Accurate and reliable personnel positioning in underground mines is critical for safety management and emergency response. However, conventional positioning systems, which rely heavily on fixed infrastructure such as communication networks and continuous power supply, become ineffective during power outages or network failures, severely hindering rescue operations and evacuation efforts. We propose an autonomous positioning method for long linear tunnels that operates independently of external infrastructure, in which a novel Base Station Cluster comprising multiple MEMS UWB (Micro-Electro-Mechanical System Ultra Wide Band) sensors serves as a reference framework for real-time location estimation. The positioning coordinates are then solved via a Constrained Sequential Quadratic Programming (CSQP) algorithm by measuring distances between this Base Station Cluster and the target. Solve the problem of the lack of personnel positioning methods in the event of power and network disconnection during emergency rescue. Experimental results demonstrate that the system achieves static three-axis coordinate accuracy within 1 m in both elongated indoor corridors and underground tunnel environments. Under dynamic conditions, the three-axis coordinate accuracy of this method reaches within 1.5 m. Under complex scenarios conditions, the three-axis coordinate accuracy remains within 1.5 m, with the algorithm exhibiting good robustness in scenarios involving bumpy motion and signal obstruction.

To improve the prevention of coal spontaneous combustion (CSC) and overcome the poor durability of traditional inhibitors, a novel double-network (DN) biomass hydrogel, termed SGPGc, was developed. It was synthesized from sodium alginate (SA), gelatin (GEL), poly-(vinyl alcohol) (PVA), and glycerol (GL) via a CaCl2-borax dual cross-linking system. The Ca2+-SA ionic network constituted a rigid skeleton, whereas the dynamic borate bonds between B-(OH)4 - and PVA provided toughness and self-healing capability. This synergy endowed SGPGc with a high tensile strength of 16.25 MPa and a fracture elongation of 286.07%, ensuring tolerance to harsh underground mining environments. The hydrogel also exhibited excellent thermal stability and water retention, showing only 38.6% water loss at 90 °C, coupled with a high rehydration capacity of 37.73 g/g (dry weight basis) for the dried film, which enabled dynamic cooling and functional regeneration. Structural analysis revealed that SGPGc significantly reduced the total pore volume and specific surface area of coal by 47.23 and 50.25%, respectively, effectively blocking oxygen diffusion channels. Furthermore, its water retention capability enabled sustained cooling, while its high rehydration capacity facilitated secondary sealing. In comparison with raw coal, the SGPGc-treated samples showed significantly reduced CO generation and production rate, along with substantially increased crossing point temperatures (CPT, up by 33.7 and 29.0 °C). The demonstrated inhibition efficacy surpassed that of conventional calcium chloride, confirming the operational closed-loop synergistic mechanism of "barrier-cooling-functional regeneration" in effectively inhibiting CSC.

Coal mine conveyor belts undergo thermo-oxidative aging, mechanical wear, and surface contamination during long-term service, which can alter their pyrolysis behavior and fire hazard. In this study, unused and in-service steel-cord PVG conveyor belts were comparatively investigated by scanning electron microscopy coupled with energy-dispersive spectrometry (SEM–EDS), thermogravimetry Fourier transform infrared spectroscopy-mass spectrometry (TG-FTIR-MS), and cone calorimetry. The results show that the used belt exhibits more severe abrasive damage, denser microcracks, more developed pore structures, and clearer surface enrichment in Cl. Under Ar, the peak temperatures of HCl release shift to lower values by 108.92 °C, while the peak temperatures of CO and CO2 decrease by 101.33–125.15 °C. Under air, the peak temperature of HCl decreases by 12.77

