Abstract:Real-time and reliable detection of dust concentration is critical for ensuring safety in coal mine operations.However,existing image-based dust concentration detection methods often suffer from limited interpretability and insufficient accuracy.To address these challenges,a dust concen-tration image recognition model that integrates prior interpretable features with a multi-kernel re-sidual attention network was proposed in this study.First,an image feature library was constructed to capture multidimensional characteristics,including color,texture,and geometric features.The Pearson correlation coefficient and mutual information were then employed to select a subset of lin-ear and nonlinear features that are highly correlated with dust concentration,thereby enhancing model interpretability.Subsequently,a multi-kernel learning framework was developed,in which radial basis function kernels were used to separately map the selected linear and nonlinear features into high-dimensional feature spaces.A weighted fusion strategy was introduced to balance repre-sentation capability and interpretability across different feature types.To further improve model per-formance,residual connections were incorporated to facilitate gradient propagation during training,and a channel attention mechanism was introduced to dynamically emphasize critical image fea-tures.These architectural designs enhanced the model's robustness and adaptability to complex un-derground mining environments.Experimental results demonstrate that the proposed model achieves superior performance on the benchmark dataset,with a mean squared error(EMSE)of 0.90 mg2/m⁶,a mean absolute error(EMAE)of 0.74 mg/m3,and a mean relative error(EMRE)of 1.76％.The coefficient of determination(R2)reaches 0.916 0,significantly outperforming com-parative models such as Support Vector Regression and Random Forest.Ablation experiments fur-ther confirm the effectiveness of the multi-kernel fusion strategy,residual architecture,and atten-tion mechanism in improving prediction accuracy.Overall,this study achieves a unified framework that balances model interpretability and recognition accuracy,providing a reliable,transparent,and high-precision solution for intelligent dust concentration in coal mines.The proposed approach of-fers important practical value for enhancing mine safety monitoring and risk prevention.

Abstract:Accurately characterizing the spatial heterogeneity of rock mass stress environments and evaluating the tectonic-geomechanical coupling complexity of coal mine stress fields therefore exert critical significance for both coal resource exploitation optimization and disaster-resilient under-ground infrastructure design.Ningzheng-Binchang mining area was taken as the study area,ex-plores the current tectonic stress pattern and the characteristics of the in-situ stress field through the regional tectonic evolution analysis,focal mechanism interpretation,and in-situ stress test.Based on the decomposition of principal stresses and considering the three-dimensional stress state of rock masses,a stress state index used to characterize the differences in the in-situ stress environment of rock masses was proposed.By selecting four indicators,namely the mining depth of the coal seam,the maximum horizontal principal stress,the strength-stress ratio of the surrounding rock,and the in-situ stress difference parameter,an evaluation model for the complexity of the in-situ stress field of coal mine was constructed.The results show that the focal mechanisms types of study area are diverse and the macroscopic stress field is under the action of tectonic stress with torsion-compres-sion and compression,with the property of slipping around the intermediate principal stress.More-over,the fitting curves of the horizontal maximum principal stress with the change of depth signifi-cantly exceeds the national average level of coal mines in China,and is mainly in the near northeast-southwest direction.The stress state index at some measurement points in Hujiahe coal mine,Gao-jiapu coal mine,and Tingnan coal mine exceeds 2.7,indicating significant differences in surround-ing rock stress in these regions.The complexity index of the in-situ stress field in the central and northern parts of the study area is relatively high,with local values above 0.8.The overall area near the southern and Yadian coal mines is below 0.3,and the evaluation results are basically con-sistent with the actual situation of rock burst in the study area.

