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The effect of bolt support in mining roadways with fractured or weak surrounding rock is poor, and the roof easily loses stability. Studying the support control technology of bolts on fractured surrounding rock is necessary. Based on the theories of pressure arches and combined arch support, the bolt anchorage and anchorage effect angle are proposed a model is established, and the optimal bolt anchorage is calculated. The influence of related factors on the bolt anchorage and the scope of bolt action are analysed via numerical simulation and experimental methods. The pretightening force of the bolts and the spacing between the rows of bolts are positively correlated and negatively correlated with the bolt anchorage, respectively. The compression zone conforms to the reinforced arch state when the bolt end is anchored. The experimental work shows that the maximum spacing a of the anchor rods and the length L of the anchor rods in the surrounding rock satisfy 4.28a < 2L < 5a. The support of fractured surrounding rock is discussed, and the concept of roof fall prevention and control with an increasing or constant pretightening force, high surface strength and reasonable support density as the core principles is proposed. A field test of the Youzhong Coal Mine shows that the corresponding support effect is good and that this work provides a new method for roof support of fractured surrounding rock. [ABSTRACT FROM AUTHOR]

Microseismic data are widely employed for assessing rockburst risks; however, significant disparities exist in the monitoring capabilities of seismic networks across different mines, and none can capture a complete dataset of microseismic events. Such differences introduce unfairness when applying the same methodologies to evaluate rockburst risks in various mines. This paper proposes a method for assessing the monitoring capability of seismic networks applicable to heterogeneous media in mines. It achieves this by integrating three gradient boosting algorithms: Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost). Initially, the isolation forest algorithm is utilized for preliminary data cleansing, and feature engineering is constructed based on the relative locations of event occurrences to monitoring stations and the working face. Subsequently, the optimal hyperparameters for three models are searched for using 8508 microseismic events from the a Coal Mine in eastern China as samples, and 18 sub-models are trained. Model weights are then determined based on the performance metrics of different algorithms, and an ensemble model is created to predict the monitoring capability of the network. The model demonstrated excellent performance on the training and test sets, achieving log loss, accuracy, and recall scores of 7.13, 0.81, and 0.76 and 6.99, 0.80, and 0.77, respectively. Finally, the method proposed in this study was compared with traditional approaches. The results indicated that, under the same conditions, the proposed method calculated the monitoring capability of the key areas to be 11% lower than that of the traditional methods. The reasons for the differences between these methods were identified and partially explained. [ABSTRACT FROM AUTHOR]

Background: Coal mining requires safe and effective roadway support to ensure production and worker safety. Anchor support is a common method used for controlling the roof of coal seams. This study aims to analyze the effectiveness of different anchor support schemes and provide a theoretical basis for designing safe and effective roadway support. Methods: The authors used a computer simulation tool called FLAC3D to simulate and analyze the spacing between anchor bolts, anchor bolt length, anchor cable length, and effective roadway roof control, and support the schemes at the western wing roadway in the no. 15 coal seam of no. 1 mine of Ping'an Coal Mine. Results: The study found that using different combinations of anchor bolts and cables with varying lengths could effectively control the deformation of the roadway surrounding rock, depending on the spacing between layers of the coal seam. The most effective support schemes were recommended depending on the specific conditions. Conclusion: The study provides a theoretical basis for the design of anchor support in coal mines, which can ensure the safety of production and improve roadway stability. The results could be useful for other mining operations facing similar challenges in roadway support and stability. [ABSTRACT FROM AUTHOR]

Fractures have significant impact on the stability of underground projects such as coal mining. The identification of geological features based on drilling parameters is a promising option for intelligent detection of rock formations. A series of studies conducted to identify fractures under unstable drilling conditions are presented in this paper. First, the forces acting around the drill bit are analyzed to further improve the force model of the two-wing PDC drill bit. Then, based on the self-developed borehole drilling device, the drilling parameters are collected in real time while drilling in concrete of different strengths and different fracture widths. Finally, the response characteristics of drilling parameters are analyzed, and the multi-parameter voting method is proposed for fracture identification. The experimental results show that when fracture width increases, the crushing area, which forms around the borehole when the drill bit encounters the fracture, tends to increase. The rate of penetration (ROP) increases suddenly, the revolution per minute (RPM) decreases, and the torque increases at fracture encounter. The sudden changes are recovered after passing the fracture. The multi-parameter voting method has a high recognition rate for fractures of width greater than 2 mm, but a relatively low recognition rate for fractures of 1 mm width. In addition to detecting fractures, the method performs well in predicting fracture location and fracture width. Highlights: The response characteristics of multiple drilling parameters at the fracture were analyzed. As the thrust (torque) increases, the amount of change in penetration rate caused by the unit change in thrust (torque) decreases. Results show that the proposed multi-parameter voting method has a high recognition rate for fractures with width greater than 2 mm. [ABSTRACT FROM AUTHOR]

