Abstract:Open-pit coal mining is a complex system involving multiple intersecting processes,whose three-dimensional dynamic spatiotemporal evolution requires scientific planning.However,due to the lack of a temporal sequencing plan-ning method,mining plans still rely on manual preparation,resulting in crude planning and frequent adjustments to pro-duction decisions.To establish an optimal material extraction sequence plan within the closed spatiotemporal field of open-pit mines,this study analyzes the impact of flow direction and flow rate planning of coal and rock block models on min-ing plan optimization.By incorporating transportation costs into the economic value attributes of block models and aim-ing to maximize total net present value(NPV),a mixed-integer programming(MIP)optimization model is developed,con-sidering various complex constraints.To address the limitations of the traditional GWO algorithm in terms of conver-gence and local extremum avoidance when solving the MIP optimization model,an improved GWO algorithm is pro-posed.The enhanced algorithm integrates circle chaotic mapping to increase population diversity,introduces a nonlinear update mechanism for parameter adjustment,and employs an individual information-sharing strategy to enhance global search capabilities.Simulation experiments verify the correctness of the proposed model and algorithm.Using the Baorix-ile open-pit coal mine as a case study,the material flow direction and flow rate for block models from 2024 to 2028 are planned,and the corresponding mining plan is developed.The results demonstrate that the optimized plan increases total NPV by 5.27%and improves efficiency by 19 times compared to traditional manually prepared plans.The developed plan-ning model and improved algorithm significantly enhance the scientific rigor and economic efficiency of open-pit mining plans,providing theoretical support for automated decision-making in open-pit coal mining.

Abstract:At present,TBM(Tunnel Boring Machine)has been widely adopted in major national tunneling projects such as highways,railways and water conservancy,and it has been gradually used in coal mine roadway excavation.During shield tunneling operations,the deployment of geophysical advanced detection techniques is imperative to mitigate water inrush hazards associated with concealed water-bearing structures.However,when TBM completely occupies the tunnel space,there is no construction space for conventional transient electromagnetic advanced detection.To address this tech-nical challenge,this study proposes a surface-tunnel transient electromagnetic-while-tunneling advanced detection method in TBM tunnels,in which one fixed electrical source is laid on the surface,and eight electrodes are mounted on the shell of TBM to form a multi-component observation array for coordinated observing the transient electric field in the surrounding rock.Geophysical models for surface-tunnel transient electromagnetic-while-tunneling advanced detection of electrical source are established.Numerical simulations of the spatiotemporal distribution of subsurface transient electric fields of electrical source are performed using the finite-element method with unstructured tetrahedral meshes.The results show that:When the electrical source is perpendicular to the excavation direction and its midpoint deviates a certain distance from the tunnel axis,three-component transient electric fields are successfully acquired,and anomalous responses induced by low-resistivity anomalous body can be observed around the tunnel.The x-direction electric field is more sensitive to the spatial position change of the low-resistance anomalous body,and the position is qualitatively interpreted through the combination of anomalous responses characteristics of six electric field components.The y-direction and z-direction elec-tric fields are more sensitive to the distance change between the low-resistance anomalous body and the excavation face,and analyzing amplitude changes of these electric fields enables detection of distant low-resistivity anomalous body.With a 5%amplitude difference as the detection threshold,a detection range of 60 m is achievable for a low-resistance anomal-ous body measuring 50 m×50 m×10 m with a resistivity ratio of 1∶100 to the surrounding rock.This research provides a new approach for the realization of tunneling-exploration integration in TBM tunnels,and offers a theoretical basis for the surface-tunnel transient electromagnetic-while-tunneling advanced detection.However,a systematic processing-interpreta-tion methodology has not been established.Future work will focus on correcting strong electromagnetic interference from TBM and deriving the formula of subsurface whole space apparent resistivity.

Abstract:Salinity waste water is characterised by complex pollution components,high treatment costs and difficulties,and improper treatment can cause serious ecological damage.Incineration is a harmless disposal method of salinity waste water,but because the alkali metal salts in salinity waste water may cause the ash melting temperature to decrease,result-ing in corrosion of incineration equipment and accumulation of ash slag and other problems.Therefore,it is necessary to study the effects and mechanisms of common salts in saline wastewater and coal blending combustion process on the melt-ing characteristics of coal ash.Three common salts NaCl,Na2SO4,and NaNO3 from saline wastewater were loaded into two kinds of combustion coals by impregnation method and ash production was carried out at a temperature of 815℃ to obtain ash samples from different coal samples.Ash melting point tests were performed for ash samples loaded with dif-ferent sodium salts.It was found that under 3%sodium salt blending ratio,NaCl,Na2SO4 and NaNO3 blending will signi-ficantly reduce the coal ash melting temperature,resulting in coal ash slagging.The deformation and softening temperat-ures of coal 1 were both highest when loaded with Na2SO4 and lowest when loaded with NaCl.Meanwhile,after loading the three sodium salts on Coal 1,Rz was greater than 2.5,and all of them had a tendency to severe slagging.Effect of NaCl on the ash melting temperature is particularly significant,and it will produce by-products of HCl,resulting in the corro-sion of heated surfaces,and the effects of Na2SO4 and NaNO3 on different coal types are slightly different.In addition,the elemental composition of the ash samples showed an increase in the total content of the alkali metal elements Na,Fe,and Ca in the ash particles as compared to that in the absence of sodium salt loading.According to the scanning electron mi-croscopy and X-ray diffraction analysis,there was an obvious bonding phenomenon between coal 1 ash-NaCl particles and particles,and low melting point substances such as NaAlSiO4 and KNa3(AlSiO4)4 were also generated in the ash samples,and they may further form a low-temperature eutectic,which resulted in the susceptibility to slagging during the combus-tion process of the NaCl-loaded coal samples.Therefore,when the concentrate or crystallized salt of salt-containing wastewater and coal are mixed and burned,the mixing ratio must be strictly controlled,especially for wastewater with high NaCl content.