Abstract:Gas explosion is a destructive and frequent major disaster type in coal mines,and the ex-isting risk assessment system still has shortcomings in accuracy,objectivity,and real-time perfor-mance.In response to the practical needs and challenges in coal mine gas explosion risk assess-ment,this article constructs the data-driven coal mine gas explosion risk assessment system.First,a three-level indicator system covering multiple dimensions such as monitoring,manage-ment,hidden danger status,and environmental conditions was constructed by using the hybrid-driven method integrating text mining and disaster mechanisms,which enabled real-time collection and expression of multi-source heterogeneous data.Second,scoring rules for third-level indicators and threshold rules for second-level indicators were formulated based on domain knowl-edge to provide standardized support for model inputs.Third,a multi-level and multi-model fusion risk assessment method was developed by integrating FAHP,CRITIC,linear weighting models,end-point mixed triangular whitenization weight functions,and risk level-risk value transformation models,achieving a balance between interpretability and data processing capabilities.Finally,in-dustrial testing was conducted on coal working faces and return airways of three types of coal mines:low-gas,high-gas,and outburst mines.The results indicate that the proposed assessment system can integrate multi-source heterogeneous data in real time,enabling risk assessment across multiple regions and levels with an accuracy rate of 98.3%.Comparative analysis demonstrates that its as-sessment accuracy is improved by 1.6%and 8.7%respectively compared to single weighting method and traditional grey clustering model.The system achieves real-time,accurate,and adap-tive coal mine gas explosion risk assessment under various working conditions,significantly outper-forming traditional models and demonstrating strong industrial applicability and promising prospects for widespread adoption.

Abstract:To address the challenge of coal mine goaf reignition caused by high-temperature crack-ing and low flame-retardant efficiency in traditional coal gangue slurry,this study introduces ammo-nium octamolybdate(AMM),a highly effective flame-retardant and smoke-suppressing agent,into the coal gangue slurry system.The aim is to elucidate the mechanism by which AMM-modified slurry inhibits coal spontaneous combustion.Through grouting backfill fire prevention and extinguishing test systems,the macroscopic combustion characteristics of raw coal,blank grouted coal,magnesium chloride(MAG),and AMM-modified grouted coal were compared during oxida-tion at 30-270℃.Electron spin resonance and Fourier transform infrared spectroscopy were em-ployed to analyze changes in free radical types,concentrations,and surface functional groups in coal before and after AMM addition.Results indicate:Compared to 7％MAG-modified slurry,5％AMM-modified slurry reduces peak CO release concentration by 19.97％,exhibiting an inhibi-tion rate 11.78％higher than MAG.After slurry treatment,raw coal showed lower g-values,line widths,and radical concentrations during oxidation,demonstrating stronger self-ignition suppres-sion by AMM-modified slurry than MAG-modified slurry.Quantitative analysis of active functional group changes during oxidation revealed that AMM addition reduced oxygen-containing functional groups(-OH,-C=O)in coal molecules,inhibited internal methyl side-chain cleavage,and pro-moted formation of more stable ether bonds.Based on experimental results,it is inferred that dur-ing coal oxidation,AMM thermally decomposes to form MoO3,promoting intermolecular cross-linking reactions to create a protective carbon layer.This blocks the further generation of oxygen-containing radicals into R-OH,instead forming more stable compound structures.Consequently,the production of combustible CO gas is reduced,inhibiting coal spontaneous combustion from a physicochemical perspective.This achieves the enhanced fire prevention and extinguishing effect of AMM-modified coal gangue slurry.

