract A new fluid alternative to slick water for fracturing shale gas can reduce the waste of water resources and improve the extraction efficiency, enabling volumetric fracturing. For the new fracturing technique, the experiments of different release pressures under pre-injection and for pre-injection were conducted using a self-designed true triaxial experimental system, and the pressure pulse curves were plotted to analyze the fracturing principle. The experimental results showed that: (1) the pressure rise curve in the reactor can be divided into five stages: initial reaction, linear pressure rise, rate slowdown, instantaneous pressure release, and residual pressure stages; (2) Pre-filling fracturing requires a smaller expansion ratio, weaker pressure degradation, resulting in better fracturing effect; (3) The increase in the initial fracture length leads to an increase in the pressure required to extend the fracture, and high-pressure subcritical water impact fracturing achieved fracture extension at a lower fluid pressure; (4) The fractal dimension has a strong linear relationship with fracture complexity, which is a new option when evaluating the fracturing effect. Volumetric fracturing allows for the creation of more tiny trenches that increase reservoir permeability, leading to better recovery of the reservoir’s energy resources.

Abstract In this study, uniaxial compression tests and simultaneous acoustic emission (AE) monitoring were carried out on four rocks (yellow sandstone, white sandstone, marble and limestone). The mechanical properties and AE energy evolution characteristics of different rocks were analysed. With the help of critical slowing down (CSD) theory, the AE precursor characteristics of their failure were investigated. It is pointed out that the AE during rock loading has a CSD phenomenon. A sudden change in the variance of one of the CSD indicators can be regarded as a precursor to failure, and it has the advantage of being more accurate and sensitive to failure than the autocorrelation coefficient. The stress level of a rock's failure precursor is closely related to its brittleness characteristics. The higher the brittleness of the rock, the more backward the failure precursor is, and the more difficult the early warning is. The study aims to provide new indicators and references for the monitoring and early warning of rockbursts and other disasters induced by rock fracture in deep underground engineering.

Different coal failure impact types exhibit different damage statuses and failure modes, resulting in distinct signal characteristics of infrared radiation (IR) and acoustic emission (AE). This paper combines IR and AE monitoring methods to innovatively establish coal damage and failure precursor warning models and obtains the IR and AE precursor characteristics for different coal failure impact types. This research shows that there is a good correspondence between IR and AE timing and spatial distribution of different coal impact types. As the impact tendency increases, the intensity of IR and AE signals increases with coal failure, and the AE positioning points and IR high-temperature areas tend to concentrate. The coal body gradually changes from tensile failure to shear failure. The shear cracks in the failure stage of coal with no, weak, and strong impact are 39.9%, 50.9%, and 53.7%, respectively. The IR and AE instability precursor point of coal with no, weak, and strong impact occurred at 55.2%, 66.3%, and 93.4% of coal failure, respectively. After the IR and AE combined instability precursor point, the dissipated energy and combined damage variable increase rapidly, and the coal body will undergo instability and failure. The research results provide a theoretical basis for comprehensive monitoring of coal body failure and rock burst.

Pansharpening refers to the process of fusing multispectral (MS) images with panchromatic (PAN) images to obtain high-resolution multispectral (HRMS) images. However, due to the low correlation and similarity between MS and PAN images, as well as inaccuracies in spatial information injection, HRMS images often suffer from significant spectral and spatial distortions. To address these issues, a pansharpening method based on multimodal texture correction and adaptive edge detail fusion is proposed in this paper. To obtain a texture-corrected (TC) image that is highly correlated and similar to the MS image, the target-adaptive CNN-based pansharpening (A-PNN) method is introduced. By constructing a multimodal texture correction model, intensity, gradient, and A-PNN-based deep plug-and-play correction constraints are established between the TC and source images. Additionally, an adaptive degradation filter algorithm is proposed to ensure the accuracy of these constraints. Since the TC image obtained can effectively replace the PAN image and considering that the MS image contains valuable spatial information, an adaptive edge detail fusion algorithm is also proposed. This algorithm adaptively extracts detailed information from the TC and MS images to apply edge protection. Given the limited spatial information in the MS image, its spatial information is proportionally enhanced before the adaptive fusion. The fused spatial information is then injected into the upsampled multispectral (UPMS) image to produce the final HRMS image. Extensive experimental results demonstrated that compared with other methods, the proposed algorithm achieved superior results in terms of both subjective visual effects and objective evaluation metrics.