To solve the adverse effect that temperature rise from static expansive agents (SEAs) hydration deteriorates coal thermal stability, CO2 is adopted to synergize SEAs hydration to develop coal fracture networks, improve gas drainage efficiency and ensure safe gas extraction. In this work, multiple characterization tests including scanning electron microscopy (SEM), low-temperature nitrogen adsorption, true and apparent density measurement, in-situ Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG-DTG) and temperature-programmed oxidation are carried out to systematically analyze the pore-fracture morphology, surface functional groups and pyrolysis-oxidation behaviors of coal under single SEAs treatment and CO2-assisted SEAs modification. The results show that CO2 generates coupled hydration expansion and carbonation crystallization stresses to construct interconnected pore-fracture networks, and coal porosity increases by 6.5%–65.5% within 3–24h compared with solely hydrated coal samples; adsorbed CO2 covers active sites on coal surfaces and reduces the thermal loss of -OH, C=O and -COOH groups by 16.2%–27.3%, lowering the total pyrolytic mass loss by 3.3%, while the inert CO2 atmosphere suppresses coal oxidation and decreases the peak release rates of CO, CH4 and C2H6 by 1.3%–18.6%. Optimized pore channels and stabilized surface functional groups work together to avoid local heat accumulation and secondary thermal decomposition reactions, and this study clarifies the coupling mechanism of pore evolution, functional group protection and oxidation inhibition, which provides theoretical support for safe permeability enhancement of low-permeability coal seams.

The gaseous composition of the goaf atmosphere represents a critical factor governing processes of coal spontaneous combustion, creating essential need to investigate how varying CO2 concentrations influence the characteristics of coal spontaneous combustion (CSC). This study systematically examined effects of different CO2 concentrations on CSC through temperature-programmed gas chromatography and in situ infrared spectroscopy experiments, combined with numerical simulations to analyze impact of CO2 injection on oxidation zone area before and after implementation. The study revealed that CO2 concentrations above 30

This study analyzed mechanical response patterns induced by explosion shock waves in coal mine roadways by integrating biomechanical and engineering perspectives. A three-dimensional (3D) reconstructed human body model was coupled with a fluid-dynamics explosion model to quantify biomechanical vulnerability under different explosion conditions. Geometric models of the human body, including muscles, bones, and internal organs, were reconstructed along with the actual roadway structures. An ALE-based Chapman-Jouguet (CJ) detonation model was adopted to simulate shock wave propagation around the human body in the roadway. The model was used to assess mechanical loading severity under different conditions. Results indicated that the overpressure near the body was approximately three times that measured 1.25 m in front of it. The seated posture exhibited overpressure levels 20%-30% higher than those in the other postures. The predicted mechanical responses showed a clear "distance-orientation effect", with distal limbs being most vulnerable. Among all body regions, the feet exhibited the highest mechanical vulnerability, with element failure ratios reaching up to 55%, whereas the trunk showed the lowest. Stress distribution within internal organs exhibited a pattern of being lower in upper regions and higher in lower regions. Based on the proposed comprehensive impact index (CII), the mechanical loading levels were ranked in the following order: sitting > standing > running. The findings provide theoretical support for emergency rescue and injury prevention in coal mine explosion accidents.

Driven by the low-carbon transition, a zero-cement quaternary cementitious material (GCCP) was developed by integrating circulating fluidized bed fly ash (CFB) and pulverized fuel ash (PFA) into a granulated blast furnace slag (GS)-carbide slag (CS) system. The synergistic mechanisms effects of CFB and PFA governing rheology, mechanical properties and hydration in GCCP were elucidated. The economic and environmental benefits of different mix designs were evaluated. Mechanical results reveal a staged optimization: Compared to GCC0P0 (without CFB and PFA), GCC14P6 (14 % CFB, 6 % PFA) achieves the highest 3-day strength (7.62 MPa, a 21.92 % increase) driven by sulfate-activated AFt formation, whereas GCC10P10 (10 % CFB, 10 % PFA) yields the maximum 28-day strength (25.56 MPa, a 34.62 % increase) as PFA promotes long-chain C-(A)-S-H polymerization. Rheologically, the spherical PFA exerts a lubrication and dilution effect, counteracting the flow resistance induced by the porous CFB. Mechanistically, the synergy boosts mineral reactivity via a time-dependent process: sulfate release from CFB accelerates early nucleation, while aluminum supplementation from PFA promotes latestage polymerization, further evidenced by earlier exothermic peaks, an induced third hydration heat peak and a microstructure dominated by highly polymerized gels. Environmental performance evaluation demonstrates that the optimal mix GCC10P10 reduces Global Warming Potential and cost by 92.06 % and 34.62 % compared to 32.5 R cement, suggesting its potential as a sustainable, high-performance construction material.