Sedimentary rocks provide information on previous environments on the surface of the Earth. As a result, they are the principal narrators of the former climate, life, and important events on the surface of the Earth. The complexity and cost of direct destructive laboratory tests adversely affect the data scarcity problem, making the development of intelligent indirect methods an integral step in attempts to address the problem faced by rock engineering projects. This study established an artificial neural network (ANN) approach to predict the uniaxial compressive strength (UCS) in MPa of sedimentary rocks using different input parameters; i.e., dry density (ρd) in g/cm3, Brazilian tensile strength (BTS) in MPa, and wet density (ρwet) in g/cm3. The developed ANN models, M1, M2, and M3, were divided as follows: the overall dataset, 70% training dataset and 30% testing dataset, and 60% training dataset and 40% testing dataset, respectively. In addition, multiple linear regression (MLR) was performed for comparison to the proposed ANN models to verify the accuracy of the predicted values. The performance indices were also calculated by estimating the established models. The predictive performance of the M2 ANN model in terms of the coefficient of determination (R2), root mean squared error (RMSE), variance accounts for (VAF), and a20-index was 0.831, 0.27672, 0.92, and 0.80, respectively, in the testing dataset, revealing ideal results, thus it was proposed as the best-fit prediction model for UCS of sedimentary rocks at the Thar coalfield, Pakistan, among the models developed in this study. Moreover, by performing a sensitivity analysis, it was determined that BTS was the most influential parameter in predicting UCS. [ABSTRACT FROM AUTHOR]

Coal-accompanying gas is an essential resource, with numerous mining methods. The practice has proved that injecting high-pressure air into the coal seam can replace and flush the gas in the coal seam, effectively solving the problem of inadequate single gas drainage in soft and low permeability coal seams. This paper uses the finite element method to solve the model, simulate and study the gas drainage by high-pressure air injection in the bedding drilling, and establish a fluid-structure coupling model for gas drainage by high-pressure air injection. The competitive adsorption of N2, O2, and CH4, diffusion and migration of CH4 in coal matrix and fissure, matrix deformation caused by CH4 adsorption, and desorption and control of coal deformation by applied stress are considered in the model. When the fixed extraction time is 600 days (d), the optimal spacing between the extraction hole and injection hole is 12.5 m. The safe extraction effect and minimum drilling amount can be ensured. It provides a basis for guiding gas drainage by injecting high-pressure air on-site. [ABSTRACT FROM AUTHOR]

In order to alleviate the relationship between mining and roadway, the 3204 working face and the 3206 roadway in Shanxi Taitou coal mine are taken as an example, and the width of mining and the support parameters of mining while reversing mining and excavation under dynamic pressure are optimized. The research includes field investigations, theoretical analysis, numerical simulation, and field tests. Based on the characteristics of roof fracture and the distribution of coal pillar stresses that determine the coal pillar is 18.7 m wide, the control scheme of mining while reversing mining and excavation was developed; the stress of coal pillar and the characteristics of roadway deformation and failure are summarized. By means of FLAC3D numerical simulation software, the influence of coal pillar widths and different mining positions on the stability of roadway surrounding rock are discussed. The asymmetric support structure of trapezoidal roadway is proposed as the core support, and the support scheme of dense bolts and anchor cables is proposed. The support of the 3206 return airway is composed of bolt, anchor cable, and anchor mesh, combined with M-shaped steel belt and steel beam. Through the research on the current situation of roadway support, the support scheme is optimized to make the 3206 return airway meet the production requirements, which provides a new breakthrough for roadway support under dynamic pressure in deep mines in China. [ABSTRACT FROM AUTHOR]