Abstract:The traveltime and ray path of seismic waves are key parameters in seismic data processing,and the accuracy,efficiency and stability of their calculation directly affect the imaging accuracy and analytical capabilities of seismic waves.However,traditional algorithms exhibit deficiencies in computational efficiency and accuracy.To address these de-ficiencies,a ray tracing method based on Multipoint Spline Traveltime Interpolation(MSTI)is introduced.Theoretical cal-culations and analyses show that the traveltime curve obtained through the MSTI method closely matches the actual travel-time curve,significantly outperforming traditional approaches such as Linear Traveltime Interpolation(LTI)and Parabola Traveltime Interpolation(PTI).In numerical simulation,both uniform and vertical gradient velocity models are construc-ted.The results indicate that:① The traveltime calculated using the MSTI method is closer to the theoretical traveltime,and even with fewer nodes,the computational accuracy surpasses that of the LTI method;② When the number of interpol-ation nodes at the element boundaries is the same,calculation accuracy improves as the discrete elements are refined;③ When the size of the discrete element is fixed,increasing the number of nodes significantly enhances the traveltime ac-curacy of the MSTI method,while the improvement in the LTI method accuracy is marginal;④ In the vertical gradient velocity model,the traveltime calculated using Snell's law is closer to the theoretical traveltime,and increasing the num-ber of nodes significantly improves the accuracy of the MSTI method,while the improvement in the LTI method accuracy tends to stagnate.To further verify validate the effectiveness of the MSTI method,a comparative analysis of inversion res-ults for different anomalies is conducted.The tomographic imaging technique based on the MSTI method accurately loc-ates different anomalies,demonstrating the method's superiority.Field test results indicate that the inversion of velocity anomalies using the 2.5D curved ray tracing tomographic imaging algorithm based on the MSTI method closely matches the spatial positions of the faults exposed during mining practice,providing robust technical support for the safe and effi-cient production of coal mines.

Abstract:The geological structure of coal mines in China is complex,and precise detection of coal seam thickness and orientation is crucial for intelligent and safe mining operations.Conventional geophysical ahead-detection methods suffer from continuously expanding detection errors in coal-rock structure identification with increasing advance distance.Moreover,most borehole geophysical exploration equipment exhibits limited effectiveness in coal thickness identification due to inadequate directional capability.To address these challenges,a mine directional borehole radar is developed.Dir-ectional identification of coal seam thickness is realized through the integration of a directional radar antenna,a high-pre-cision PWM motor speed control system,an angular and directional perception system,and positioning and calculation al-gorithms.A spatial relationship model between the directional borehole radar antenna and the target body is constructed,enabling precise perception of the target detection direction.The azimuth angle perception error is minimized to 1°(when motor speed is lower than 3.71 r/min).A study on coal thickness identification using directional borehole radar and ima-ging accuracy analysis is conducted to provide guidance for on-site radar operation and development of in-situ drilling de-tection equipment.Firstly,the working principle of the directional borehole radar and coal thickness detection method are systematically elaborated.Secondly,following clarification of the relationship between PWM duty cycle and motor speed,experiments with different PWM duty cycles are designed to study and analyze the impact of motor speed on acquisition accuracy.It is found that when data sampling accuracy error is within 2%,the optimal motor speed is 7.84 r/min.In view of the current situation where advancement speed of conventional mining drilling machines is approximately 0.01-0.30 m/s,a series of detection experiments with different advancement speeds ranging from 0.05-0.40 m/s are designed.The influence laws of detection speed on sampling accuracy and of collection accuracy on imaging accuracy are analyzed and clarified in detail.The experimental results show that under current tunnel drilling machine working conditions in mines,when the directional borehole radar acquisition speed is 7.84 r/min and detection advance speed is 0.05 m/s,the angle acquisition accuracy error rate is minimized to 2.8%,acquisition positioning accuracy of 97.2%is obtained,and tar-get body identification resolution of 0.256 m is achieved.In mine measurement results,the coal-rock interface and depth and orientation information of the coal seam are detected by the directional borehole radar,with a coal thickness detection accuracy error of 3.15%.Effective technical support for mine geological transparency and intelligent construction of coal mines is provided through these research results.

Abstract:Pressurized oxy-fuel combustion technology,regarded as one of the main directions for CO2 capture in coal-fired power plants in the future,has been widely studied by academics in recent years.Among these studies,the wet-cycle pressurized oxy-fuel combustion process,in which the recirculating flue gas contains H2O,has been considered to have better economic potential.The effect of a CO2/H2O atmosphere on the pressurized oxy-fuel combustion of char fragments in the pressure range of 4-10 MPa was investigated using reactive molecular dynamics(ReaxFF MD).The contributions of oxidation,CO2 gasification,and H2O gasification to char conversion were quantified through an atomic labeling method,and the mechanisms by which pressure and the CO2/H2O atmosphere influence char conversion were explored.It was shown that the increase in H2O inhibited char conversion,resulting in a decrease in carbon conversion by approximately 10%at lower pressures and 1%at higher pressures,while the increase in CO2 facilitated char conversion,leading to an in-crease in carbon conversion by approximately 6%-9%with CO2 across the range of pressures studied under the combus-tion conditions of the mixed char/O2/CO2/H2O system.The carbon conversion of char was found to increase by 2%-14%with increasing pressure,with the enhancement becoming more pronounced with increasing H2O and decreasing CO2.It was observed that pressurization increased the contribution of gasification to char consumption but decreased the contribu-tion of oxidation.This phenomenon was most pronounced in the 30%-CO2 atmosphere,where carbon conversion was en-hanced by 14%and the contribution of oxidation was decreased by 3%with increasing pressure,while the contribution of gasification was elevated by 17%.A competitive relationship was identified between oxidation,CO2 gasification,and H2O gasification.At 4 MPa and 40%-H2O/60%-CO2,as H2O concentration increased,the contribution of oxidation decreased by 22.4%,and the contribution of CO2 gasification decreased by 5.5%.Conversely,as CO2 concentration increased,the contribution of oxidation decreased by 10%,and the contribution of H2O gasification decreased by 12%.The competition between oxidation and gasification was reflected in the competition between gasification products and char for O2,while the competition among gasifications was reflected in the competition for active sites.

