Achieving a synergistic improvement in the reactivity and attrition resistance of iron ore-based oxygen carriers remains a significant challenge in chemical looping combustion. In this study, potassium feldspar powder was employed to modify-iron ore oxygen carriers via surface loading, aiming to enhance their oxygen release performance and structural stability during redox cycling. A series of composite oxygen carriers were prepared by varying the loading ratios and methods for potassium feldspar loading. The reactivity and attrition resistance of the modified oxygen carriers were evaluated based on data of oxygen release rates and attrition rates obtained from thermogravimetric analysis and long-cycle fluidized bed experiments. In addition, the attrition mechanisms under different stress conditions and the modification effect of potassium feldspar were systematically investigated. The results showed that the oxygen release rates of the samples with 0.5 % and 3 % potassium feldspar loading reached approximately 5.06 % and 5.71 %, corresponding to increases of 22.8 % and 38.6 % relative to the unmodified sample. Furthermore, the sample with 0.5 % potassium feldspar loading exhibited an attrition rate reduced to approximately 2.65 %, representing a 52.6 % improvement in attrition resistance, primarily attributed to the fiber-bridging effect induced by potassium feldspar. These findings demonstrate that a 0.5 % loading of potassium feldspar effectively enhances both the reactivity and mechanical durability of iron ore-based oxygen carriers, providing a promising strategy for developing high-performance and cost-effective materials for chemical looping combustion.

The anti-punching drilling robot is essential for pressure relief operations in high-stress mines. Its accuracy in identifying coal and rock properties directly impacts drilling efficiency and pressure relief effectiveness. This paper addresses the current reliance on manual experience for coal-rock drilling state recognition, which suffers from low accuracy, long response times, and inability to meet unmanned drilling and pressure relief requirements. Based on a one-dimensional convolutional neural network (1DCNN) and long short-term memory (LSTM) combined with simulation experiments, a coal-rock properties recognition method for the drilling process is proposed. The model's recognition accuracy is enhanced by incorporating a convolutional block attention mechanism (CBAM), and the improved dung beetle optimization (IDBO) algorithm is employed to further optimize the model's hyperparameters, determining the optimal network parameter combination. Coal and rock drilling simulation test bench is constructed, featuring six types of representative coal and rock test blocks. Four categories of sensor signals, including rotation speed, rotation torque, feed speed, and feed pressure, are collected to conduct corresponding comparative testing and analysis. Results demonstrate that the proposed method achieves high coal-rock drilling recognition accuracy of 97.00%, significantly outperforming 1DCNN, 1DCNN-LSTM, logistic regression, support vector machines (SVM), decision trees, random forests, K-means clustering, and Transformer approaches.

At the top-coal caving face, accurately and quickly identifying the content of coal and gangue is an important prerequisite for intelligent and efficient mining. Data scarcity has been caused by the limited conditions in the mine, restricting the recognition of the coal-gangue mix ratio at the top-coal caving face. Therefore, this article proposes a method for identifying the coal-gangue mix ratio under insufficient sample conditions, based on improved auxiliary classifier generative adversarial network (IACGAN) and parallel coordinate and squeeze-and-excite attention (PCSA)-MobileNetV3. First, the coal-gangue vibration data are mapped into 2-D vibration spectral images. Then, the IACGAN is enhanced with a self-attention (SA) mechanism and residual structure to generate diverse, high-quality training samples despite sample deficiency. These generated images are then added to the dataset to expand the dataset size. Finally, the PCSA mechanism is integrated into the MobileNetV3 model to classify coal-gangue vibration spectral images based on the learned spatial and spectral features. The experimental results indicate that the proposed method outperforms superior recognition performance and effectively assists in the mix ratio recognition of coal and gangue under a small sample.

To detect frozen coal residue in railcars during winter transportation in mid-to-high latitude regions, this paper proposes a method using a spin-type multi-line LiDAR system. The LiDAR is positioned above the railcar, with its rotation axis aligned to the train’s direction, capturing point cloud data as the train moves. The data processing involves three steps: first, extracting point cloud data within the railcar’s range based on the LiDAR-railcar positioning; then correcting for contour tilt and motion distortion and stitching the data using a motion displacement fusion algorithm. Statistical filtering and voxel grid methods are applied to filter, simplify, and smooth the stitched data. Finally, a 360-degree ray and alpha-blending algorithm extracts contour slices used to estimate frozen coal volume. Experiments were conducted to optimize voxel grid size and slice spacing parameters. With optimal configuration, the proposed technique achieves over 93.5% accuracy, addressing the inaccuracy of manual estimation and supporting frozen coal removal planning.