Elastic modulus (E) is a key parameter in predicting the ability of a material to withstand pressure and plays a critical role in the design of rock engineering projects. E has broad applications in the stability of structures in mining, petroleum, geotechnical engineering, etc. E can be determined directly by conducting laboratory tests, which are time consuming, and require high-quality core samples and costly modern instruments. Thus, devising an indirect estimation method of E has promising prospects. In this study, six novel machine learning (ML)-based intelligent regression models, namely, light gradient boosting machine (LightGBM), support vector machine (SVM), Catboost, gradient boosted tree regressor (GBRT), random forest (RF), and extreme gradient boosting (XGBoost), were developed to predict the impacts of four input parameters, namely, wet density (ρwet) in gm/cm3, moisture (%), dry density (ρd) in gm/cm3, and Brazilian tensile strength (BTS) in MPa on output E (GPa). The associated strengths of every input and output were systematically measured employing a series of fundamental statistical investigation tools to categorize the most dominant and important input parameters. The actual dataset of E was split as 70% for the training and 30% for the testing for each model. In order to enhance the performance of each developed model, an iterative 5-fold cross-validation method was used. Therefore, based on the results of the study, the XGBoost model outperformed the other developed models with a higher accuracy, coefficient of determination (R2 = 0.999), mean absolute error (MAE = 0.0015), mean square error (MSE = 0.0008), root mean square error (RMSE = 0.0089), and a20-index = 0.996 of the test data. In addition, GBRT and RF have also shown high accuracy in predicting E with R2 values of 0.988 and 0.989, respectively, but they can be used conditionally. Based on sensitivity analysis, all parameters were positively correlated, while BTS was the most influential parameter in predicting E. Using an ML-based intelligent approach, this study was able to provide alternative elucidations for predicting E with appropriate accuracy and run time at Thar coalfield, Pakistan. [ABSTRACT FROM AUTHOR]

The coal-bed methane (CBM) resources in soft and low-permeability coals are assumed to be as much as 15 × 1012 m3 in China. Indirect fracturing technology can be an effective method to successfully extract methane within soft coals. The key to the success of this technique is to optimize the parameters, such as water injection flow rate and fracture initiation location, so that the hydraulic fracturing parameters enable the fractures to pass through the interface between coal and rock and propagate sufficiently into the coal. This paper focuses on solving the above problems by focusing on discontinuities and plastic characteristics of soft coals. Voronoi polyhedron was used to simulate the discontinuities of coal, and the constitutive relations of ductile fracture-seepage and elastoplastic damage-seepage are, respectively, given to the discontinuities and coal matrix. A numerical model was established based on the above theory to simulate the effect of stress difference Δσ, coal-rock interface friction coefficient fc,r, water injection flow rate i w , and distance between the well and the interface Dop on indirect fracturing fractures. The results show that the HFs area in the coal is positively correlated with Δσ, fc,r, and i w , and it first increases and then decreases with the decrease of Dop. The above results were applied in the Zhaozhuang mine of Qinshui Basin by optimizing Dop = 1 m and iw = 8 m3/min, so that CBM production has been greatly increased. The results can provide theoretical support for the efficient development of CBM in fractured and low-permeability coal seam areas. [ABSTRACT FROM AUTHOR]

Uniaxial compressive strength (UCS) and elastic modulus (E) are the fundamental parameters in rock engineering and rock structure designs. The laboratory-based direct measuring of UCS and E according to the recommended International Society for Rock Mechanics (ISRM) and American Society for Testing and Materials (ASTM) standards is complicated, time-consuming, and expensive process involving sample destruction. Likewise, preparation of the required core samples in case of weak, internally damaged, thin, and highly foliated rock is quite difficult. Therefore, the indirect assessment of UCS and E by employing the rock index tests is need of the day. In this study, firstly UCS in MPa, E in GPa, wet density (ρѡet) in g/cm3, dry density (ρd) in g/cm3, and Brazilian tensile strength (BTS) in MPa were measured. Next, the adaptive neuro-fuzzy interference system (ANFIS), artificial neural network (ANN), and multiple linear regression (MLR) models were used to predict the UCS and E of soft sedimentary rocks collected from Block-IX Thar Coalfield. The estimated UCS and E results were compared with their actual values. The performance of ANFIS model for UCS and E shows the most powerful prediction with the strongest coefficient of determination (R2), minimum root mean squared error (RMSE), and the highest variance accounts (VAF) of 0.93 and 0.85, 0.16939 and 0.24702, and 0.96 and 0.91, and 0.95 and 0.91, 0.06938 and 0.03294, and 0.99 and 0.97 at the training and testing stages of the data, respectively. Finally, through the prediction index (PImod) performance test, the accuracy of the proposed models was further improved, which also shows that the prediction accuracy of the ANFIS model is the best among all the models used. [ABSTRACT FROM AUTHOR]