Abstract:In-seam seismic exploration has been widely used in underground geophysical exploration of coal mines be-cause of its high resolution and long detection distance.This technology can detect the location and trend of faults,but it cannot realize the quantitative detection of fault displacement.In order to realize the quantitative identification of fault throw,from the perspective of theoretical derivation and numerical simulation,the influence of faults with different fault throws on the dispersion characteristics and energy distribution mode of Love trough wave is analyzed,and the influen-cing factors of energy distribution are analyzed.By quantitatively calculating the amplitude distribution curve and disper-sion curve of Love wave and comparing with the theoretical data,the sensitive parameter of equivalent reflection coeffi-cient(the ratio of reflected in-seam wave energy to the total energy of reflected and transmitted in-seam wave)is pro-posed,and the quantitative relationship between fault throw and the change rate of equivalent reflection coefficient with wavelength is derived.The adaptive range of the quantitative relationship is analyzed by the in-seam wave data of numer-ical simulation.The verification of the numerical model shows that the parameter has good detection accuracy when the fault distance is greater than 1 m.When the fault distance is less than 1 m,the detection accuracy may decrease due to the error in energy picking and calculation.Finally,through the test of measured in-seam wave data,it is found that the equi-valent reflection coefficient is not only affected by the fault displacement,but also by the fault dip angle and other factors.The absolute error between the fault displacement predicted by the quantitative relationship and the actual exposed fault displacement is 0.58 m,and the relative error is 12.9%.The predicted fault distance of the measured data is basically con-sistent with the exposed fault distance,which verifies the effectiveness of the method.This method can provide technical support for safe and efficient production of working face and accurate geological modeling of subsequent coal mining face.However,this method is limited by fault dip angle and observation system in application.In the case of large fault dip angle and difficulty in receiving transmitted channel wave,the accuracy will be further reduced.The next step will study fault dip angle detection and reduce the dependence of this method on observation system.

Abstract:The presence of geological anomalies such as faults,collapse columns,and thin coal seams in coal seam work-ing faces severely constrains safe production,making it necessary to detect their internal structures in advance.Seismic in-seam wave exploration technology is widely applied to internal structural imaging of working faces with high resolution capabilities,but the application of explosive sources is restricted in certain scenarios,necessitating the development of working face internal structure imaging technology independent of explosive sources.Compared with active source ex-ploration techniques,ambient noise-based imaging technology has significant advantages in structural detection as it does not require active source excitation.At Huaning Coal Mine,ambient noise surface wave tomography is applied to structur-al detection in coal mine working faces,whereby vibration signals generated by underground machinery and mining activ-ities are utilized and waveform data are selected using diffuse wavefield indices prior to cross-correlation functions calcu-lation;as a result,interference from non-stationary phase zone noise sources is suppressed and reliable surface wave dis-persion data are obtained.Based on this,the one-step surface wave imaging technique is employed to directly invert three-dimensional velocity structure from dispersion data,successfully obtaining the internal velocity structure of the working face and delineating the positions of internal anomalous structures.The velocity imaging results show significant corres-pondence with geological anomalies revealed during actual mining,validating the feasibility and effectiveness of ambient noise tomography method in working face structural detection.The proposed diffuse wavefield selection technique and one-step surface wave imaging workflow provide new technical approaches for geological structural detection in under-ground coal mines.This method requires no active sources and offers green detection advantages,providing technical sup-port for safe and efficient mining operations in working faces.

Abstract:Fault reactivation in mining areas can cause significant hazards,including rock bursts and mining-induced seis-mic events.Water injection and fracturing shows a great potential for fault reactivation regulation and seismicity mitiga-tion.However,the mechanical driving processes of fault reactivation induced by water injection and fracturing and the as-sociated seismic response patterns remain unclear.An investigation is conducted into fault slip induced by hydraulic frac-turing under true triaxial stress conditions.Two field scenarios are considered:The water injection borehole either con-nects or disconnects with the fault plane.Initially,two types of 45°-inclined fault specimens were prepared:connected and disconnected specimens,both measuring 150 mm×150 mm×150 mm.A self-developed true triaxial stress loading sys-tem was used to simulate critically stressed fault,with stress conditions of 10,12,20 MPa for the connected specimens,and 5,6,10 MPa for the disconnected ones.During the experimental process,parameters including fault slip displacement,water injection rate,water injection pressure,and acoustic emissions(AE)were continuously monitored and recorded.Ad-ditionally,the three-dimension CT scan was employed to observe internal cracks development for the post-fracturing dis-connected specimens.By analyzing the spatiotemporal distribution of AE events,focal mechanisms,CT scan results,and mechanical processes,the pore pressure-dominated and poroelastic coupling-dominated mechanisms of fault reactivation/slip induced by hydraulic fracturing are confirmed,along with associated seismic response patterns.Results show that poroelastic coupling-dominated fault slips can be induced during the whole hydraulic fracturing process.In the initial stage,fractures initiates at the bottom of borehole due to stress concentration,which then propagate along with the initial fractures and develop in the direction perpendicular to the tangential stress,until intersect with fault plane and res-ultantly induce pore pressure-dominated fault slip.The main focal mechanism of fault slip is compressive-shear,whereas that of hydraulic fracturing damage is tensile-shear.Their corresponding AE events are both mainly distributed near the fault plane and the bottom of borehole.The fault friction coefficient promptly responds to changes in water injection rates,so as to maintain the stable fault slip.Such response shows an increase in the first and then decrease with the increase of water injection rates,which indicates a feasibility of regulating fault slip rates via injection rate control.Moreover,direct water injection into faults proves to be more effective for fault slip regulation in low-permeability formations,whereas hy-draulic fracturing works better in high-permeability formations.These findings could provide important insights for seis-mic signal identification induced by hydraulic fracturing near faults and for induced seismicity regulation.