Recognition of coal-rock in coal mining face is a significant prerequisite to ensure intelligent control and stable operation of the shearer. The main challenges of underground application are the potential safety hazards at the comprehensive mining face and the single cutting mode of the shearer, resulting in insufficient number of collected samples, unbalanced distribution, and interference with background information. To this end, a data generation method based on improved Wasserstein generative adversarial network with gradient penalty (WGANGP) is proposed for generating high-quality infrared thermal (IRT) images, which solves the problem of coal-rock recognition with limited samples. First, a conditional random field is incorporated into the generator for postprocessing the generated images to increase the accuracy of the GAN model in the boundary areas of the generated images. Second, an attention-embedded WGAN-GP is constructed to obtain global thermally relevant information of IRT images. Finally, coal wall cutting experiments prove that the improved WGAN-GP model can generate highquality coal-rock IRT images, and its performance is superior to that of other advanced GANs model.

Methane is a potent greenhouse gas, and mitigating its substantial emissions, primarily from coal mines with low concentrations, is among the most effective strategies to slow global warming. Catalytic combustion using transition metal oxides is increasingly pivotal in addressing this issue; however, the low-temperature activity of these catalysts limits their widespread application. In this study, we aimed to develop highly active and costeffective catalysts for large-scale combustion of low-concentration methane. To this end, a series of transition metal oxides (Cr2O3, Mn2O3, Fe2O3, Co3O4, NiO, and CuO) supported on open cell foams were synthesized, and their catalytic performance for methane combustion at 1 vol% CH4 was assessed in a fixed-bed reactor. Comprehensive characterization was conducted using XRD, SEM-EDS, XPS, H2-TPR, and O2-TPD techniques to elucidate the underlying mechanisms of CH4 catalytic combustion. Results demonstrated that the structured catalysts exhibited exceptional activity and thermal stability. Among them, NiO showed the highest activity, followed by Fe2O3 and Co3O4 with similar activity, and then Mn2O3, CuO, and Cr2O3 showing progressively lower reactivities. Complete CH4 conversion was achieved over NiO at approximately 500 degrees C, comparable to certain noble metal catalysts. The superior catalytic activity was attributed to the abundant reactive oxygen species, originating from chemically adsorbed oxygen and surface lattice oxygen transformations. Additionally, the rich oxygen vacancies facilitated CH4 dissociation and enhanced activity. This study provides an effective framework for advancing catalyst design to improve methane oxidation efficiency, thereby enhancing the practical management and utilization of low-concentration methane emissions from coal mining activities.

Drilling pressure relief is the primary measure for preventing and controlling impact ground pressure in high stress mines, while accurate identification of coal and rock in the drilling process is a prerequisite for improving the efficiency of drilling pressure relief and guaranteeing intelligent drilling operation. In this paper, we propose a novel time-frequency analysis method of electromagnetic reflected waves of coal and rock while drilling based on CWT and GAPSO-ROA to extract the key time-frequency information of electromagnetic signals for enhancing the accuracy of coal and rock recognition. First, coal and rock drilling electromagnetic detection experiment is carried out to obtain the electromagnetic signals, including lignite, bituminous, anthracite, shale, mudstone, and sandstone. Then, time-frequency analysis method is designed combining the continuous wavelet transform (CWT) and the hybrid swarm intelligence optimization algorithm (GAPSO-ROA) to extract the key time-frequency information of the electromagnetic signals, which more accurately identifies the coal and rock. The experimental results verified the superiority and feasibility of the proposed method.