To address the issue of fluid loss leading to pressure failure when applying temporary plugging fracturing technology from the oil industry to enhance gas recovery in coal mines, and considering the current low efficiency of CO2 solidification and utilization, a new method is proposed to inject SC-CO2 and hot alkali solution together into coal to produce solidified particles as temporary plugging agents for solidification and utilization of CO2 and fracturing transformation of coal. At present, the mechanisms governing pressure increase during temporary plugging with solidified CO2 particles, as well as the relationship between internal pore and fracture pressures after plugging and fluid loss rate, remain unclear. Based on CT images, a complex geometric model of interconnected pores and fractures of coal is constructed. The morphology of solidified CO2 particles is obtained via microscopic scanning, and conducts numerical simulation research on fluid solid coupling. Clearly define the pressure and flow distribution inside the coal under different temporary plugging positions and injection conditions. Revealing the pressure and fluid loss law inside the coal after temporary plugging. The results show that when particles are temporary plugging at different positions, the average internal pressure in the coal ranges from 8.05 MPa to 12.03 MPa. The fluid loss rate varies from 0.037 cm3/s to 0.152 cm3/s. Establish equations for the relationship between injection pressure, fracture size, temporary plugging location, internal pressure, and fluid loss rate, with a fitting formula R2 of 0.988. Furthermore, an experimental setup and methodology involving supercritical CO2 and hot alkali liquor injection were designed to validate the accuracy of the numerical simulation results regarding pressure enhancement and fluid loss under solidified particle plugging. This study provides theoretical support for enhanced coalbed methane recovery and the development of integrated technologies for underground CO2 storage and hydraulic control of gas emissions.

Fires originating from belt conveyors present significant hazards in coal mines, necessitating prompt and accurate localization of fire sources. This study proposes a novel fire source location algorithm predicated on the distribution patterns of characteristic gases within coal mine tunnels. This method combines a three-dimensional Gaussian plume gas diffusion model applicable to confined tunnel spaces with a hybrid GA-PSO (genetic algorithm particle swarm optimization) algorithm. To validate the approach, the conveyor belt combustion experiments on the small-scale tunnel were performed, complemented by numerical simulations, to characterize the spatiotemporal distribution of HCl (Hydrogen Chloride) during combustion. In practical application, HCl concentration data from sensors are utilized in an inversion calculation, leveraging the optimized diffusion model to determine the precise fire source coordinates. Findings indicate that the relative error of the predicted location information is small, the error is reduced by 87.5-91.7% compared with other algorithms, and the location accuracy is more than 98%, validating its effectiveness and feasibility for fire source identification in the challenging subterranean conditions of coal mines. This work strengthens the mechanistic link between characteristic-gas evolution and fire location, providing a quantitative tool to optimize sensor layout, accelerate fire detection, and support more timely evacuation and emergency response in underground coal mines.