Drilling rate index (DRI) is a fundamental parameter in the investigation of rock drillability, as drillability is considered one of the main problems in rock engineering. Several researchers have continuously tried to analyze and correlate rock DRI, but the problem remains unchanged. This study elucidates the machine learning approaches, namely long short term memory (LSTM), simple recurrent neural network (RNN) and random forest algorithm (RFA) to predict DRI of rocks using multivariate inputs, that is, uniaxial compressive strength in MPa; Brazilian tensile strength (BTS) in MPa; brittleness value (S20); Sievers' J value (Sj); modulus ratio (MR); shore hardness (SH), porosity (n) in %; shimazeks F abrasitivity in N/mm; and equivalent quartz content in %. For all proposed methods, the original dataset was divided into 70% for training and the remaining 30% for testing. Next, the performance indices, such as correlation coefficient (R2), root mean square error (RMSE), variance accounts for (VAF) and a-20 index of each proposed method were determined to examine the accuracy of the predicted data. In this study, according to the results of LSTM, simple RNN and RFA methods, the LSTM revealed the best prediction output for DRI with the strongest R2, the lowest RMSE, the largest VAF and an appropriate a-20 index values as 0.999, 0.13416, 0.997, and 0.999 in the training stage and 0.998, 0.19479, 0.996, and 0.997 in the testing stage, respectively. Therefore, LSTM is an applicable machine learning approach that can be applied to accurately predict the DRI. [ABSTRACT FROM AUTHOR]

In the traditional edge detection models, due to the influence of artifact, occlusion and other factors, the detection efficiency is poor and the error is large, which affects the subsequent image processing. Therefore, this paper proposes a new edge detection method based on Gaussian positive-negative radial basis neural network (GPNRBNN). Firstly, a novel GPNRBNN is constructed in this paper. Each pixel preprocessed by Gaussian filter in the image is taken as the central point of the GPNRBNN and input into the neural network. Then, the weight sharing and sparse connection in the convolutional neural network are used for processing the pixels. The results are output after the calculation in the extended layer and the hidden layer. Thirdly, the edge is extracted by contour tracking according to the output results. Finally, experiments are conducted on the composite image, part of the uneven gray image and medical images etc. Compared with other models, the efficiency of the proposed model is improved, and the edge connectivity is better. [ABSTRACT FROM AUTHOR]

Compared to traditional couplings, the multiple corrugated diaphragm (MCD) coupling has the advantages of high torque diameter and weight ratios, and high compensation capability. Due to the irregularity of the MCD, it is difficult to analyze and study it through traditional methods. In this paper, an analytical method for calculating the axial stiffness of MCDs is derived based on the mechanical theory of corrugated circular plates, and the results of the analytical method, finite element method, and stiffness tests are compared. The results indicate that the analytical solution of the MCD axial stiffness is consistent with the finite element analysis and experimental results. This proves the feasibility of analyzing the MCDs using the theory of corrugated annular plates. This study provides a theoretical basis for the design of MCD coupling and can guide the rapid design of MCD coupling. [ABSTRACT FROM AUTHOR]

The uniaxial compressive strength (UCS) of rock is one of the essential data in engineering planning and design. Correctly testing UCS of rock to ensure its accuracy and authenticity is a prerequisite for assuring the design of any rock engineering project. UCS of rock has a broad range of applications in mining, geotechnical, petroleum, geomechanics, and other fields of engineering. The application of the gradient boosting machine learning algorithms has been rarely used, especially for UCS prediction, and has performed well, based on the relevant literature of the study. In this study, four gradient boosting machine learning algorithms, namely, gradient boosted regression (GBR), Catboost, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost), were developed to predict the UCS in MPa of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan, using four input variables such as wet density (ρw) in g/cm3; moisture in %; dry density (ρd) in g/cm3; and Brazilian tensile strength (BTS) in MPa. Then, 106-point dataset was allocated identically for each algorithm into 70% for the training phase and 30% for the testing phase. According to the results, the XGBoost algorithm outperformed the GBR, Catboost, and LightGBM with coefficient of correlation (R2) = 0.99, mean absolute error (MAE) = 0.00062, mean square error (MSE) = 0.0000006, and root mean square error (RMSE) = 0.00079 in the training phase and R2 = 0.99, MAE = 0.00054, MSE = 0.0000005, and RMSE = 0.00069 in the testing phase. The sensitivity analysis showed that BTS and ρw are positively correlated, and the moisture and ρd are negatively correlated with the UCS. Therefore, in this study, the XGBoost algorithm was shown to be the most accurate algorithm among all the investigated four algorithms for UCS prediction of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan. [ABSTRACT FROM AUTHOR]