The degree of effective utilization of biomass char depends on the rate of conversion of the elemental carbon in it, which is influenced by the physical and chemical structure of the biomass itself. Clarifying how physical and chemical structure properties of biomass char change during pyrolysis is a key issue in determining its subsequent utilization efficiency. In order to investigate the evolution of char structure during the high-temperature rapid pyrolysis of corn straw. In this paper, a corn straw high-temperature rapid pyrolysis system was designed and constructed, and the evolution of corn straw char at different temperatures and residence times was investigated by precisely controlling the pyrolysis parameters. The physicochemical structure of corn straw char was characterized by scanning electron microscopy and Raman spectroscopy (RAMAN), and the changes of char yield, pore development, chemical functional groups and carbon structure were explored. The results showed that the corn straw char yield decreased rapidly with increasing temperature and residence time, and the residence time of 5 s at 1300 degree celsius led to the fusion of surface ash to form attached molten ash balls. With the increase of pyrolysis temperature from 900 degree celsius for 5 s to 1300 degree celsius for 5 s, the specific surface area of corn straw char increased from 1.50 m(2)/g to 293.13 m(2)/g, and finally to 588.51 m(2)/g at 1300 degree celsius for 13 s. The pores were mainly distributed in the range of 2-10 nm. The high temperature and long residence time resulted in a more ordered char structure and increased concentration of aromatic rings. The increase in temperature breaks the C-O bond, -OH, leading to the release of oxygen functional groups and graphitization of the carbon skeleton.The C-C/C-H content increases from 80.25 % at 900 degree celsius for 5 s to 91.65 % at 1300 degree celsius for 5 s, whereas the C-O, C=O, and COO- content decreases. With the increase of pyrolysis temperature, the average number of aromatic rings increased and the number of surface methylene groups decreased. This study can provide a reference for the evolution of the structure of corn straw char and its subsequent utilization.

This work systematically investigated the reaction characteristics of cotton stalk pyrolysis volatiles with CuO and NiO loaded on olivine (Cu/Ni/O) aiming to produce hydrogen-rich gas. The effect of pyrolysis temperature, gasification temperature, and oxygen carrier to biomass ratio (OC/B) on tar content, gas yield, carbon conversion has been investigated. Lattice oxygen donation capability and catalytic performance of OC was evaluated by comparing the Biomass Chemical Looping Gasification (BCLG) and catalytic gasification. Furthermore, the distribution of oxygen in the pyrolysis products and the distribution of lattice oxygen in the gasification products were investigated. The results indicate that cotton stalk pyrolysis tar is mainly composed of phenolic compounds. The OC can not only decompose most of cyclic compounds but also further reduce the content of monocyclic compounds to hydrogen-rich gas. The release of lattice oxygen from Cu/Ni/O was 56.2 %, which decreased to 47.7 % when steam was introduced at 800 degrees C. A H2 concentration of 50.4 % and a H2 yield of 0.57 Nm3/kg were achieved by both the reaction of tar reforming and the reaction of steam with reduced Fe in Cu/Ni/O. These findings offer new insights and a theoretical foundation for a detailed understanding of the BCLG.

This study first draws inspiration from the dual biomimetic design of plant cell walls and honeycomb structures, drawing on their structural characteristics to design a flexible shell structure that can achieve significant deformation and withstand large loads. Based on the staggered bonding of this flexible shell structure, we propose a new design scheme for a large-load pneumatic soft arm and establish a mathematical model for its flexibility and load capacity. The extension and bending deformation of this new type of soft arm come from the geometric variability of flexible shell structures, which can be controlled through two switches, namely, deflation and inflation, to achieve extension or bending actions. The experimental results show that under a driving pressure within the range of 150 kpa, the maximum elongation of the soft arm reaches 23.17 cm, the maximum bending angle is 94.2 degrees, and the maximum load is 2.83 N. This type of soft arm designed based on dual bionic inspiration can have both a high load capacity and flexibility. The research results provide new ideas and methods for the development of high-load soft arms, which are expected to expand from laboratories to multiple fields.

During the chemical looping process, oxygen carriers are subjected to extremely challenging conditions, such as high temperatures, fluidization, and redox reactions, which significantly increase their susceptibility to attrition. Overall, particle attrition is caused by mechanical, thermal, and chemical stresses, but their exact contribution and mechanism are unclear. In this work, five distinct experimental conditions and cold jet attrition tests were established to discern the contributions of different stresses to attrition and their impact on performance. Particle size versus strength was obtained for up to 1320 particles, and hotspot plots were used to reveal the relationship between the two. It was found that thermal stress was the dominant factor only during the pre-attrition phase, contributing 45 % to attrition. And then swiftly superseded by mechanical stress. Chemical stress emerged as the primary cause of attrition during the middle and late stages of the experiments, contributing up to 90 % of attrition. OC's strength typically ranged between 6 and 8 N without chemical stress and, conversely, dropped to below 1 N. Furthermore, chemical stress was found to induce an increase in particle volume and oxygen transport capacity, primarily achieved by reducing apparent density. The volume of particles can be enlarged by a factor of 1.56, and the oxygen release rate was increased from 4 % to 5.6 % under chemical stress. And a correlation was observed between apparent density and both attrition rate and strength.