Meta-instability stage is the most abundant precursory information and the most intense change stage in the process of fault stick-slip instability. In order to deeply explore the characteristics of coal meta-instability and the response law of acoustic and electrical signals in this process, the uniaxial graded loading experiments of coal samples with different prefabricated crack angles were carried out. The internal fracture source location, surface displacement field, acoustic emission and electromagnetic radiation signals of the samples were synchronously collected, and the mechanical behavior and acoustic and electrical characteristics of coal meta-instability were analyzed. The results show that: ① The inclination angle of the prefabricated crack significantly affects the internal stress distribution of the loaded coal sample, and even the expansion distribution of the new cracks in the meta-instability stage. The acoustic emission count and energy have obvious responses to stress and failure. When the meta-instability is near, the acoustic emission count and energy increase sharply at the same time, and the signal proportion is close to 20%. The response characteristics can be used as the basis for judging the crack coal sample entering the meta-instability stage. ② After entering the meta-instability state, the electromagnetic radiation activity is the most intense, which is almost consistent with the occurrence time of stress drop. Before the main fracture occurs, the energy and amplitude of electromagnetic radiation increase sharply, and the peak energy increases first and then decreases with the increase of crack dip angle. When the crack dip angle is 45°, the electromagnetic radiation count accounts for the largest proportion of the total instability process. ③ The fracture profile of the coal sample in the meta-instability stage has been basically formed. The inclination angle of the prefabricated crack has a significant impact on the duration of the meta-instability stage of the coal sample. When the inclination angle is 45°, the duration of the meta-instability stage is the longest, and when the inclination angle is 60°, the duration proportion is the shortest. The research results can be used to formulate the monitoring scheme of fault meta-instability, and the evolution and disaster of large-scale rock burst in fault structural area

As shallow coal resources are gradually exhausted in China, the shift of coal mining from shallow to deep will become a new normal condition for ensuring the energy demand of China. Aiming at the problems of coal and gas outbursts, rockburst, and complex dynamic disasters faced by the mining of deep coal resources, the research progress of coal and rock dynamic disaster mechanism in China is analyzed, the key technologies of coal and rock dynamic disaster evaluation, monitoring and early warning are expounded, and the measures and technical means of coal and rock dynamic disaster prevention and risk control are summarized. Based on the trend of deep coal mining, the scientific and technological problems and scientific research prospects for the prevention of coal and rock dynamic disasters are put forward. In terms of research means, the research and development should focus on scientific research instruments that can truly reflect the complex geological conditions, engineering conditions and the process of multi-field coupling. The simulation and reconstruction technology should be developed for the evolution of mine dynamic disasters. Also, the coupling evolution mechanism of coal and rock dynamic disasters should be investigated and revealed. In the aspect of dangerous area detection, it should further develop the advanced acceptable detection theory and technology of dynamic disaster dangerous area of working face based on geophysical means, and develop the drilling and inversion technology of multi-parameter space-time distribution of coal and rock strata under the influence of in-situ conditions and mining. In the aspect of risk assessment, it should carry out research on key indicators and intelligent assessment methods of disaster risk assessment under the coupling conditions of deep complex strata and mining engineering. In the aspect of monitoring and early warning, the coal mine multi-disaster integrated monitoring and early warning platform should be established to realize the coal mine multi-disaster integrated monitoring, intelligent early warning and accurate analysis of safety situation. The remote and accurate regional prevention and control technology of coal and rock dynamic disasters should be developed to realize the advanced regional prevention and control of coal and rock dynamic disasters. The digital emergency decision-making theory and key technology of coal and rock dynamic disasters should be studied in order to realize the intelligent emergency decision-making of coal and rock dynamic disasters. The systematic research on theory, technology, and equipment will guarantee the effective prevention and control of dynamic disasters and safe and efficient mining of coal resources.