The gob-side entry retaining plays an important role in improving working face ventilation, alleviating working face connection, and increasing mining revenue. According to the characteristics of the crossheading roof at the 2103 working face of a mine in Shanxi, a structural mechanics model of the roof was established to derive the theoretical formulae for the ultimate hanging arch length of the layered roof with anchors and the initial support resistance of the entry-side support. The influence factors of the ultimate hanging arch length were evaluated using local sensitivity analysis. Based on the theoretical study, the work proposed the collaborative support technology of the crossheading, collaborative support at the 2103 working face. The results showed that the ultimate hanging arch length was most influenced by the width of the plastic zone, followed by the width of the roadway, supporting strength, anchoring strength, layered thickness, and mining depth, while the ultimate tensile strength had little influence. The initial support resistance of the entry-side supports was closely related to the ultimate hanging arch length and the process of gob-side entry retaining. The improved entry-retaining supporting process could control the sharp surface convergence of the surrounding rocks of the entry retaining, the sinkage of the roof of the entry-retaining section was controlled below 100 mm, and that of the advanced section was controlled below 50 mm. The stability of the supports next to the entry is improved, and the needs of the site project are met. [ABSTRACT FROM AUTHOR]

In the traditional edge detection models, due to the influence of artifact, occlusion and other factors, the detection efficiency is poor and the error is large, which affects the subsequent image processing. Therefore, this paper proposes a new edge detection method based on Gaussian positive-negative radial basis neural network (GPNRBNN). Firstly, a novel GPNRBNN is constructed in this paper. Each pixel preprocessed by Gaussian filter in the image is taken as the central point of the GPNRBNN and input into the neural network. Then, the weight sharing and sparse connection in the convolutional neural network are used for processing the pixels. The results are output after the calculation in the extended layer and the hidden layer. Thirdly, the edge is extracted by contour tracking according to the output results. Finally, experiments are conducted on the composite image, part of the uneven gray image and medical images etc. Compared with other models, the efficiency of the proposed model is improved, and the edge connectivity is better. [ABSTRACT FROM AUTHOR]

Measurement while drilling is an important part of the intelligent development of coal mines. The main purpose of this paper is to comprehensively analyze the response characteristics of borehole drilling parameters and find a better method to predict rock mechanical properties based on drilling parameters. Firstly, six concrete blocks and multiple specimens were prepared with different material ratios. Next, the concrete specimens were tested for mechanical properties in the laboratory. Meanwhile, the displacement, rotation speed, torque, and sound pressure level (SPL) were observed during the drilling of the concrete blocks. Finally, the response characteristics of drilling parameters such as rotation speed, rate of penetration (ROP), torque, and SPL were analyzed. Besides, multiple prediction models of rock mechanical parameters were obtained by data analysis. The research results indicate that the drilling process can be classified into the initial stage of drilling (fast speed) and the steady stage of drilling (slow speed). The torque work ratio accounts for more than 99%, which increases with the increase in rock strength. The penetration depth per revolution and torque work ratio are significantly related to rock uniaxial compressive strength, Brazilian tensile strength, cohesion, and elastic modulus. The ROP is the best choice for estimating rock mechanical parameters. This research provides an important reference for laboratory rock mechanics parameter testing and geological features detection based on drilling parameters. [ABSTRACT FROM AUTHOR]