Abstract:In order to address the challenges posed by the unwieldy regulation of air volume,the un-timeliness of regulation,and the deficiency in regulation accuracy in the wind location beneath the mine,this study proposes an intelligent mine louver regulation and control method within the venti-lation network for on-demand wind supply.The proposed method involves the construction of an automatic louver regulation and control system,the execution of experimental research,the pro-cessing of data through Kalman filtering,the establishment of a system mathematical model,and the development of a model.The subsequent step involves identifying,designing,and improving a PID controller for the automatic regulation of the louver,considering its characteristics.The regula-tion effects of PID control,fuzzy PID control,and segmented PID control are then compared.The next stage involves developing a remote monitoring software module for louver regulation,which is equipped with wind demand prediction and branch prioritization functions.Finally,the improved PID-based remote monitoring software module for louver regulation is applied in practice.PID con-trol,fuzzy PID control and segmented PID control of the regulation of the louver,the development of air demand prediction and branch preference function of the regulation of the remote monitoring software module of the louver,and improve the PID of the mine louver regulation and control sys-tem combined with the ventilation network real-time solving platform for use.The results show that:This paper has determined that the opening degree of the louver[0,35)is the high-sensitivity zone,[35,60)is the medium-sensitivity zone,and[60,90]is the low-sensitivity zone.The mathematical model of the louver automatic control and air regulation is obtained by system identifi-cation,and the transfer function model of the automatic louver control system is obtained.The fuzzy PID and segmented PID control algorithms are proposed.The control capabilities of the lou-ver are compared among PID,fuzzy PID,and segmented PID algorithms.The overshoots are 10.12%,13.36%,and 7.44%respectively,and the regulation times are 56.69,38.17,and 53.19 s respectively.The segmented PID algorithm has a smaller overshoot and can meet the re-quirements of stable air volume control.Combined with the improved PID mine louver control sys-tem and the real-time ventilation network solution platform,the louver opening degree is adjusted from 40° to 45° in the 23204 mining face.The air volume of the working face increases by 4.354 m3/s,and the air volume control of the working face and its related branches is achieved.

Abstract:Mine roadways are narrow,confined spaces,characterized by rapid smoke spread,dis-rupted ventilation systems,and significant challenges in firefighting and rescue during fires.This paper systematically reviewed the technological advancements in emergency rescue for mine road-way fires,focusing on fire thermodynamics,detection techniques,response techniques,and rescue exercise technologies.Theories of fire development and smoke movement in roadways were ana-lyzed,the thermodynamic disaster characteristics under different ventilation methods and roadway forms were clarified,and the challenges of rescue operations in high-temperature smoke environ-ments were expounded.Detection and monitoring technologies and equipment used during rescue operations were summarized,and techniques and methods for smoke flow regulation,automatic fire suppression,and manual firefighting in roadways were reviewed.The current status of firefight-ing training,equipment deployment,and auxiliary decision-support technologies was also dis-cussed.Finally,the development trends of mine roadway fire technology in China are proposed.At the theoretical level,full-scale experimental studies on fire development,smoke flow control,and fire suppression in roadway networks should be strengthened to enhance technical validation un-der real fire conditions.At the equipment level,the development of intelligent detection and fire-fighting equipment should be accelerated,and coordinated research on ventilation control and fire suppression should be promoted,and emergency rescue decision-support systems integrating big data and artificial intelligence should be developed.In terms of rescue training,it is necessary to strengthen the combination of practical firefighting operations and virtual scenario drills to improve the emergency rescue capability of rescue teams.This review provides new directions for improv-ing the level of emergency rescue technology.

Abstract:Thermal runaway and the cascading propagation pose a core challenge limiting the large-scale safe application of lithium-ion batteries.Focused on 100 Ah LiFePO4 batteries,their thermal runaway evolution and kinetic propagation characteristics was systematically investigated by con-structing a multi-cell module experimental platform.The results show that the thermal runaway process is divided into four stages:self-heating with battery micro-expansion,pressure accumula-tion and activation of the safety valve,thermal runaway explosion and recession.Notably,the mu-tation point of expansion force precedes the earliest detectable temperature signal by up to 476 s,providing a critical criterion for ultra-early warning.Furthermore,thermal runaway propagation ex-hibits a hierarchical"thermal hysteresis-burst"characteristic.The first three batteries form the ba-sic propagation unit,while the third cell acts as the initial propagation barrier due to accumulated thermal resistance.The fourth cell transforms into an energy hub through preheating and transient thermal shock,driving the reconstruction of propagation pathways.Based on this mechanism,a graded blocking strategy is proposed:A material cooling layer can be installed between the second and third cells to reinforce the thermal resistance barrier,with an integrated liquid cooling structure between the third and fourth cells to mitigate the acceleration effect of the energy hub.This study reveals the nonlinear dynamics of thermal runaway propagation,providing theoretical and technical foundations for inherent safety design in electric vehicles and energy storage systems.