Deep coal is mostly in a three-dimensional unequal stress state. In order to study the dynamic characteristics of coal under impact load, the dynamic failure mechanics experiment of coal was carried out by true triaxial Hopkinson experimental system. This system can be used to provide uniaxial (σ1≥σ2=σ3=0), biaxial (σ1≥σ2 > σ3=0) and true triaxial (σ1≥σ2≥σ3 ≠ 0) pre-stressing for coal samples respectively(where, σ1 is axial prestress; σ2 is vertical prestress; σ3 is horizontal prestress), so as to realize the mechanical property test of coal samples at high strain rates. By analyzing the dynamic mechanical characteristics and differences of coal under uniaxial and true-triaxial static pre-stress, the relationships of dynamic peak strength, peak strain and macroscopic fracture morphology with three-dimensional static pre-stress and strain rate were studied. The results show that the mechanical curves of coal under true triaxial impact load are basically the same, including three stages: linear elastic stage, plastic stage and failure stage. The peak strength and strain of coal samples under uniaxial and true triaxial impact loads have obvious strain rate effects .With the increase of strainrate, the peak strength and peak strain of coal under uniaxial and true triaxial impact loading increase gradually. Compared with uniaxial and true triaxial impact, the three-dimensional static load pre-stress has obvious constraint on the dynamic failure of coal specimen, and the mechanical strength of coal specimen is higher than that of uniaxial impact. The mechanical peak strength and strain of the coal sample decrease with the increase of the principal stress σ1 while the stress σ2 and σ3 remain unchanged. With the increase of strain rate, the coal under uniaxial impact load is gradually broken into particles or powder, and the average particle size of the fragments decreases linearly with the increase of strain rate. However, the coal under three-dimensional static pre-stress presents soma macroscopic fractures, and the average particle size of fragments decreases linearly with the increase of σ1 while the damage degree is lower than that of uniaxial impact.

With the continuous increase of mining depth, coal and gas outburst poses a significant threat to mining safety. Conducting research on the mechanisms of coal and gas outbursts contributes to understanding the evolutionary process of such incidents, thus enabling accurate prediction and prevention of coal and gas outbursts during mining operations. This paper has developed a comprehensive visual experimental system that is specifically tailored to simulate diverse coal body conditions, ground stress and gas pressures. By monitoring and analyzing the real-time progression of coal fissures during the outburst process, we can obtain valuable insights into the evolution and mechanisms of coal and gas outbursts. Additionally, this study introduces a method to determine the critical threshold for predicting coal and gas outbursts, and the critical gas pressure threshold for Jiulishan Coal Mine (Jiaozuo City, Henan Province, China) is established at 0.6 MPa.

When the traditional drill and blast method is applied to rock crushing projects, it has strong vibration, loud noise and dust pollution, so it cannot be used in densely populated areas such as urban public works. We developed a supercritical CO2 true triaxial pneumatic rock-breaking experimental system, and conducted laboratory and field tests of dry ice powder pneumatic rock-breaking. The characteristics of the blast-induced vibration velocity waveform and the evolution of the vibration velocity and frequency with the focal distance were analyzed and discussed. The fracturing mechanism of dry ice powder pneumatic rock breaking is studied. The research results show that: (1) The vibration velocity induced by dry ice powder pneumatic rock breaking decays as a power function with the increase of the focal distance; (2) The vibration frequency caused by dry ice powder pneumatic rock breaking is mainly distributed in 1–120 Hz. Due to the dispersion effect, the dominant frequency of 10–30 Hz appears abnormally attenuated; (3) The traditional CO2 phase change fracturing energy calculation formula is also applicable to dry ice pneumatic rock breaking technology, and the trinitrotoluene (TNT) equivalent of fracturing energy is applicable to the Sadovsky formula; (4) Dry ice powder pneumatic rock breaking is shock wave and high-energy gas acting together to fracture rock, which can be divided into three stages, among which the gas wedge action of high-energy gas plays a dominant role in rock mass damage.