Abstract:To meet the demands for coal-rock interface identification in intelligent mining and to overcome the limita-tions of manual interpretation—such as inefficiency and inconsistency under noisy,real-time,and dynamic conditions—an intelligent recognition method based on ground-penetrating radar(GPR)is proposed,integrating Random Forest(RF),Particle Swarm Optimization(PSO),and Long Short-Term Memory(LSTM)networks.Using the borehole columnar sec-tion of the 15219 working face in Xinjing Mine,Yangquan,Shanxi as a reference,a three-layer forward model with an in-clined interface(sandstone-coal-mudstone)is constructed by the finite-difference time-domain(FDTD)method.The sim-ulation results provide noise-free reference data for feature analysis and selection.For each trace containing 1 024 sample points,18 time-and frequency-domain features are extracted.RF is then applied to rank feature importance,and 8 key fea-tures with cumulative contribution exceeding 60%are retained:first-order difference,raw-signal amplitude,Hilbert envel-ope,mean wavelet coefficient,central frequency,signal mean,low-frequency energy,and spectral bandwidth.All features are standardized via Z-score normalization to eliminate dimensional effects.Subsequently,PSO is employed to automatic-ally optimize the hyperparameters of LSTM—as well as,for comparison,those of RNN and SVM.The optimal LSTM hy-perparameters are determined as follows:128 units,an initial learning rate of 3.3×10-3,and a dropout rate of 0.394.Con-sidering the structural characteristics of each model,the input data for both LSTM and RNN are organized into a tensor format of[number of samples,1 024 time steps,8 features],enabling the models to capture dynamic characteristics and phase continuity in electromagnetic wave propagation through the medium.In contrast,SVM is trained using a corres-ponding two-dimensional feature matrix.Finally,validation is performed using measured GPR data collected from the lower extraction roadway of the 15219 working face.Results indicate that,on the same test set,the RNN model quantitat-ively outperforms the LSTM model.To investigate this discrepancy,the prediction results of the LSTM model are further analyzed.In the LSTM-predicted roof interface of the coal seam,discontinuous segments,sharp undulations,and other an-omalies inconsistent with the original labels are observed.These anomalies correspond precisely to the influence zones of geological structures—such as collapse columns and watered floor sections—identified in the mining area's geological survey data.The underlying mechanism is attributed to LSTM's unique gating architecture,which enables deep extraction of information from both local and global characteristics,as well as from detailed and structural signal features.Con-sequently,LSTM predictions more accurately reflect the actual geological conditions and demonstrate the ability to tran-scend reliance on manual labels.In comparison,the RNN model tends to overfit the training labels,while SVM struggles with high-dimensional time-series features,resulting in fragmented recognition outputs.Overall,the findings confirm that the LSTM model offers unique advantages in analyzing the time-series characteristics of GPR data.It not only learns from manual labels to perform coal-rock interface recognition,but also uncovers latent physical patterns within the GPR sig-nals,thereby enabling more comprehensive detection of subtle signal variations caused by geological structures—vari-ations often missed by manual interpretation.

Abstract:At present,most of the techniques for inverting coal thickness through channel wave dispersion are based on the theoretical dispersion curve to select a single frequency for velocity CT tomography imaging,and the accuracy of the in-verted coal thickness in the working face is not high.To improve the prediction accuracy of coal thickness in coal seam working faces,the channel wave dispersion curve of the multi-layer elastic medium model is calculated,and the effective-ness of the three-dimensional dispersion inversion method was verified through forward simulation.The dispersion curve of the Love channel wave in the actual coal seam was extracted by using the generalized S-transform.Tomographic ima-ging of the working face was performed by setting the frequency range and step size,and the velocity CT imaging maps of the working face at different frequencies were obtained.The working face is divided into several sections.The dispersion curves of each section are calculated based on the results of tomographic imaging.The dispersion curves of each section are inverted,and the velocity distribution and coal thickness distribution of the entire working face are obtained by integ-rating the inversion results.The dispersion inversion algorithm selects nonlinear global optimization algorithms,such as genetic algorithm,pattern search algorithm,particle swarm optimization algorithm and simulated annealing algorithm,etc.This type of algorithm is more likely to find the global optimal solution and thereby improve the accuracy of coal thick-ness inversion.The three-dimensional dispersion inversion technology of channel waves in the coal mining face of a cer-tain coal mine is selected for verification.The average coal thickness of this working face was 3.7 m.The double-channel transmission method was adopted for channel wave seismic exploration.The generalized S-transform was used to extract each dispersion curve of the Love channel wave,and the velocity was extracted once every 10 Hz within the frequency band of 100-250 Hz.The CT imaging results of the working face velocity at 16 frequencies were obtained by using tomo-graphy.Then,each dispersion curve of the working face was calculated based on the tomography results,and the entire dispersion curve was inverted by using the genetic algorithm.The results show that the three-dimensional dispersion inver-sion of channel waves improves the accuracy of coal thickness prediction in coal seam working faces.Compared with the coal thickness exposed in the roadway,the average fitting error is only 0.22 m.Therefore,the three-dimensional disper-sion inversion imaging technology of channel waves has a relatively high accuracy in the prediction of coal thickness in the working face.