Abstract:To achieve accurate detection of unauthorized interactions in mine conveyor belt areas,an improved PP_LiteSeg semantic segmentation algorithm integrating transfer learning and a fea-ture attention enhancement mechanism was proposed to tackle the challenges of sample scarcity,multi-scale targets,and blurred edges in underground images.A Feature Attention Pyramid Pool-ing module was designed to fuse multi-scale features,thereby enhancing the perception of target de-tails across various scales.A lightweight multi-level unified attention fusion decoder network was constructed to strengthen the discriminative ability between targets and complex backgrounds.Ad-ditionally,a transfer learning strategy using pre-trained weights was introduced to accelerate conver-gence on the conveyor belt dataset.The results show that the proposed algorithm achieves an accu-racy of 99.2%,a mean intersection over union of 90.4%,a Dice similarity coefficient of 94.8%,and a kappa coefficient of 95.4%.These metrics show significant improvements compared with mainstream networks,including DeepLabv3,U-Net,EfficientNet,ShuffleNet,MobileNetV3,and the original PP_LiteSeg.This study provides high-precision technical support for unauthorized behavior detection and intelligent safety supervision in mine conveyor belt zones.

Abstract:Aiming at the problem of large deformation and difficult support of deep soft rock in Hudi Coal Mine of Qinshui Coalfield,the stress characteristics of surrounding rock of roadway with dif-ferent cross-section shapes were analyzed in depth.Based on the theory of uniform-strength sup-port,the full-space cooperative support model of elliptical ring double-anchor shell concrete-filled steel tube support was proposed for the first time.The equivalent axial ratio adjustable technology was developed to dynamically match the in-situ stress environment.The anchor cables with differ-ent anchorage lengths were determined to construct the elliptical bearing structure,and the high-strength concrete-filled steel tube support was used as the"rigid support core"to form a full-space cooperative system with active and passive coordination.The calculation formula of supporting strength required by surrounding rock of roadway with different section and buried depth was ana-lyzed.The numerical simulation method was used to analyze the stress evolution and deformation of surrounding rock under different cross-section shapes,buried depths,axial ratio relationships,cooperative effects,and differences in support methods.The results show that with the increase of buried depth,the surrounding rock control ability of the full-space cooperative support in different sections is gradually enhanced and better than that of the initial support method.The maximum con-trol deformation efficiency can reach 75.4%,the peak stress decreases by about 11.9 MPa,and the stress difference decreases,which proves the feasibility of the equivalent axial ratio control.The stress of anchorage boundary tends to be stable,and the difference is 0.98～1.21 MPa.The feasibility of the full-space cooperative support is verified by monitoring the stress state of the whole section of the support through the field industrial test.

Abstract:Traditional safety monitoring system,which rely on a passive response mode of"monitor—alarm—power cut off",fall short of the requirements for proactive early warning and collabora-tive control in the intelligent coal mine construction.On the basis of a systematic analysis of the de-velopment process of coal mine safety monitoring system in China,this paper defines the connota-tion of a new-generation intelligent safety monitoring system,and proposes an overall system archi-tecture and a technical route based on"cloud-edge-end".In this paper,the research was conducted respectively on the following aspects:from an"end"side perception layer,technical research cur-rent states of sensor generic technologies,gas laser detection,precise wind measurement,etc.;from an"end-edge"collaboration perspective,the adaptability and key technologies of inspection robots such as rail-type,trackless-type,and individual mine inspection equipment under complex underground coal mines environments;from an"edge"side control layer,long-distance full-IP net-working and communication-computation-control integrated technologies;and from a"cloud"side platform layer,the progress of system key technologies for disaster integration monitoring,multi-disaster composite monitoring and early warning based on a unified data foundation.By means of on-site industrial verification,a false alarm rate of the researched intelligent safety moni-toring system was significantly reduced,and an ability to actively identify potential hazards and an intelligent level of inspection were effectively enhanced.Finally,the development trends of the new-generation coal mine intelligent safety monitoring system were prospected.It was indicated that in the future,efforts should be devoted to formulating a unified communication protocol stan-dard platform,developing vertical large models for coal mine safety,constructing an intelligent sys-tem for heterogeneous inspection robot groups,and ultimately forming a new paradigm of digital and intelligent precise disaster prevention in mines,so as to provide theoretical and technical sup-port for comprehensively improving the intrinsic safety level of coal mines.