Abstract In the process of green and smart mine construction under the context of carbon neutrality, China's coal safety situation has been continuously improved in recent years. In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents, this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years (2017–2021), from four dimensions (accident level, type, region, and time), and then proposed the preventive measures based on accident statistical laws. The results show that the storage of coal resources has obvious geographic characteristics, mainly concentrated in the Midwest, with coal resources in Shanxi and Shaanxi accounting for about 49.4%. The proportion of coal consumption has dropped from 70.2% to 56% between 2011 and 2021, but still accounts for more than half of the all. Meanwhile, the accident-prone areas are positively correlated with the amount of coal production. Among different levels of coal mine accidents, general accidents had the highest number of accidents and deaths, with 692 accidents and 783 deaths, accounting for 87.6% and 54.64% respectively. The frequency of roof, gas, and transportation accidents is relatively high, and the number of single fatalities caused by gas accidents is the largest, about 4.18. In terms of geographical distribution of accidents, the safety situation in Shanxi Province is the most severe. From the time distribution of coal mine accidents, the accidents mainly occurred in July and August, and rarely occurred in February and December. Finally, the "4 + 4" safety management model is proposed, combining the statistical results with coal production in China. Based on the existing health and safety management systems, the managements are divided into four sub-categories, and more specific measures are suggested.

Abstract To investigate the effect of water on the mechanical properties and acoustic emission (AE) characteristics of coal in the failure and deformation processes. Coal samples of different content were subjected to uniaxial compression tests and AE signals were monitored. The characteristics of the AE signals were further analyzed using fractal analysis. The results show that saturated coal samples have substantially reduced mechanical properties such as uniaxial compressive strength (UCS), dissipation energy, peak stress, and elastic modulus. Under loading, stress–strain curves are characterized by five distinct stages: (1) compaction; (2) linear elastic; (3) crack stable propagation; (4) crack accelerating propagation; and (5) post-peak and residual stages. Using phase-space theory, a novel Grassberger Procaccia (GP) algorithm was utilized to find the AE fractal characteristics of coal samples in different stages. It is significant to note that AE energy does not exhibit fractal characteristics in either the first or second stages. Contrary to the first two stages, the third stage showed obvious fractal characteristics. Fractal analysis of AE time sequences indicates that fractal dimension values change as stress increases, indicating the initiation of complex microcracks in coal. In the fourth stage, the fractal dimension rapidly declines as the strength reaches its limit, indicating the occurrence of macrocracks. However, fractal dimensions continued to decrease further or increased slightly in the fifth stage. Consequently, the coal begins to collapse, potentially resulting in a disaster and failure. It is, therefore, possible to accurately predict coal and rock dynamic failures and microcrack mechanisms by observing the subsequent sudden drop in the correlation dimension of the AE signals in response to different stages of loading.