This work elucidates dynamic control equations of the anchoring system and the derivation of displacement equations and corresponding vibration modes. Furthermore, the anchoring system is found to be composed of three different vibration modes: (1) when ω < (k1/ρ1A1)1/2, the vibration mode of the anchoring section is an exponential function; (2) when ω = (k1/ρ1A1)1/2, the vibration mode of the anchoring section is a parabolic function; (3) when ω > (k1/ρ1A1)1/2, the vibration mode of the anchoring section is a trigonometric function, while all the free sections are trigonometric functions. With an increase of frequency, the amplitude of the bolt exhibits multipeak distribution characteristics and an intermittent amplification phenomenon. When the frequency reaches a certain value, the bolt of the free section exhibits only the amplified state. Under dynamic load, the amplitude of the bolt increases from end of bolt to the maximum in the root. On the other hand, when the frequency is low, the peak position of the roof bolt is stable, and the excitation wave component is the main influencing factor of the peak value of axial force at the root of the bolt, independent of frequency. When the frequency is relatively high, the peak value of the axial force is stable at the interface, and the higher the frequency, the greater the peak value of axial force. Axial force of the bolt has responded strongly to the frequency at the interface, and the farther away from the interface, the weaker the response. [ABSTRACT FROM AUTHOR]

The control system of parallel robot, especially industrial robot, is a very complex multi-modal nonlinear system, which has the characteristics of time-varying, strong coupling and strong nonlinearity. Trajectory tracking control algorithm is a very important part of industrial robot control system. It is required that the algorithm can realize the continuous tracking of each joint of the robot and the processing and tracking of the desired trajectory. However, due to the strong influence of acceleration and speed on the trajectory tracking of industrial robots, the corresponding control difficulty and control accuracy are seriously affected. Based on the core idea of fuzzy neural network algorithm, the functional relationship between control error and arrival degree is established to improve the control quality of industrial robots. At the same time, combining with the PID feedforward control algorithm, the self-adaptive adjustment of PID parameters is realized, and the accuracy of the tracking algorithm is improved. In order to verify the superiority of the proposed trajectory tracking control algorithm over the traditional PID algorithm, the model of industrial robot is established by using the virtual simulation system Adams. At the same time, the model is simulated by joint experiment. Experimental results show that the trajectory control algorithm based on the proposed trajectory control algorithm is effective. This method has good control accuracy and stability. [ABSTRACT FROM AUTHOR]

At present, Measurement While Drilling (MWD) for detection of the roof rock stratum characteristics is mainly focused on numerical simulation and laboratory research, and the research results are somewhat different from the field experimental results. In order to achieve accurate prediction of the interface position of different rock layers, data acquisition of drilling displacement was performed by Laser displacement sensor in the field experiment. The sinusoidal model of MATLAB is used to fit the displacement, and the penetration rate model and the longitudinal vibration model are established by clustering to analyze the drilling response of different strength rock formations. Finally, the two models established were applied to investigate the position of rock interfaces in a drill hole by clustering. It is revealed that drilling process is cyclical, and the penetration rate processed in the field experiment is consistent with the laboratory and numerical simulation penetration rate. The dynamic response of penetration rate and longitudinal vibration for rock with different strength is an important indicator for identifying rock formations. [ABSTRACT FROM AUTHOR]

Based on the geological conditions of soft-rock roadway with a buried depth of 1336 m and the data that are achieved by various experimental methods, the multi-factor coupling analysis of the instability mechanism of soft-rock roadway is carried out through theoretical analysis and numerical simulation. Additionally, following the Nishihara model and Drucker–Prague's modification of Mohr–Coulomb yield condition, the stability control theory of soft-rock coal roadway is analyzed. By fully considering the bearing capacity of each supporting component, the original supporting structure is innovatively examined with crush tube, spherical tray, high-strength bar and steel strip to form a flexible and high-performance bolt supporting structure, and the stability control of 1336 m soft-rock coal roadway is also comprehended. Therefore, the studies have shown that the convergence trend of omnidirectional, strong rheological and large deformation constitutes the essential characteristics of deep soft-rock roadway deformation. The instability process of roadway surrounding rock is accompanied by "domino-effect" similar to that of multi-factor coupling. The irrational design of the support scheme and the destruction of the support structure are the external factors of this effect, although the prominent contradiction between high in-situ stress and the weak bearing capacity of the deep degraded rock mass is the internal factors of this effect. Similarly, the engineering practice and observation data of the new scheme have shown that the deformation coordination of support components and the matching degree of bearing characteristics should be one of the main factors to be considered in the design of deep soft-rock roadway support, high elongation and multiple adjustable characteristics to adapt to the basic characteristics of deep soft-rock roadway deformation. Hence, the construction idea of the new scheme has contributed the satisfactory engineering significances and reference value for optimizing the stress environment of soft-rock roadway and further reducing the support cost. [ABSTRACT FROM AUTHOR]