Longwall top coal caving (LTCC) mining technique is widely used in thick and extra-thick coal seams in China, India and Türkiye. Considering that the depth of coal seam varies widely (from 188 to 988 m in China), the different overburden pressure has great influence on the failure and drawing process of top coal in LTCC. In this paper, the top coal drawing mechanism considering overburden pressures was investigated through theoretical analysis, physical experiments and numerical calculation. The shape of the drawing body, coal–rock interface and recovery of top coal under different overburden pressure were analyzed deeply. The results show that the motion acceleration and fluidity of top coal particles increase first and then decrease with the increase of overburden pressure. When gangue-to-coal density ratio (γ) is larger than 1, the increasing of overburden pressure is beneficial to the recovery of top coal to some extent. With the increase of overburden pressure, the top coal boundary in the initial drawing stage gradually expands to the goaf, which increases the volume of the initial drawing body. The expansion of the initial drawing body’s width is attributed to the growth of the goaf-side width and is unrelated to the support-side width. With the increasing of the overburden pressure, the proportion of strong force chain gradually increases and the force arch is gradually formed between the goaf and the coal wall, which is conductive to the mixing of gangue form the goaf direction. This is the internal reason why the top coal recovery ratio decreases when the overburden pressure is too large. The “excessive coal drawing method” is proposed for deeply buried coal seams, which is conducive to recover more top coal and reduce the residual coal left in the goaf.

Human activities and industrial processes result in substantial methane emissions, predominantly at low concentration. This is particularly evident in coal mining where the gas concentration is notably low, posing challenges for effective utilization. Chemical looping catalytic oxidation (CLCO) is believed to be a potential approach for the disposal of ultra-low concentration methane (UCM) and the capture of CO2. Unlike pure air, which is generally used to oxidize OC in air reactor, UCM typically contains 0.1 similar to 1 %CH4 and less than 60 ppm H2S, therefore, the introduction of UCM into the air reactor would potentially threaten oxygen carrier (OC). In this study, the evolution of OC in CLCO process was investigated in terms of reaction performance and physicochemical parameters compared to traditional chemical looping process. XRD showed that the phase compositions of OC remained stable over 300 cycles and no sulfur-containing compounds were detected. The comparison showed that CLCO process negatively affected the performance of OC, especially for attrition. The attrition behavior of OC can be summarized in three stages: fines blowing out, steady-state attrition and intenseattrition stage. The main reason for increased attrition was attributed to methane oxidation, which released a large amount of heat and would impose a heat shock on OC. Contrary to the commonly reported "L"-shape, our data showed a "U"-shaped attrition rate trend in long-term cycles. The difference was that the attrition rate would suddenly increase after a certain number of cycles, indicating that the actual service life of OC may be significantly lower than predicted.

Coal spontaneous combustion (CSC) in goafs, one of the most serious disasters in coal mines, not only wastes resources and destroys the ecological environment, but also causes casualties. As global underground mining gradually shifts to the deep, this problem becomes increasingly prominent. Deep mining is operated in a complex mechanical environment characterized with high stress, high permeability, high temperature, and strong mining disturbance. To avoid stress concentration areas, narrow coal pillars are often utilized in roadway excavation along the goaf. However, narrow coal pillars are likely to fracture and lose stability during the mining process. Consequently, goaf areas of two adjacent working faces might connect, which promotes the CSC risk in the goaf. Most of the current researches are focused on CSC risk areas under shallow mining conditions and the CSC-gas coupling disasters, yet research on CSC risk areas in the goaf triggered by narrow coal pillars under deep mining conditions is rarely reported. Moreover, there is a lack of relevant means to prevent and extinguish fires. This study takes the narrow coal pillar-utilized 130,205 working face in Yangchangwan Coal Mine as the research object. First, the development of coal pillar fractures was simulated by adopting the discrete element method of PFC. Besides, on-site monitoring and FLUENT numerical simulation were conducted to identify CSC risk areas in the goaf of the narrow coal pillar-utilized working face. Finally, a double-pipe liquid CO2 injection technology was proposed for fire prevention and extinguishing. The following beneficial results were obtained. Affected by high stress in deep mining, the coal pillar collapses, which expands the range of the oxidation zone on the return side. Meanwhile, the adjacent goaf is also exposed to CSC risk. Double-pipe liquid CO2 injection can effectively reduce air leakage near the working face and suppress spontaneous combustion of residual coal by inerting the goaf. This study can provide guidance and reference for fire prevention and extinguishing in goafs under the condition of narrow coal pillar-utilized deep mining.