The uniaxial compression experiments and acoustic emission (AE) monitoring are conducted to investigate the macroscopic mechanical behavior and microscopic fracture characteristics of limestone samples with varying moisture contents. The findings revealed that as the moisture content increases from 0 to 6.6%, there is a decrease in peak stress and an increase in peak strain. A clear trend towards greater complexity in fracture characteristics is observed with increasing moisture content. In addition, AE activities demonstrate a heightened frequency, accompanied by an elevation in the corresponding multifractal parameter Δα as the moisture content rises. These variations are attributed to the increase in moisture content, which promotes the proliferation of small-scale microcracks and inhibits their evolution into large-scale microcracks. Consequently, the damage and failure process of the limestone samples transitions from being predominantly controlled by a few large-scale microcracks to being collectively influenced by a multitude of small-scale microcracks as the moisture content increases. In conjunction with the Criterion of Microcrack Density, the correctness of the analysis above is substantiated through mathematical derivation. Further, a quantitative model that links the microcrack system to moisture content is established based on the multifractal parameter Δα. Following this, a characterization model that depicts the macroscopic mechanical properties of limestone affected by moisture content is developed. This model effectively encapsulates the quantitative relationship between moisture content and the macroscopic characteristics of limestone and is validated through fitting experimental data. This research contributes to understanding the macroscopic mechanical response and microscopic fracture characteristics of limestone samples with different moisture contents, providing valuable insights and guidance for ensuring safety during engineering construction processes.

Abstract During the deformation and fracture process, the acoustic emission (AE) signals can be produced for the of coal, rock and other solid materials, which revealing the damage localization evolution process. The effect of gas adsorption and pressure can change mechanical properties of coal mass and affect its damage development. Based on this, the experimental system for gas-bearing coal loading and AE monitoring was constructed, to analyze AE response characteristics under the joint action of loading stress and gas pressure on coal specimen. Afterwards, the damage localization evolution process of coal mass was studied with the moment tensor inversion method. Results showed that temporal response of AE signals was closely related to the damage degree and loading level of coal specimen, which could reveal its local severe damage and final failure characteristics. The spatial distribution and spread trend of AE fracture events inside coal specimen could be calculated through the moment tensor inversion method. It was basically consistent with the results of crack expansion on the specimen surface. The zones, where fracture events occurred intensively, gathered and spread in a continuous trend, were conductive to forming the macrocrack belt macroscopically. It could be regarded as the hazard zone with dynamic failure occurrence. Moreover, when the coal specimen faced the critical failure, the precursor characteristics of AE response appeared with the shear fracture events dominated markedly. The study results provide a new research idea for revealing the damaging localization evolution process under the coupling effect of stress and gas and lay the application foundation.

This paper conducts impact dynamics experiments on coal measures sandstone in a deep mine via the established dynamic load and temperature split Hopkinson pressure bar (SHPB) experimental system. Firstly, the experimental conditions for the impact dynamics of fine sandstone were determined, with temperatures of 18, 40, 60, 80, and 100 °C, an axial static load range of 1–9 MPa, and a preset bullet incidence velocity of 1.0–5.0 m/s. Secondly, based on the analysis of the basic parameters and physical composition, the dynamic stress and strain responses of fine sandstone under different experimental conditions were obtained, and the change mechanism of its dynamic mechanical process was theoretically analyzed. When the temperature rose from 18 °C to 100 °C, the dynamic peak stress of fine sandstone increased from 36.04 MPa to 73.41 MPa, with an increase of 103.7%. At a temperature of 40 °C, when the axial static load increased from 1 MPa to 9 MPa, the dynamic stress peak of fine sandstone increased from 57.25 MPa to 80.01 MPa, and the corresponding peak strain also showed an increasing trend. The experiment analyzed the variation characteristics of dynamic stress in fine sandstone under the combined action of different strain rates or bullet incidence velocities and different temperatures. In the strain rate range of 47.1 s−1 to 140.9 s−1, there was a significant strain rate effect on the dynamic peak stress and peak strain of fine sandstone, which increased with the increase of strain rate. The study found a polynomial relationship between the dynamic mechanical parameters of fine sandstone and the impact of experimental parameters, with a coefficient of determination greater than 0.9. A dynamic stress constitutive model for fine sandstone under one-dimensional stress state under dynamic load and temperature action was established, and the model validation and parameter determination of dynamic stress changes in fine sandstone under different temperature conditions were carried out. The research results provide a new experimental method for the static and dynamic mechanical analysis of coal and rock masses under complex geological conditions and can provide a basic reference for the prevention and control of dynamic disasters in deep mining processes.