Early prevention and control of coal spontaneous combustion have emerged as a critical research area in coal mine safety. Due to their sustainability and environmental friendliness, microorganisms have gained attention. A filamentous fungus was collected in the coal mine and identified as Absidia spinosa. Results indicated that the mycelium effectively covered and repaired many coal pores. The oxygen consumption ratio of A. spinosa was higher in coal-containing environments than in coal-free conditions. The fungus significantly impacted aliphatic functional groups, disrupting bridging bonds and side chains connected to aromatic structures and reducing the relative content of CAO bonds. Additionally, A. spinosa increases the ignition temperature by 25.34 degrees C. The total heat release was decreased by approximately 32.58 %, and the activation energies were increased. The genome of Absidia spinosa revealed genes related to oxygen consumption, small molecule degradation, and secretion of metabolic products, such as those annotated under GO ID: 0140657, etc. The pathways involved in the degradation of small organic molecules (e.g., ko00626, etc.), carbon fixation, and nitrogen cycling, all linked to coal decomposition. Through oxygen consumption and the alteration of coal-active structures, A. spinosa effectively inhibits CSC, providing an experimental basis for exploring eco-friendly biological control methods in the goaf. (c) 2025 China University of Mining & Technology. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Optimizing the droplet size can effectively enhance the performance of spray dust suppression. The current predictive model for predicting the volume median diameter (D-50) fails to accurately reflect the dynamic changes of D-50 along the process. Based on the existing empirical equations and combined with the three highly relevant influencing factors of atomizing nozzle type, water supply pressure and orifice diameter, the spray characteristics parameters of flow rate, atomization angle and maximum range of the three intermediate links are constructed to predict the axial median particle size of the single-fluid pressure nozzle. The model explicitly accounts for the competition between liquid breakup and droplet coalescence by introducing a coalescence growth term to characterize the observed increase in D-50 at downstream locations. It is applicable for predicting D-50 in spray fields of circular orifice nozzles with an axial distance greater than 5 cm. Results demonstrate that the proposed model accurately predicts the axial variation of D-50 across the spray field. A critical distance (L-CRIT), corresponding to the minimum D-50 value and located within the vicinity of adjacent measurement points, is identified: D-50 decreases monotonically from the nozzle exit to L-CRIT and subsequently increases from L-CRIT to the maximum spray range. The model achieved the average absolute relative deviation of approximately 11% and the root mean square error of no >27 mu m, which confirmed the stability of the model. The L-CRIT of the average out-of-bound error was also within an acceptable range, indicating that the D-50 can be accurately predicted.

To study the risk of coal spontaneous combustion (CSC) in goafs under poor oxygen concentrations, lignite, gas coal, and fat coal were selected as experimental samples for thermal analysis. The thermogravimetric curves and kinetic parametric equations of coal with different metamorphisms at oxygen concentrations of 18%, 14%, 10%, 5%, and 3% were studied. The results showed that the higher the degree of coal metamorphism, the lower the tendency for the oxidation reaction and spontaneous combustion. With the decrease of oxygen concentration, the weight loss rate of coal gradually decreased, and the apparent activation energy gradually increased. However, the heat release of CSC first increased and then decreased, with the greatest heat release when HM was at a 14% oxygen concentration, QM at 10%, and FM at 18%. On this basis, the thermal analysis parameters of CSC under different metamorphisms and oxygen concentrations were analyzed by fuzzy clustering, and coal was divided into two categories: spontaneous combustion risk and no spontaneous combustion risk. Combined with lattice tightness, the risk of CSC under different metamorphisms and oxygen concentrations can be determined.

To address the problem of spontaneous combustion of residual coal in goaf of gently inclined coal seams, a numerical model of gas migration in goaf was established based on the porous medium model and gas component transport equation. The influences of injection position and flow rate of pure CO2 and CO2-N2 mixture on the distribution range of the “three zones” in goaf were investigated, and the gas migration law under CO2-N2 mixed inertization was analyzed. The results show that when CO2 is injected from the intake air side to inertize the goaf, the area of the oxidation zone first decreases and then increases with the increase of the distance between the CO2 injection position and the working face. With the increase of CO2 injection rate, the oxidation zone area decreases, and the CO2 migration pattern presents a “trumpet shape”, forming “inertization blind zones” near the working face on the intake air side and in the middle of the goaf. When CO2 is injected on the intake air side and N2 on the return air side for mixed inertization, the oxidation zone area first decreases and then increases with the increase of the distance between the N2 injection position and the working face. With the increase of N2 injection rate, the oxidation zone area decreases, and the N2 migration pattern shows a “wave shape”, which reduces the area of the “inertization blind zone” in the goaf. The optimal inertization effect is achieved when the CO2 injection position is 40 m from the working face with an injection rate of 750 m3/h, and the N2 injection position is 50 m from the working face with an injection rate of 750 m3/h. Under these conditions, the CO2 volume fraction in the return airway does not exceed 1.5%, the oxidation zone area decreases from 4 100.445 m2 to 2 463.205 m2, which is 14.84% lower than that under single CO2 inertization. An “isolation zone” is formed in the middle of the goaf, which effectively restrains the migration of O2 to the deep goaf.