Abstract:Coal fires are a major geological hazard that severely constrain coal resource security and ecological environmental protection in China.To address the limitations of traditional remote sens-ing methods for coal fire monitoring,specifically in spatial resolution and anomaly extraction accu-racy,this study takes the Laojunmiao coalfield in the eastern Junggar Basin of Xinjiang as the re-search area and develops an intelligent coal fire monitoring framework based on the Google Earth Engine(GEE)platform by integrating multi-source remote sensing data.First,high-resolution multispectral features from Sentinel-2 and thermal infrared data from Landsat-8 are fused to con-struct a multi-dimensional input feature set composed of spectral bands and indices.An improved U-Net network is then employed to achieve 10 m spatial downscaling reconstruction of land surface temperature(LST),significantly enhancing the spatial accuracy of thermal anomaly information.Second,an unsupervised anomaly detection method based on autoencoders is introduced to auto-matically identify coal fire regions without the need for manual labeling,enabling precise boundary extraction and dynamic tracking of distribution changes.Finally,by combining multi-temporal coal fire identification results,a coal fire thermal anomaly index(CFTA)is proposed to quantitatively analyze the spatiotemporal evolution of coal fire activities and their mitigation effects from 2016 to 2025.The results demonstrate that the proposed intelligent monitoring framework can effectively capture the dynamic changes during coal fire development and remediation processes,offering high spatial resolution and sensitivity.This provides a reliable technical pathway for accurate monitoring and prevention of coal fire hazards.

Abstract:After the occurrence of a disaster,how to achieve the rapid and efficient detection of life information of trapped individuals becomes the key to improving rescue efficiency and success rates.To this end,this paper elaborates on the critical issues and corresponding solutions encoun-tered in the rescue processes of major disaster types such as earthquakes,mining accidents,and col-lapses.On this basis,it further analyzes the research progress of four life information detection technologies—audio-video detection,infrared detection,gas detection,and radar detection—and systematically reviews the developmental trajectories of these technologies,clarifies the technical challenges and key technological milestones faced in their evolution,and finally outlines the direc-tions that future research should prioritize.Meanwhile,from the perspective of rescue needs,this paper conducts a comprehensive analysis and discussion on the development directions of disaster rescue and detection technologies.The review presented herein points out the direction for the de-velopment of high-performance,multimodal life information detection technologies and equipment for rescue operations.

Abstract:Coal is a cornerstone of China's energy structure,and fluctuations in its price not only af-fect the upstream and downstream of the industrial chain but also bear on achieving the"dual-carbon"goals and safeguarding macroeconomic stability.To improve forecasting accuracy,this study develops an Informer-based multimodal cross-attention forecasting model,using the Bohai-Rim 5 500 K thermal coal price as the prediction target.We build a multimodal dataset that inte-grates key drivers including raw coal output,coal imports and tariffs,geopolitical uncertainty,coal enterprise inventories,total thermal power generation,and the consumer price index.The numeri-cal modality is processed via linear mapping;the textual modality employs a RoBERTa encoder to extract semantic representations;and a cross-attention mechanism is introduced for cross-modal fu-sion between numerical sequences and textual information.Empirical results show that Informer performs better than multiple benchmark models on long-horizon forecasting;relative to simple con-catenation,introducing cross-modal cross-attention significantly improves predictive accuracy;the model also passes robustness tests under noisy text conditions.The proposed Informer-based multi-modal cross-attention model provides methodological support for scientific coal price forecasting and offers theoretical and practical value for energy-market research and related policy formulation.