The occurrence of rock burst hazards is closely related to the brittleness of rocks. Current research has paid less attention to the in-depth relationship between rock brittleness and acoustic emission (AE) signal characteristics and precursor information caused by rock fracture. Therefore, in order to further improve the accuracy of the AE monitoring of rockburst hazards, uniaxial compression tests were carried out and AE were monitored for rocks with different brittleness (yellow sandstone, white sandstone, marble, and limestone) in this paper. The relationship between the mechanical properties and the time-frequency characteristics of the AE was analyzed. In addition, the multi-fractal theory was introduced to further deconstruct and mine the AE signals, and the multi-fractal characteristics of AE from rocks with different brittleness were investigated. The results show that the stronger the brittleness of the rock, the higher the main frequency and main frequency amplitude of the AE. Brittleness is positively correlated with the multi-fractal parameter Δα (uniformity of data distribution) and negatively correlated with Δf (frequency difference between large and small data). In addition, the dynamics of Δα and Δf provide new indicators for AE monitoring of rock stability, and their abrupt changes can be regarded as precursors of failure. The weaker the brittleness of the rock, the earlier the failure precursor is and the more significant it is. This has potential engineering application value, which can help identify rockburst precursors and take timely protective measures to ensure engineering safety.

Incipient fault detection in a hydraulic system is a challenge in the condition monitoring community. Existing research mainly monitors abnormal working conditions in hydraulic systems by separately detecting the key working parameter, which often causes a high miss warning rate for incipient faults due to the oversight of parameter dependence. A principal component analysis provides an effective method for incipient fault detection by taking the correlation of multiple parameters into consideration, but this technique assumes the systems are Gaussian-distributed, making it invalid for a dynamic non-Gaussian system. In this paper, we combine a canonical variable analysis (CVA) and adaptive kernel density estimation (AKDE) for the early fault detection of nonlinear dynamic hydraulic systems. The collected hydraulic system data set was used to construct the typical variable space, and the state space and residual space are divided to represent the characteristics of different correlations between the two variables, which are quantitatively described using Hotelling’s T2 and Q. In order to investigate the proper upper control limits, AKDE was utilised to estimate the underlying probability density functions of T2 and Q by taking the nonlinearity of the hydraulic system variables into consideration. The advantages of the proposed approach for incipient fault detection are illustrated via a marine power plant lubrication system.

In-situ coal bio-gasification can be defined as one of the coal bio-mining methodology that fully utilizes the methanogenic bacteria in coal to review the current findings, namely anaerobic digestion of organic components. The following experiment has been done in regards, one vertical well and one multi-branch horizontal well were used as experiment wells and two vertical wells were used as control wells, the pilot test was carried out with single well nutrition injection method. By applying the above mentioned method, the concentration of Cl− ion and number altered in Methanogen spp. were used to trace nutrition diffusion. Furthermore, technical implementation results analysis has been made with the observation of CH4 production changes and coal bed biome evolution.Gas production rates in each well were monitored by using the FLLQ gas roots flow mete. The concentration of CH4 and CO2 were evaluated by using the Agilent 7890A gas chromatograph, on the other hand, concentrations of Cl− were determined by the application of ICS-1100 ion chromatography system. The F420 fluorescence method was adopted to test for the presence of methanogenic bacteria. In the interim of the completion stage, the study stated that the bacterial diversity of underground water of Z-7H well has a high pass sequence with the experimental period of 814 days. Gas production data in Z-159 and Z-7H wells showed the gasification of coal lasted 635 and 799 days, yielded 74817 m3 and 251754 m3 coalbed methane, respectively. Furthermore, experimental data presented that one time nutrition injection in anthracite coalbed methane wells achieved an average of 717 days of continuous gas production among all experimental wells. The above fore-said study dedicated the significance of native bacterial fermentation, as it proven the fact that anthracite can be applied to accomplish coal bio-gasification and coalbed methane production stimulation in-situ.