Abstract:The deep mining working face is characterized by high in-situ stress and high water pressure,making water in-rush hazards increasingly severe.With the rapid development of artificial intelligence and the continuous advancement of smart mining construction,deep learning and computer vision have been widely applied in mine safety monitoring,provid-ing new approaches for mitigating water inrush risks.Aiming at the need for real-time water inrush early warning in deep mines,this study innovatively integrates deep learning,machine vision,and electrical monitoring,proposing a real-time two-stage electrical monitoring method based on machine vision.The monitoring process consists of two consecutive stages:the visual recognition stage and the analysis and decision-making stage.In the visual recognition stage,the light-weight deep learning model YOLO11s is used to rapidly and accurately identify low-resistivity regions in electrical im-ages and obtain their spatial coordinates.These coordinates are then passed into the analysis and decision-making stage,where an OpenCV-HSV color filtering algorithm analyzes the identified low-resistivity regions from three aspects—quant-ity,area ratio,and color depth—to comprehensively determine whether the regions pose potential water inrush risks,trig-gering multi-level warning responses through an automatic decision mechanism.Results show that the YOLO11s model can accurately assess whether water sources may cause water inrush hazards and automatically trigger multi-level warn-ings,overcoming the limitations of other monitoring methods in real-time detection,disaster evolution analysis,and early warning.The YOLO11s model achieved a mean Average Precision(mAP)of 90.2%,with an average inference time of 34.6 ms per frame and an average processing rate of 28 Frames Per Second(FPS),outperforming YOLOv8,YOLOv5,and Fast R-CNN in detection accuracy and speed.The OpenCV-HSV color filtering algorithm required only 7 ms per image for analysis and decision-making,realizing real-time early warning of water inrush hazards.

Abstract:The rock wall-concrete shotcrete layer,which is supported by anchor and shotcrete in a mining environment,represents a typical example of an anisotropic structural plane anchored by rock mortar.The objective of this study is to investigate the mechanical behaviour of the rock wall-spray layer interface supported by bolting and shotcreting.To this end,the findings of an experimental study on the mechanical properties of rock-mortar non-anchor and anchored aniso-tropic structural plane specimens under triaxial compression are presented herein.The mechanical properties of rock-mor-tar unanchored and anchored anisotropic structural plane specimens under triaxial compression were investigated utilising the MTS 815 rock mechanics test system.The confining pressure of the test was set at 10,15,20 and 25 MPa.The rock-mortar anisotropic structural plane is defined as an isosceles triangular serrated surface.The undulating angles are 30°,45°,and 60°.This study analyses the influence of bolt anchorage and confining pressure on the mechanical properties and failure mode of rock-mortar structural planes.Additionally,the acoustic emission signal in the compression test process is analysed.Subsequently,the three-dimensional morphology of the structural plane following fracture is scanned.Finally,the compressive strength prediction model of rock with anchored inclined anisotropic structural plane is established.The findings indicate that the peak strength of rock-mortar anisotropic structural plane specimens exhibits an increase with the rise in confining pressure and undulation angle of the structural plane.The mortar matrix exerts a dominant influence on the trend observed in the deviatoric stress-strain curve of rock-mortar non-anchor anisotropic structural plane specimens.Following the anchoring process,the peak strength of the rock-mortar anisotropic structural plane specimen is demon-strably enhanced,accompanied by a notable increase in the specimen's capacity to withstand plastic deformation.Follow-ing the fracture of the specimen,it was observed that the material was still capable of withstanding significant stress.Addi-tionally,the deviatoric stress-strain curve exhibited double-peak characteristics.A comparative analysis of the failure modes exhibited by rock-mortar anisotropic structural plane specimens,both before and after anchoring,reveals that the unanchored specimens display shear slip failure along the anisotropic structural plane.Conversely,specimens that have been anchored demonstrate"X"-shaped conjugate shear failure.Comparing the acoustic emission characteristics of rock-mortar anisotropic structural plane specimens before and after anchoring under triaxial compression,it is found that the acoustic emission signal of the specimen after anchoring is sparse in the early stage of loading,but the ringing count sig-nal is more intensive after the macroscopic fracture of the specimen,which means that the bolt after anchoring is very good before the macroscopic fracture of the specimen,which limits the generation of small cracks inside the specimen.After the macroscopic fracture,the bolt better exerts the performance of the structural plane itself.Three-dimensional mor-phological scanning of the structural plane following fracture revealed that the degree of wear on the rock structural plane was less than that observed on the mortar structural plane.Furthermore,the degree of wear on the structural plane was found to decrease following anchoring.Comparing the test results with the strength prediction model results,the average error of the predicted strength under different structural surface roughness is 6.64%,which verifies the reliability of the prediction model.