The fusion of geomagnetic and PDR positioning is a crucial research direction for autonomous underground personnel localization. A significant challenge in this approach is promptly and accurately determining the weights of geomagnetic matching results during the fusion filtering process. This study introduces a novel Suitability Evaluation method based on Sliding Window Geomagnetic Features (SE-SWGF), providing a rigorous computational framework to iteratively determine weights within the Kalman filter used for geomagnetic and PDR positioning fusion. The proposed method comprises three main steps: selecting optimal geomagnetic features from frequency and spatial domains, constructing a suitability evaluation model, and dynamically adjusting weights during the geomagnetic and PDR fusion filtering. Experiments conducted with over 2,000 sliding window data samples collected from 120 different roadways-including building access routes, emergency drill passages, gold mines, phosphate mines, and coal mines-identified The 1st Mel-frequency cepstral coefficients (MFCC1), standard deviation, roughness, fractal dimension, coefficient of variation, and entropy as critical features strongly correlated with geomagnetic matching suitability. Moreover, the threshold-constrained decision tree approach significantly reduces computational costs compared to the RBF neural network model, while maintaining high accuracy exceeding 81.75 %. Additionally, this method significantly improves the accuracy of fusion positioning. With dynamic weight adjustments based on SE-SWGF evaluation results, positioning errors were reduced below 2.32 m in the X-direction and 2.85 m in the Y-direction, maintaining overall localization errors within 3.5 m and demonstrating improved convergence. Compared to standalone PDR positioning, fusion positioning accuracy improved by 90.43 % (X-axis) and 89.22 % (Y-axis). Compared to standalone geomagnetic positioning, accuracy enhancements were 24.75 % (X-axis) and 23.10 % (Y-axis).

Under the context of intelligent coal mine development, this study reviews the research progress in optimizing the performance of gas extraction pipeline network and intelligent control for promoting efficient and intelligent gas extraction. Specifically, a composition framework for gas extraction pipeline network was established, and the fluid flow laws within the pipeline network were elucidated. A "static-dynamic" two-dimensional framework was established based on the existing performance optimization technologies for gas extraction pipelines. The static optimization technologies can enhance the system's inherent performance through pipe material selection, structural redesign, and fault diagnosis, while the dynamic optimization technologies can dynamically adjust pump and valve parameters based on multi-source data sensing and intelligent evaluation to ensure real-time optimal operation of the pipeline network system. The present performance optimization and intelligent control technologies face such limitations as the lack of a universal model for pipeline network topology design, insufficient visualization and verification of abnormal conditions, and weak coordination among intelligent algorithms. To address these challenges, this study proposed to determine optimal combinations of parameters such as pipe diameter and slope by combining orthogonal experiments with the Analytic Hierarchy Process; develop a testing platform for simulating abnormal operations and control of mine gas extraction pipeline to replicate operating conditions such as leaks, blockages, and deformation; integrate various data mining and neural network algorithms to establish more effective intelligent control models. This study can provide guidance and reference for promoting intelligent and efficient coalbed methane extraction and ensuring the safe and sustainable development of coal mines.