A comprehensive understanding of the failure behavior and mechanism of coal is a prerequisite for dealing with dynamic problems in mining space. In this study, the failure behavior and mechanism of coal under uniaxial dynamic compressive loads were experimentally and numerically investigated. The experiments were conducted using a split Hopkinson pressure bar (SHPB) system. The results indicated that the typical failure of coal is lateral and axial at lower loading rates and totally smashed at higher loading rates. The further fractography analysis of lateral and axial fracture fragments indicated that the coal failure under dynamic compressive load is caused by tensile brittle fracture. In addition, the typical failure modes of coal under dynamic load were numerically reproduced. The numerical results indicated that the axial fracture is caused directly by the incident compressive stress wave and the lateral fracture is caused by the tensile stress wave reflected from the interface between coal specimen and transmitted bar. Potential application was further conducted to interpret dynamic problems in underground coal mine and it manifested that the lateral and axial fractures of coal constitute the parallel cracks in the coal mass under roof fall and blasting in mining space.

In order to study the detection effect of cotton boll opening after spraying defoliant, and to solve the problem of low efficiency of traditional manual detection methods for the use effect of cotton defoliant, this study proposed a cotton detection method improved YOLOv5x+ algorithm. Convolution Attention Module (CBAM) was embedded after Conv to enhance the network’s feature extraction ability, suppress background information interference, and enable the network to focus better on cotton targets in the detection process. At the same time, the depth separable convolution (DWConv) was used to replace the ordinary convolution (Conv) in the YOLOv5x model, reducing the convolution kernel parameters in the algorithm, reducing the amount of calculation, and improving the detection speed of the algorithm. Finally, the detection layer was added to make the algorithm have higher accuracy in detecting small size cotton. The test results show that the accuracy rate P (%), recall rate R (%), and mAP value (%) of the improved algorithm reach 90.95, 89.16, and 78.47 respectively, which are 8.58, 8.84, and 5.15 higher than YOLOv5x algorithm respectively, and the convergence speed is faster, the error is smaller, and the resolution of cotton background and small target cotton is improved, which can meet the detection of cotton boll opening effect after spraying defoliant.

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

The EP (electric potential) signals can be generated during the deformation and fracture process of coal and rock mass. Meanwhile, the EP response is closely related to its stress state and damage evolution, which is expected to be used in monitoring and coal and rock dynamic disaster hazards. Based on this, this paper developed an EP monitoring device for mining to continuously monitor the temporal response characteristics and spatial distribution of coal seam internal EP signals in real time. Further, the experimental tests were carried out, whose results showed that the device has high monitoring sensitivity and little error for the EP signals and can reveal the loading state and damage degree of the coal and rock specimens during the deformation and fracture process. Moreover, the tests and application of EP monitoring were carried out during mining activities in the field. The results showed that the EP signals fluctuate during the coal mining stage and remain relatively stable during the maintenance stage. When the abnormal mining stress or the coal cannon phenomenon occurs, the intensity of EP signals increases rapidly and fluctuates violently, which has precursory response information for the hazards of dynamic disasters. Considering the advantages of sensitive response and nearly non-destructive monitoring, the study results can provide key monitoring equipment and research basis for field testing the EP signals during the mining process, to monitor and forecast the hazards of coal and rock dynamic disasters.