Abstract:The low level of automation and intelligence of roadway support equipment in coal mine restricts the forming efficiency of coal mine roadway,which is the key reason for"mining imbalance".In order to solve the problems of low automation and poor support efficiency of coal mine roadway support equipment,a path planning method of drilling and anchoring robot arm based on deep reinforcement learning is proposed for a drilling and anchoring robot arm integrating cantilever road header and multi-degree-of-freedom manipulator.The coal mine roadway environment is constructed in the virtual environment,and the collision detection model of the manipulator and the fuselage,the coal wall and the sup-porting steel belt is established.The collision detection is carried out in the virtual environment by using the hierarchical bounding box method,and the obstacle avoidance strategy under the condition of limited boundary of the coal mine road-way is formed.Based on the PPO(Proximal Policy Optimization)algorithm,combined with various factors,an improve-ment is proposed.Considering that the state space input length of the multi-degree-of-freedom manipulator is not fixed,the environmental state input processing method of the LSTM(Long Short Term Memory networks)neural network is introduced,which can improve the adaptability of the algorithm to the environment.In addition,the ICM(Intrinsic Curi-osity Module)is introduced in the case of sparse rewards and punishments,and the agent is encouraged to explore the en-vironment to a greater extent by giving internal rewards.Based on the reward and punishment mechanism,the agent is es-tablished.According to the motion characteristics of the drilling and anchoring robot,its state space and action space are defined.In the same scene,two algorithms are used to train the agent respectively.The comprehensive reward value,round steps,Actor network loss value,Critic network loss value and other indicators are compared and analyzed.Finally,through the simulation ablation experiment test comparison:The experimental results show that when the original PPO al-gorithm cannot complete the task,the path length of the improved algorithm is 3.98%shorter than that of the PPO-ICM al-gorithm which can also complete the task,and the time used is shortened by 25.6%.In order to further verify the robust-ness of the improved algorithm,multiple sets of experiments are designed.The improved PPO algorithm completes the path planning task.The distance error between the path end point and the target position is within 3.88 cm,and the angle error between the bolt and the vertical direction is within 3°.It can effectively complete the path planning task and im-prove the automation degree of the coal mine roadway support system.The results verify the feasibility and effectiveness of the proposed method in the path planning of the multi-degree-of-freedom manipulator of the drilling and anchoring ro-bot in the case of the changeable position of the anchor hole in the coal mine roadway support.

Abstract:The Dananhu Coalfield in the southeastern part of the Turpan-Hami Basin contains abundant coal resources,but the coals in this area have multiple layers and vary greatly in thickness,resulting in increased difficulty in coal exploration.In order to explore the coal accumulation regularity of the Xishanyao Formation in the Dananhu Coalfield,the coal-accu-mulating models,palaeogeography,and distribution of coal-accumulating centers of the middle member of Xishanyao Formation were analyzed based on borehole cores and geophysical loggings data.Three types of sedimentary facies were identified in this member,including fluvial,delta,and lacustrine facies.The coal-accumulating swamps were developed from the fluvial overbank,interdistributary bays of the delta plain,and shore-shallow lakes,among which the interdistribu-tary bay swamp was the most favorable coal-accumulating environment.The paleogeography and coal thickness changes of the middle member of Xishanyao Formation have been analyzed,which shows that the major paleogeographic units in-cluded alluvial plain,delta plain,delta front,and shore-shallow lake.The two coal accumulation centers with coal thick-ness greater than 95m were found to be located in the interdistributary bay area.The coal accumulation was influenced by a combination of paleo-tectonics,paleoclimates,paleo-vegetations,and paleoenvironment conditions.The relationship among coal seam thickness,total stratal thickness,and the sandstone to mudstone thickness ratios is further analyzed us-ing the vector cloud diagram.The result shows that the area with a moderate stratal thickness and a low sandstone to mud-stone thickness ratio is associated with the thicker coal seams,indicating that the preferred coal-forming environment was the interdistributary bays where the moderate subsidence rates and relatively less supply of coarse-grained sediments were maintained.Based on these paleogeographic analyses,we proposed that the coal accumulation centers were mainly distrib-uted in the central area of the No.1 mine field and the central north of the F1 mine field.A coal accumulation model has been established in which the swamps of interdistributary bays of the delta plain had better coal accumulation than the swamps developed from the fluvial overbank and shore-shallow lakes.

Abstract:Controllable shockwave technology,as a new type of coal seam penetration enhancement technology,has the characteristics of safety and reliability,high energy utilisation,and the number of impacts and energy can be controlled,etc.It has good application prospects in reforming the permeability of coal seams and strengthening gas extraction.This technology has a good application prospect in transforming the permeability of coal seams and strengthening gas extrac-tion.Aiming at the problems of poor gas extraction effect and short effective extraction time in soft and low-permeability coal seams,the technology of permeability enhancement in the roof of soft and low-permeability coal seams based on the controllable shock wave is proposed.However,the crack extension and damage evolution law of coal and rock under the cyclic impact loads of different discharge voltages are not clear,which cannot provide guidance for the determination of key process parameters.Physical models of coal-rock assemblages were cast according to the similarity criterion,and a controllable shockwave similarity simulation test platform capable of cyclic loading of the physical models with different discharge voltages was constructed independently in the laboratory.Based on the above conditions,a similar simulation test of controllable shockwave penetration enhancement in the roof of a soft and low-permeability coal seam was carried out.Various methods were used to investigate the dynamic response of the model,including analysing the crack distribu-tion and evolution patterns under different discharge voltages,constructing the displacement field on the surface of the model using a digital camera and Matlab-Ncorr open source scattering software,and establishing a mathematical relation-ship between the damage factor and the ultrasonic wave speed to quantitatively characterise the three-dimensional damage evolution inside the model.The main conclusions are as follows:Discharge voltage and number of times play a key role in the process of controllable shockwave penetration of soft and low-permeability coal seams,and high voltage leads to high crack density and rapid expansion of the model.Increasing the number of discharges can promote the crack expansion,forming a"fan-shaped"crack network and optimising the penetration enhancement effect.As the number of discharges in-creases,the vertical and horizontal displacements of the coal-rock model increase.The displacement is positively correl-ated with the discharge voltage.The increase in displacement promotes the crack expansion of the coal rock body,provides more space for gas transport,and contributes to the unloading and enhancing permeability of the coal seam.Coal and rock damage gradually accumulate under the action of controllable shock wave,and the damage factor is positively correlated with the number of discharges,and coal and rock damage is a cumulative process.The damage of coal and rock near the fracturing drill hole and coal-rock interface is serious,and the damage under high voltage accelerates the evolu-tion and eventually forms a completely damaged area,which promotes the enhancement of coal seam penetration.This test elucidated the dynamic response characteristics of cracks,displacements and damages under cyclic impact loads with dif-ferent discharge voltages,and provided a reference for the selection and optimisation of engineering parameters.