In coal pillar fires, the fire source is hard to be detected and the adjacent goaf is extremely likely to be affected. Such fires would give rise to thermal and dynamic disasters in mines, further causing casualties and environmental disruption. In this study, with the coal pillar spontaneous combustion (CPSC) accident in Chahasu Coal Mine taken as the research object, the oxygen uptake and limit of oxygen concentration of CPSC were explored. Based on the research results, a similar model was constructed, where a control group was used to simulate the hazardous area of CPSC in a bid to investigate the law of CPSC. Moreover, the polymer colloid perfusion system was constructed and the drilling parameters and perfusion process parameters were determined, and practices concerning spontaneous fire control were carried out. Here are the conclusions: First, air leakage in the coal pillar may lead to coal spontaneous combustion due to the impact of rib spalling, threatening 2-6 m above the middle of the coal pillar at a shallow position. Second, coal pillar grouting, injecting polymer colloids for cooling, and coal pillar cement reinforcement prove to be effective ways to prevent CPSC fires and combat recombustion.

Pyrolysis is considered as an effective method to convent coal tar residue (CTR) with carcinogenic polycyclic aromatic hydrocarbons into high value-added products. However, high contents of heavy components in tar restrict the efficient utilization of CTR. In this paper, USY zeolite was leached by HNO3 and subsequently loaded by Zr and Ni for upgrading of CTR pyrolysis volatiles. The effects of the modified catalysts on the distribution of pyrolysis products, the yield and compositions of light tar (boiling point below 360 degrees C) were investigated. Results showed that compared with raw USY, the modified USY with HNO3 leaching for 2 h (UN2) improved light tar fraction up to 63.55 % and naphthalene content in tar increased by 96.01 %. The contents of toluene, xylene and naphthalene in tar were 32.00 %, 32.89 % and 11.57 % higher than that of UN2 and light tar fraction was improved up to 66.00 % when 10 wt% Zr was introduced into UN2 (10Z-UN2). Ni loading resulted in further upgrading of the tar. The fraction of light tar was up to 73.13 % at Ni content of 8 wt% (8Ni-10Z-UN2), and toluene content in upgraded tar was 3.56 times that over 10Z-UN2. To further improve the upgrading performance, steam was introduced in the action of 8Ni-10Z-UN2. The highest yields of tar (41.56 wt%) and light tar (31.07 wt%) were obtained at the mass ratio of steam to material (S/M) being 0.28, and the average molecular weight of tar was decreased to 219 amu from 744 amu before upgrading. Isotope tracing using D2O as tracer was coupled with the cracking of cetane, m-cresol and 1-methylnaphthalene as tar model compounds over 8Ni-10ZUN2 to reveal the mechanism for high tar yield under steam. It was confirmed that center dot H produced by reaction of H2O with model compounds participated in tar formation over 8Ni-10Z-UN2, and the contents of benzene and naphthalene were obviously enhanced. This work provides a sample route to upgrade the CTR pyrolysis volatiles into aromatic hydrocarbons.