Underground rock masses have shown a general trend of natural balance over billions of years of ground movement. Nonetheless, man-made underground constructions disturb this balance and cause rock stability failure. Fractured rock masses are frequently encountered in underground constructions, and this study aims to restore the strength of rock masses that have experienced considerable fracturing under uniaxial compression. Coal and sandstone from a deep-buried coal mine were chosen as experimental subjects; they were crushed by uniaxial compression and then carefully restored by a chemical adhesive called MEYCO 364 with an innovative self-made device. Finally, the restored specimens were crushed once again by uniaxial compression. Axial stress, axial strain, circumferential strain, and volumetric strain data for the entire process were fully captured and are discussed here. An acoustic emission (AE) testing system was adopted to cooperate with the uniaxial compression system to provide better definitions for crack closure thresholds, crack initiation thresholds, crack damage thresholds, and three-dimensional damage source locations in intact and restored specimens. Several remarkable findings were obtained. The restoration effects of coal are considerably better than those of sandstone because the strength recovery coefficient of the former is 1.20, whereas that of the latter is 0.33, which indicates that MEYCO 364 is particularly valid for fractured rocks whose initial intact peak stress is less than that of MEYCO 364. Secondary cracked traces of restored sandstone almost follow the cracked traces of the initial intact sandstone, and the final failure is mainly caused by decoupling between the adhesive and the rock mass. However, cracked traces of restored coal only partially follow the traces of intact coal, with the final failure of the restored coal being caused by both bonding interface decoupling and self-breakage in coal. Three-dimensional damage source locations manifest such that AE events are highly correlated with a strength recovery coefficient; the AE events show a decreasing tendency when the coefficient is larger than 1, and vice versa. This study provides a feasible scheme for the reinforcement of fractured rock masses in underground constructions and reveals an internal mechanism of the crushing process for restored rock masses, which has certain instructive significance. [ABSTRACT FROM AUTHOR]

Bolt supports within stratified strata in coal mines contribute to the unique characteristics of low-buried engineering structures such as tunnels or subways. Failure at the bolt interface is the main trigger of support failure in such settings. This paper comprehensively investigates the serial decoupling mechanism at a resin-rock interface, which is a process that occurs frequently in stratified strata. There are, however, different evolutionary processes that exist at the interface, from a total bonding stage to a plastic bonding stage, a slippage plastic bonding stage, a slippage plastic stage and a total slippage stage, sequentially. These processes accelerate the shortening speed of anchor life, whereupon axial force will fluctuate at each stage and corresponding equations can be derived successfully. Finally, a long-term field monitoring test which verifies the theoretical results and effective measures, such as pregrouting, can be used to prevent serial decoupling. The service life of the bolt system also can be prolonged. [ABSTRACT FROM AUTHOR]

A limitation in research on bolt anchoring is the unknown relationship between dynamic perturbation and mechanical characteristics. This paper divides dynamic impulse loads into engineering loads and blasting loads and then employs numerical calculation software FLAC3D to analyze the stability of an anchoring system perturbed by an impulse load. The evolution of the dynamic response of the axial force/shear stress in the anchoring system is thus obtained. It is revealed that the corners and middle of the anchoring system are strongly affected by the dynamic load, and the dynamic response of shear stress is distinctly stronger than that of the axial force in the anchoring system. Additionally, the perturbation of the impulse load reduces stress in the anchored rock mass and induces repeated tension and loosening of the rods in the anchoring system, thus reducing the stability of the anchoring system. The oscillation amplitude of the axial force in the anchored segment is mitigated far more than that in the free segment, demonstrating that extended/full-length anchoring is extremely stable and surpasses simple anchors with free ends. [ABSTRACT FROM AUTHOR]