Abstract:Injection of CO2-containing hot flue gas as a heat-carrying medium into deep coal seams can improve coal per-meability and gas displacement effect,while achieving geological sequestration of CO2.Elucidating the multi-field coup-ling mechanism of enhanced coal permeability and gas displacement by hot flue gas is a crucial point for the scientific reg-ulation and control of gas recovery enhancement efficiency.A geological model of a heterogeneous coal reservoir was constructed based on the heterogeneous distribution characteristics of mechanical parameters obtained from Nano indenta-tion tests.Numerical simulations were conducted to analyze the spatiotemporal evolution characteristics of multi-fields during the coal permeability enhancement and gas displacement by hot flue gas.On this basis,an evaluation index for gas recovery enhancement efficiency considering gas breakthrough effect was utilized for exploring the intrinsic response rela-tionships between main engineering control parameters(temperature,CO2 volume fraction,and pressure of flue gas)and the gas displacement efficiency by hot flue gas.The results show that:Weibull probability distribution function is more suitable for describing the spatially heterogeneous distribution of the microscopic elastic modulus of coal.The input of the released elastic strain energy from coal damage and the heat from mineral dissolution leads to the development of local-ized abnormally high-temperature zones.The gas displacement modes in the near field and far field are thermal displace-ment and CO2 displacement,respectively.Although N2 can rapidly break through the reservoir,it plays a role in increas-ing the seepage pressure gradient and reducing the flow resistance of the mixed gas during displacement.Within the heat-ing range of coal adjacent to the hot flue gas injection well,the stronger mineral dissolution effect is attributed to coal damage under the high temperature and pressure effect of hot flue gas,which facilitates CO2 enrichment.In insufficient heating zones,coal temperature is not high enough to induce coal damage,and excessive thermal expansion of the matrix leads to a significant reduction in permeability.In the early displacement stage,the range of insufficient heating zones sur-rounding the hot flue gas injection well remains unchanged,but extensive CO2 enrichment causes the low-permeability front to expand outward.As displacement time increases,the range and degree of coal damage near the hot flue gas injec-tion well rapidly increase and gradually stabilize,while the soluble mineral content in fractures decreases significantly,resulting in a significant permeability enhancement effect.During the gas displacement by hot flue gas,the area of the low-permeability front first increases and then decreases.To optimize gas recovery enhancement efficiency through multi-field regulation,the main engineering control parameters should be determined according to the actual duration of the recovery enhancement cycle.For short production cycles,flue gas pressure has a greater influence than CO2 volume fraction or flue gas temperature,and low-pressure flue gas contributes to higher recovery enhancement efficiency of gas injection.For long production cycles,high flue gas pressure,low CO2 volume fraction,and high flue gas temperature can lead to higher recovery enhancement efficiency of gas injection.

Abstract:Clarifying the effects of dynamic stress waves on coal-damage behavior supports the development of water-free coal-permeability enhancement methods.This study examines the time-frequency and energy characteristics of stress waves generated by impact load and the resulting damage to low-permeability coal.Dynamic impact tests were conducted on coal specimens from Wuyang Mine(Shanxi Province)under various impact velocities.Stress-wave monitoring equip-ment captured raw waveform data before and after coal damage.Using the adaptive optimal kernel time-frequency analys-is(AOK-TFA)technique combined with MATLAB-based numerical processing,the energy evolution of stress waves was systematically analyzed to elucidate the damage mechanisms associated with triaxial waves.The results show that with in-creasing impact velocity,energy across all frequency bands of the triaxial stress waves rises consistently,indicating that energy accumulation in these bands is the primary driver of coal damage.The frequency bands most responsible for dam-age differ from those of blast-induced stress waves in rock;for impact-induced stress waves,damage energy is mainly concentrated in the medium-to-high frequency ranges of 39.06-312.50 Hz and 625-2 500 Hz.The dominant spectral com-ponents of these waves appear initially at about 0.4 s,but after passing through damaged coal,a consistent time delay of roughly 0.05 s occurs.Overall,coal damage caused by impact-loading stress waves during energy transfer and attenuation results from the combined effects of triaxial stress waves(P,SV,and SH waves).These findings offer valuable insights in-to how impact dynamic loads can enhance coal permeability.