Abstract:The form of the crushing body and the loading rate significantly influence the material crushing process,making the selection of an appropriate crushing method essential for energy-effi-cient comminution and particle size control.In this study,drop weight impact tests were con-ducted by varying the penetration angle and drop height to investigate the effects of different crushing conditions on the fracture morphology,particle size characteristics,and energy effi-ciency during the fragmentation of quasi-brittle materials.The results show that as the penetra-tion angle increases,the failure mode of the specimens transitions from tensile failure to compres-sive failure.The fracture fractal dimension of the crushed products increases and reaches a maxi-mum within the penetration angle range below 120°,then decreases within the 120°—180° range.The fractal dimension increases with rising mass-specific energy,though the rate of increase di-minishes within the range of 0.167 4-0.227 7 kW·h/t.The average energy efficiency of mate-rial fragmentation under different penetration angles ranges from 1.68%to 2.86%,increasing uniformly with the penetration angle and stabilizing within the 120°—180° range.This study aims to enrich comminution theory and provide a reference for predicting crushed products and design-ing crushing bodies.

Abstract:Roadway surrounding rock is often subjected to the coupled influence of internal fracture structures and complex non-uniform loads,leading to stress redistribution,aggravated local failure,re-duced overall bearing capacity,and increased instability risk.To investigate the crack propagation and evolution characteristics of sandstone with different fracture features under non-uniform loading,three types of specimens that include intact sandstone,sandstone with prefabricated rectangular fractures,and sandstone with filled fractures were tested.A self-developed non-uniform loading apparatus was employed in combination with digital image correlation(DIC)for full-field strain monitoring,acoustic emission(AE)techniques,and FLAC3D numerical simulations to analyze crack propagation,AE re-sponse,stress field evolution,and plastic zone development.The experimental results reveal that the peak strength of sandstone is significantly controlled by fracture morphology,following the order:in-tact>filled fracture>prefabricated fracture.Based on the introduced damage factor P,the damage evolution of the three types specimens exhibits a trend of initial increase followed by a subsequent de-crease.The loading mode determines the crack propagation path,whereas fracture morphology gov-erns the failure mode:tensile failure dominates in intact specimens,tensile-shear mixed failure occurs in prefabricated fracture specimens,and shear failure prevails in filled fracture specimens.AE activity transitions from a quiescent stage to an active stage,with cumulative ringing counts increasing step-wise.A significant negative correlation exists between the b-value and cumulative ringing counts;the intact specimen maintains a relatively high b-value during the quiescent period,whereas the prefabri-cated fracture specimen exhibits the most pronounced b-value decrease at failure.Moreover,the peak frequency distribution differs markedly among specimen types.The internal stress of sandstone shows a gradient distribution positively correlated with local load intensity,with delayed peak strength across different regions.Stress gradients govern plastic zone evolution and determine crack propagation paths and coalescence behavior.This study provides theoretical insights for the support design of frac-tured rock masses and the stability evaluation of roadway surrounding rock.