The outcrop fire area in Rujigou Coal Mine in Ningxia, China has been burning continuously for over 100 years. This not only results in wastage of resources but also poses significant damage to the ecological environment. Previous research on open fire detection has mainly focused on coalfield fire areas, using single method such as infrared remote sensing or surface temperature measurement, magnetic method, electrical method, radon measurement and mercurimetry. However, the outcrop fire area has migrated to deeper parts over the years, conventional single fire zone detection methods are not capable of accurately detecting the extent of the fire zone, inversion interpretation is faced with the problem of many solutions. In fire management, current research focuses on the development of new materials, such as fly ash gel, sodium silicate gel, etc., However, it is often difficult to quickly extinguish outcrop fire areas with a single technique. Considering this status quo, unmanned aerial vehicle (UAV) infrared thermal imaging was employed to initially detect the scope of the outcrop fire area, and then both the spontaneous potential and directional drilling methods were adopted for further scope detection in pursuit of more accurate results. In addition, an applicable fire prevention and extinguishing system was constructed, in which three-phase foam was injected for the purpose of absorbing heat and cooling. Furthermore, the composite colloid was used to plug air leakage channels, and loess was backfilled to avoid re-combustion. The comprehensive detection and control technologies proposed in this study can be applied to eliminating the outcrop fire area and protecting the environment. This study can provide guidance and reference for the treatment of other outcrop fire areas.

This paper uses PFC 2D software to carry out DEM numerical simulations of coal caving, calculates the top coal recovery under the same coal seam thickness and different rock layer thicknesses, analyzes the influence of the rock layer thickness on the top coal caving law in two different stages, and explains the necessity of a thick rock layer and the optimal thickness of the rock layer. The results show that as the thickness of the loose gangue layer increases from 1 to 8 m, the recovery ratio of top coal increases from 84 to 96%, showing zigzag growth. The lateral diameter of the drawing body gradually increases. Due to the particularity of the coal caving method, in the subsequent coal caving stage, the uneven thickness of the top rock layer causes the direction of the drawing body to change, and the existence of a coal ridge causes the displacement field on the right side of the rock to be larger than that on the left side above the drawing opening. This leads to different sizes of the left and right secondary coal ridges. Through simple geometric relationship analysis, this paper explains the principle that gangue particles intrude into coal seams due to the weakening of rock constraints and an increase in the free movement of coal particles. This further demonstrates the necessity of a loose and thick rock layer. The optimum thickness of the rock layer and the relationship between the thickness of coal and rock and parameters of coal caving are calculated. Finally, the necessity of a thick rock layer is extended to three typical top coal caving methods to verify the universality of this necessity.

The recovery ratio of longwall top coal caving (LTCC) technology is an important measure of its effectiveness. However, the recovery ratio of single-opening sequential caving technology in thick and extra-thick coal seams needs improvement. To address this, an independent cluster-group caving technology is proposed in this study. Four numerical simulation experiments were conducted to compare the recovery ratio and drawing balance of four-opening independent cluster-group caving technology and single-opening sequential caving technology. Results show that the recovery ratio in four-opening independent cluster-group caving technology is approximately 6% higher than in single-opening sequential caving technology when the thickness of the broken gangue layer and the coal seam are the same. Additionally, a judgment formula for the broken immediate roof thickness is provided when the top coal recovery ratio is seriously affected. The independent cluster-group caving technology demonstrates stronger stability and better adaptability under different conditions, as its caving sequence can prevent larger thickness changes and gangue disturbances during the drawing process. Overall, this study highlights the potential of independent cluster-group caving technology to improve the recovery ratio of LTCC technology in thick and extra-thick coal seams.

Dynamic sublevel caving technology (DSCT) proposed by the researchers is one of effective methods to solve the problems of low top coal recovery, poor drawing balance and support stability in longwall top coal caving (LTCC) with large dip angle. To investigate the reasonable number of supports in a sublevel (N) and the top coal drawing mechanisms under DSCT, this research takes Panel 7401 in Zouzhuang Coal Mine as the geological background. Firstly, the optimal threshold value of N is theoretically analyzed, and the numerical simulations of drawing experiments under different Ns are calculated. The results show that when N = 3, the top coal recovery is the highest, the number of excessive drawing top coal at the upper end is relatively small, and the drawing balance is great, which is conducive to improving the resource recovery and safety management. With increasing N, the over-development of right top coal boundary towards the upper end increases, the range of coal ridge in the lower sublevel also gradually increases, while the strong force chain area at the upper end gradually decreases, resulting in the support stability becoming worse. In addition, the displacement of top coal at the upper end gradually increases with increasing N, and the permanent loss feature of residual top coal exists in the upper sublevel. The field top coal recovery under DSCT was measured finally, obtaining that DSCT can improve the top coal recovery by about 5