A monitoring trial was carried out to investigate the effect of boreholes configuration on the stability and gas production rate. These boreholes were drilled from the retaining roadway at longwall mining panel 1111(1) of the Zhuji Coalmine, in China. A borehole camera exploration device and multiple gas parameter measuring device were adopted to monitor the stability and gas production rate. Research results show that boreholes 1~8 with low intensity and thin casing thickness were broken at the depth of 5~10 m along the casing and with a distance of 2~14 m behind the coal face, while boreholes 9~11 with a special thick-walled high-strength oil casing did not fracture during the whole extraction period. The gas extraction volume is closely related to the boreholes stability. After the stability of boreholes 9~11 being improved, the average gas flow rate increased dramatically 16-fold from 0.13 to 2.21 m3/min, and the maximum gas flow rate reached 4.9 m3/min. Strengthening boreholes configuration is demonstrated to be a good option to improve gas extraction effect. These findings can make a significant contribution to the reduction of greenhouse gas emissions from the coal mining industry. [ABSTRACT FROM AUTHOR]

The traditional anchoring method of bolts has insufficient control over the surrounding rock of the coal roadway. Based on this background, full-stress anchoring technology of bolts was proposed. Firstly, a mechanical relationship model of a bolt-drawing, anchoring interface was established to obtain the equations of the axial force and obtain shear stress distribution as well as the decreasing-load transfer law of the anchoring section of bolts. Through studying the prestress-loading experimental device of bolts, we found that increasing the initial preload could increase the axial force under the same conditions and the retarded anchoring section could control the axial-force loss of bolts in the middle of the anchoring section. Under the full-stress anchoring mode, the effect of applying a pre-tightening force was better than that of applying a pre-tightening force under traditional anchoring methods. Moreover, FLAC3D (Fast Lagrangian Analysis of Continua 3D; ITASCA (Ita sca International Inc), Minnesota, USA) numerical simulation calculation was performed. Under the full-stress anchoring mode of bolts, the increased anchoring length reduced the damage of the anchoring section, with a wider control range of the rock formation and higher strength of the compressive-stress anchoring zone. Based on the above research, four methods for applying the full-stress anchoring technology of bolts in engineering were proposed. The full-stress anchoring technology of bolts in the coal roadway has been applied in the support project of the return-air roadway at working face 3204 of the Taitou Coking Coal Mine of the Xiangning Coking Coal Group, Shanxi. The maximum moving distance of the roof and floor of the roadway was reduced from 200 to 42 mm, and the maximum moving distance on both coal sides was reduced from 330 to 86 mm. The full-stress anchoring technology of bolts was able to control the surrounding rock in the coal roadway. [ABSTRACT FROM AUTHOR]

Research on drilling response characteristics of two-wing polycrystalline diamond compact (PDC) bit in different rocks is an important way to further understand the mechanism of rock-breaking, improve drilling efficiency, and identify the rock formation interfaces in coal mines. However, the research on the drilling response characteristics of two-wing PDC bits is relatively rare due to the harsh environment in coal mines. In this study, a series of two-wing PDC bits were used to drill in sandstone and sandy mudstone to study the response characteristic of sound pressure level, displacement curves, longitudinal vibration, and rock cuttings size. The collected data were processed by MATLAB based on the 3σ principle. The cuttings were collected through a newly designed cuttings collection device. The experimental results show that the sound pressure level and the longitudinal vibration are larger when drilling in the higher strength sandstone, which is opposite to the cuttings particles and the penetration rate. The reduction of drilling efficiency is more obvious when drilling in sandstone with a worn bit. Therefore, drilling efficiency can be improved by optimizing the bit structure so that the broken rock blocks flow out of the anchor holes as early as possible to avoid being broken into cuttings. [ABSTRACT FROM AUTHOR]

Understanding the acoustic emission effects on bolts under cyclic loading is of great significance for the support of roadways. The presented research focuses on the acoustic emission characteristics of bolts under cyclic loading. The following main conclusions were drawn: (1) With a higher loading frequency, the acoustic emission counts rate increases, while the total energy released in a given cyclic loading path decreases. (2) A fitting formula is established according to the relationship between the tension amplitude and cumulative acoustic emission counts, which can analyze the tension magnitude level of the cyclic load. (3) A damage factor for a cyclic load is proposed based on the acoustic emission counts generated during the cyclic and monotonic loading process that can analyze the degree of damage to the anchorage system caused by the cyclic load. (4) Based on the spatial distribution of the acoustic emission orientation points and the acoustic emission energy generated during the pull-out process, the acoustic emission damage evolution process of the anchorage specimens is deduced, and the mechanism of the high stability of the pretension anchorage system after cyclic loading is analyzed. The above conclusions may provide some experimental references for the application of acoustic emission technology in bolts supporting roadways. [ABSTRACT FROM AUTHOR]