Abstract:Dust generated by coal mining activities not only seriously threatens the occupational health of workers,but also causes environmental pollution and restricts the construction of smart mines.Dust prevention and control is a key issue that needs to be urgently addressed for safe,green,and intelligent mining in coal mines.Based on the concept of the whole life cycle,this paper constructs a theoretical framework and technical system of coal mine dust prevention and control covering six aspects:"dust generation-dust reduction-dust suppression-dust mitigation-dust re-moval-dust prevention".Based on a summary of the generation mechanism,influencing mecha-nism and diffusion law of mine dust,the research achievements of water injection for dust reduc-tion,foam for dust suppression,spray for dust reduction,ventilation for dust removal and personal protection theory and technology are expounded.Regarding water injection for dust reduction,the study focuses on analyzing the influence mechanisms of coal's physicochemical properties,pore wa-ter pressure,and hydraulic coupling effects on coal body seepage characteristics.It outlines techni-cal pathways to enhance water injection dust reduction efficacy through modifying coal properties and injecting modified fluids,while summarizing the application progress of this technology.Re-garding foam for dust suppression,this section reviews the principles of foam dust suppression alongside research advances and application in developing dust-suppressing foaming agents,foam preparation and spraying techniques.Regarding spray for dust reduction,it explores the latest find-ings on dust-capture theories involving the coupled action of dust particles and mist droplets,while outlining the development trends and current application status of spray for dust reduction technol-ogy.In the field of ventilation for dust removal,the technical advancements and practical outcomes of air curtains,wet dust collectors and dry dust collectors have been summarized.Regarding per-sonal protection,the dust filtering performance and mechanism of different filter materials are ex-plained,the classification and selection principles for individual dust respirators are defined,and the current domestic and international evaluation standards of individual dust respirators are com-pared.Finally,the key research areas and future development directions are proposed,aiming to provide useful references for promoting the technological progress of coal mine dust prevention and control.

Abstract:Accurate early warning of spontaneous coal combustion is the priority and difficulty of coal mine fire prevention and control.However,the traditional empirical model based on fixed thresholds has insufficient generalization capability due to the difficulty of adapting to the differences in coal quality and environment in different mining areas.To address this challenge,an intelligent early warning model for spontaneous coal combustion across mining areas that integrates data and physical drivers was proposed in this work.At first,the stage characteristics of CO,C2H4,and C2H2 as marker gases were clarified based on 102 sets of coal spontaneous combustion temperature programming experiments.And coal quality and environmental weighting factors were introduced to construct a four-level warning system for spontaneous coal combustion across mining areas with dynamically adjusted warning thresholds.On this basis,a data-physics fusion-driven early warning model was established by transforming the physical laws of coal oxidation process into learning fea-tures.The results show that among various algorithms,the random forest model exhibited optimal prediction performance(training:R2=0.99;testing:R2=0.93)and computational efficiency(prediction time<0.4 s)on experimental data.When directly applied to the Dafosi coal mine(fire scenario),the model accurately output high-temperature warning signals predominantly in orange and yellow.In contrast,at the Huibao coal mine(a safe scenario),it consistently maintained green safety warnings without any false alarms.These results validate that the early warning system and model developed in this study possess excellent cross-mining area adaptability and generalization ca-pability,providing an effective solution to the challenge of developing universally applicable predic-tion models for coal spontaneous combustion.

Abstract:To address the prevention and control needs for dynamic disasters easily induced by insta-bility of underground coal pillars,a constraint-enhancement and damage-monitoring method based on carbon-fiber composite mortar was developed.A systematic study was conducted by integrating theoretical analysis,COMSOL electric-field simulations,resistance monitoring,and uniaxial com-pression tests to thoroughly examine the mechanical strength,resistance change rate,and damage characteristics of coal specimens confined with composite mortars at different carbon-fiber contents.The results show that carbon fibers form a continuous network structure within the mortar matrix,enhancing the mechanical strength and electrical conductivity of the composite mortar,suppressing the migration of soluble charged ions,and shifting the conduction mechanism from ionic to elec-tronic conduction,thereby significantly reducing noise interference during resistance monitoring.At a carbon-fiber content of 2.0%,the composite mortar's resistivity is reduced by four orders of magnitude compared with plain cement mortar,the peak-to-peak noise in resistivity monitoring is reduced by five orders of magnitude relative to plain mortar specimens,and the compressive/tensile strengths increase by 136.6%and 135.1%,respectively.Wrapping coal specimens with carbon-fiber composite mortar applies circumferential confinement and enhances their mechanical strength;meanwhile,the composite mortar establishes preferential conductive pathways on the coal surface,making it more sensitive to crack propagation.With 2.0%carbon fiber content,the uniaxial com-pressive strength of the confined coal specimen increases by 25.0%compared with plain coal,and the stress sensitivity is 1.94 times that of coal specimens confined with plain mortar.When composite-mortar-confined coal specimens fracture,the stress-strain response and resistance change rate drop synchronously,enabling accurate identification of fracture events by capturing abrupt resis-tance signals.Using carbon-fiber composite mortar to confine coal specimens achieves simultane-ous mechanical reinforcement and real-time,non-destructive monitoring of the fracture process.These findings expand the application scope of carbon-fiber composite materials in mining and pro-vide a new technical pathway for damage monitoring of underground coal bodies.