The complex mechanical environment of deep coal and rock masses leads to obvious changes on their dynamic mechanical properties. However, there are few reports on the dynamic mechanical properties of rocks under the combined action of medium temperature (normal temperature ∼100°C) and static and dynamic loads. In this paper, a dynamic load and temperature combined action Hopkinson pressure bar experimental system is used to experimentally study the impact type of a fine sandstone under temperature conditions of 18°C, 40°C, 60°C, 80°C, and 100°C, an axial static load of 3 MPa, a gas chamber pressure of 0.06 MPa, and a constant temperature time of 4 h. The dynamic characteristics of the change law of the fine sandstone and the energy dissipation characteristics of the load process are analyzed, and the characteristic law of the fine sandstone surface response is analyzed using digital image correlation technology. Our results indicate the following. (1) Under conditions in which the other experimental conditions remain unchanged, the dynamic stress-strain of the fine sandstone presents a bimodal shape with a “rebound” phenomenon. Increasing temperature causes the peak strength of the fine sandstone to increase; however, the relative strength can increase or decrease. The relative increase in the strength is 1.14 MPa (°C) when the temperature increases from 40°C to 60°C, 0.15 MPa (°C) when the temperature increases from 60°C to 80°C, and 0.62 MPa (°C) when the temperature increases from 80°C to 100°C. (2) The digital image correlation results show that, under the action of a dynamic load stress wave, the fine sandstone experiences a displacement vector change on the sample surface; furthermore, under the combined action of the temperature and dynamic and static loads, the fine sandstone experiences macroscopic shear failure. The surface strain in the propagation direction of the stress wave is obviously higher and can even reach values of more than 10 times that of the strain in other directions. (3) From the perspective of energy dissipation, the incident energy, reflected energy, and dissipated energy of the fine sandstone under an impact load have the same change law. After being affected by a dynamic load, the energy rapidly increases to a certain value and then remains relatively stable. The transmitted energy is relatively small and can be approximated as a horizontal line. As the temperature increases, the incident energy, reflected energy, and dissipated energy tend to first decrease and then increase, and most of the incident energy in the fine sandstone is dissipated in the form of reflected waves.

In terms of coal’s stability and failure, soaking time and water content play a significant role in geotechnical engineering practice. To determine the soaking time effect on the mechanical behavior of coal samples and the response of AE (acoustic emission) signal throughout loading, the samples with different soaking times (0–120 hours (h)) were prepared and tested under uniaxial compression. AE signals were continuously monitored during loading to examine the AE characteristic response via the AEwin Express-8.0 system. The results revealed that the mechanical characteristics of the coal samples decreased with an increase in soaking time. When coal samples were subjected to uniaxial compression, AE events occurred due to the formation of the cracks, which further propagated to cause coal fracture. AE counts and the accumulative counts fluctuated with time and corresponded very well to the load. Therefore, AE counts and the trend of the accumulative counts of AE qualitatively explained the rupture of the coal under stress. In addition, the variation in trends of AE counts, AE accumulative counts, and load with time at various phases of all samples were obtained. It is concluded that AE counts increase suddenly during a slow increase phase and peak at the active increase phase. During the attenuation phase, the AE counts first decrease significantly with stress drop, but also a slight increase was observed due to the initiation of secondary cracks. These research results are of great significance as a precursor in coal and rock failure.

To evaluate the vibration effect caused by carbon dioxide phase-transition fracturing, the Hilbert–Huang transform was used to study the change of vibration energy with distance in different frequency bands. The results are drawn as follows: (1) The peak particle velocity (PPV) decreases as a power function with an increase in distance and has fallen below 25 mm/s at 2.8 m. (2) The energy of vibration signals induced by carbon dioxide phase-transition fracturing is mainly distributed at the frequency band of 10–50 Hz. With the increase in distance, the energy distribution of vibration signals falls in four phases: Propagation to high frequency (0–13.9 m); a rapid high-frequency energy decrease (20–30 m); energy fluctuation (30–47.2 m) and a stable energy distribution (larger than 50 m). (3) The proportion of the low-frequency vibration energy (0–10 Hz) increases as a result of the increase in distance (less than 8.7 m), which should be paid more attention.