The development of intelligent positioning requires a new method of low-cost to meet the needs of autonomous positioning or emergency positioning underground. A new method of Baseline Radio Frequency Magnetic Dead Reckoning (Baseline-RFMDR) autonomous positioning is constructed in this paper, to solve the problems of low accuracy of geomagnetic matching positioning and large cumulative errors in Pedestrian Dead Reckoning (PDR) positioning, which provides a new approach for high-precision and stable autonomous positioning of underground personnel. This method combines PDR positioning and geomagnetic matching positioning, with the constraint of baseline distance, which is the distance from the Tag Pair to the reader. The Kalman Filter solution equation for this model is constructed, and the recursive equation for the covariance matrix under baseline constraints is derived. An underground positioning test was conducted using the self-developed Baseline RFMDR positioning device, the results showed that the accuracy of this combined positioning method is significantly better than PDR positioning or geomagnetic matching positioning. At normal speed, the MAE and RMSE of Baseline-RFMDR combined positioning can be kept within 0.12 m in the X direction and within 0.2 m in the Y direction. It is 88% more accurate in the X direction than PDR, 60% more than geomagnetic matching, 70% more in the Y direction than PDR, and 75% more than geomagnetic matching. At fast speed, the MAE and RMSE of Baseline-RFMDR combined positioning can maintain 0.2 m in the X direction and 0.61 m in the Y direction. It is 79% more accurate in the X direction than PDR, 21% more than geomagnetic matching, 49% more than PDR in the Y direction, and 46% more than geomagnetic matching. At the same time, Baseline-RFMDR positioning has good robustness. When the initial coordinate error or initial covariance error or Baseline-RFMDR partial failure, the MAE and RMSE of Baseline-RFMDR combined positioning can still be maintained within 0.24 m.

Personnel autonomous positioning based on Micro Electro Mechanical Systems(MEMS) is a crucial research direction for active positioning and emergency response in mines. During MEMS-based autonomous positioning, it is imperative to evaluate the data suitability of magnetic match positioning in mine tunnels, which for weight adjustment during integrated positioning processes. To address the limitations of existing geomagnetic suitability evaluation methods, a novel Geomagnetic Matching Suitability Evaluation method incorporating Spatial and Frequency-domain features (GMSE-SF) is proposed. This method enables quantitative evaluation of the area's suitability by modeling the correlation between matching probability and suitability features using a radial basis function Radial Basis Function(RBF) neural network. The suitability features include five spatial features and three frequency-domain features derived from Mel-cepstral coefficients. These features are uniformly weighted using the Criteria Importance Through Intercriteria Correlation(CRITIC) method, which provides the initial weights for the model input parameters. Experiments were conducted in 202 tunnels across five types of areas, including building corridors, emergency response tunnels, gold mines, coal mines, and phosphate mines. Static and dynamic magnetic data were collected by a CH-530 fluxgate magnetometer and an inertial measurement unit (IMU). The experimental results demonstrate that the spatial and frequency-domain features of different types of tunnels exhibit distinct trends. However, the three Mel-cepstral coefficients derived from the magnetic measurement data can effectively represent the majority of frequency-domain features. The combined features provide a more accurate representation of the magnetic variation characteristics in underground tunnels.The GMSE-SF method achieves a suitability evaluation accuracy of approximately 96 %, which is significantly higher than the accuracy of traditional decision-based evaluation methods (around 50 %). Notably, under conditions with 20 % random noise-induced magnetic disturbances, the proposed method maintains an suitability evaluation accuracy of over 93 %.

The automatic ventilation door in mining operations is a crucial component for ensuring production safety and maintaining ventilation system stability. However, the primary power element of this equipment—the cylinder—often lacks effective monitoring, which can compromise operational reliability. To address this gap, this study proposes a Weibull life prediction method, integrating Bayesian inference and Monte Carlo simulation, aiming at anticipating changes in cylinder reliability. This proactive approach supports timely maintenance to prevent. Given the unknown shape and scale parameters of the Weibull distribution, Bayesian methodology is applied, alongside accelerated life testing principles, to analyze the life characteristics of cylinder. By deriving the posterior distribution function of Weibull parameters, Monte Carlo simulation is employed to estimate these parameters across various operational conditions. This method reveals how life characteristics relate to environmental factors such as temperature. Following the constant-failure-mechanism assumption used in accelerated life testing, the characteristic parameters of cylinder characteristic parameters under standard operating conditions are predicted. Results show that this method is effective for life prediction using truncated small-sample data, overcoming the limitations of conventional approaches. Its applicability is proven in the life assessment of automatic ventilation doors, offering a robust tool for reliability. A reliability evaluation system for mine emergency control equipment is developed. This system provides real-time assessments and visualizations of equipment reliability, enhancing maintenance and management practices essential for mining operations.