Abstract:Aiming at the problem of easy collapse of backfill in downward slicing and filling mining,geo grid reinforcement technology is applied to the backfill to improve the strength of the artificial roof backfill.Triaxial compression tests were conducted on geogrid-reinforced backfills with rein-forcement positions of 1/3H,1/2H,and 2/3H and geogrid mesh sizes of 2,3,and 4 mm.The ef-fects of confining pressure,reinforcement position,and mesh size on the mechanical properties and failure characteristics of the reinforced backfills were investigated.The research results show that compared with the unreinforced backfill,the geogrid-reinforced backfill exhibits higher peak strength and more significant plastic deformation characteristics.There is an interaction effect be-tween the mesh size of the geogrid and the reinforcement position.When the reinforcement posi-tions are 1/3H and 2/3H,the peak deviatoric stress of the reinforced backfill shows a trend of first increasing and then decreasing with the reduction of mesh size;when the reinforcement position is 1/2H,the peak deviatoric stress of the reinforced backfill increases with the decrease of mesh size.With the increase of confining pressure,the decrease of mesh size,and the downward shift of the reinforcement position,the failure mode of the geogrid-reinforced backfill gradually transforms from shear-slip failure to shear-dilation failure or bulging failure.The presence of the geogrid can inhibit the propagation of cracks and sliding surfaces within the backfill.The reinforced zone formed by the synergistic effect between the geogrid and the top layer with a high cement-sand ratio,together with its lateral confinement effect,enhances the mechanical properties of the geogrid-reinforced backfill.The above research results can provide theoretical support for the practical application of geogrid-reinforced backfill in mining engineering.

Abstract:Under the"dual carbon"strategy,exploring the path of zero-carbon coal development is of great significance for ensuring energy security and promoting a green,low-carbon transition.This study focuses on the collaborative synergistic energy optimization,coal mine methane(CMM)drainage and utilization,CO2 sequestration and ecological carbon sequestration,establish-ing a comprehensive technological system integrating"emission reduction,energy substitution,CO2 geological storage and carbon recycling".Drawing on multi-disciplinary theory and field data from the Jin-Shaan-Mongolia mining cluster,the implementation roadmap,synergy mechanisms and ap-plicability limits were systematically analyzed,and a scalable route from laboratory validation to commercial deployment was identified.The results show that coordinated optimization of hybrid en-ergy systems significantly increases renewable energy accommodation and system flexibility.CMM drainage,coupled with a carbon market mechanism,shifts from a safety-only measure to a dual-purpose operation delivering both resource recovery and verified emission reductions.CO2 storage based on backfill in goaf combined with in-situ mineralization opens a new avenue for utilizing mined-out space.The ecological carbon sequestration,via land form reshaping and stress-resilient vegetation,establishes a viable pathway for transforming post-mining landscapes into active carbon sinks.The proposed system offers a comprehensive solution for zero carbon coal mining,and the ro-bust safety assessment of complex geological storage,techno-economic optimization and standard-ized protocols are recommended for future work,providing a technical benchmark for integrating the coal sector into the evolving energy system.