Abstract:The resource utilization of biomass and coal gasification fine slag(CGFS)is considered crucial for ensuring na-tional energy security,mitigating environmental pollution,and achieving China's"dual carbon"target.Pyrolysis,as the fundamental thermochemical conversion of biomass,enables the rapid transformation of biomass into bio-oil,biochar,and small-molecule gases within milliseconds,representing one of the most promising technologies for high-value biomass utilization.However,direct application of bio-oil is hindered by its complex composition and poor stability.The conver-sion pathways of biomass pyrolysis vapors are dynamically regulated through ex-situ catalytic fast pyrolysis technology,thereby enhancing carbonyl compound content in bio-oil.This carbonyl-enriched bio-oil serves as a critical platform inter-mediate for synthesizing gasoline/diesel and lubricants via aldol condensation and reductive etherification reactions.Nev-ertheless,existing catalysts are constrained by complex synthesis procedures and prohibitive costs.Thus,CGFS was in-novatively employed in biomass catalytic fast pyrolysis,and a novel strategy termed"holocellulose rapid pyrolysis coupled with CGFS-directed catalysis"was proposed for producing carbonyl-enriched bio-oil,achieving synergistic utiliz-ation of biomass and CGFS.Systematic investigations were conducted using corn stalk holocellulose as feedstock and CGFS as catalyst through ex-situ fast catalytic pyrolysis.The effects of pyrolysis temperature,catalytic temperature,and catalyst-to-feedstock mass ratios on product distribution and composition were comprehensively analyzed.Catalyst char-acterization was performed using XRD,SEM-EDS,and XPS,with additional evaluation of cycling stability and regenera-tion capacity.Key findings demonstrated that:Bio-oil and biochar yields were reduced with increasing pyrolysis temperat-ure,peaking at 49.8％bio-oil yield at 450 ℃.A progressive decrease in bio-oil yield from 40.1％to 32.2％was observed as the catalytic temperature was elevated from 400℃ to 550 ℃,while gas yield was enhanced from 36.8％to 45.4％.This thermal transition was accompanied by significant increases in H2+CH4,CO2,and CO yields,rising from 5.3,40.7,and 53.1 mL/g to 57.2,55.9,and 124.3 mL/g,respectively.Increasing mass ratios of catalyst to holocellulose from 0.5 to 2 re-duced bio-oil yield from 46.6％to 36.2％,while CO2 and CO yields rose from 36.4 and 46.3 mL/g to 51.7 and 59.9 mL/g.A marked enhancement in carbonyl compound content was achieved through catalyst loading optimization,with relative abundance increasing from 48.9％to 81.9％as the catalyst-to-feedstock ratio was elevated from 0 to 2.Concurrently,ketonic species exhibited similar amplification from 41.4％to 81.2％.The carbonyl fraction was predominantly composed of linear ketones(e.g.,1-hydroxy-2-propanone),cyclic ketones(e.g.,2-cyclopenten-1-one),and furan derivatives includ-ing furfural and 5-hydroxymethylfurfural.Notably,peak area ratio of 1-hydroxy-2-propanone was elevated from 1.41％to 48.98％as the catalyst-to-feedstock ratio was elevated from 0 to 0.5.The crystallographic phases of CGFS remained un-altered after use,while the surface O and C atomic ratio was reduced.The fresh CGFS exhibited an Fe2+content of 60.08％,and the value decreased after use.After five catalytic cycles,carbonyl content declined from 75.7％to 67.6％,primarily attributed to oxidation of surface metallic species.

Abstract:Pressure relief mining is the most economical and effective regional gas control measure under coal seam con-ditions.However,compared to long-distance coal seam groups,the gas outflow from the first mining face under the condi-tion of pressure relief mining in ultra-close coal seams has the characteristic of sudden increase,and gas exceeding the lim-it still occurs even under the Y-shaped ventilation mode.For this purpose,based on the typical conditions of the ultra-close multi-seams mine in Shanxi Province,the evolution characteristics of the mining induced fracture field in the bottom rock layer of the ultra-close multi-seams downward pressure relief mining were studied.The"three zones"division method and discrimination criteria for gas pressure relief and migration in the underlying coal rock layer under mining were proposed,and the migration and enrichment laws of gas pressure relief in the ultra-close multi-seams mining field were elucidated.Based on this,the"blocking-reducing-controlling"synergistic control technology of pressure-relief gas was proposed,which includes gas extraction through high-level boreholes to block gas migration,and precise regulation of air volume in the main and auxiliary intake airway Y type ventilation to reduce gas accumulation,and buried pipe extraction in the goaf to control gas flow field.The optimal parameters of high-level boreholes,the optimal air volume ratio of the main and aux-iliary intake airways,and the reasonable parameters of buried pipes in the goaf were determined,and industrial test of gas governance was carried out.The results show that downward pressure relief mining causes the bottom rock layer to move toward the goaf,leading to pressure relief expansion of the underlying coal rock layer,development of mining-induced fractures,and pressure relief migration of methane gas,forming damaged gas-interflow zone,floor pressure-relief zone,and confined gas-adsorption zone.The underlying coal seam,which is extremely close to the mining layer,is located with-in the"damaged gas-interflow zone",allowing gas to fully decompress and rapidly surge into the mining space along ver-tical fractures,thereby inducing gas exceeding the limit of the mining layer working face.The maximum gas extraction volume of high-level boreholes reaches 1.34 m3/min,and gas extraction is the most effective when high-level boreholes are 15-38 m away from the working face.When the air volume ratio of the main and auxiliary intake airway is 3∶1,the gas emission rate is the highest.With an average negative pressure of 27 kPa,the amount of gas extracted from the buried pipes in the goaf reached 30 m3/min.The"blocking-reducing-controlling"synergistic control technology of pressure-re-lief gas in ultra-close multi-seams mining has reduced gas volume fraction in the tailentry and the goaf behind the sup-ports by 73.0％and 64.6％,respectively,without exceeding the coal mine safety regulations in China.