China University of Mining and Technology - Beijing

To meet the urgent market need for implementation of various heavy-load operations within complex and restricted underground environments, this paper proposes a new scientific structural development scheme for underground heavy-load robot. The scheme combines topology optimization and modular scale synthesis to achieve the optimal configuration for underground heavy-load robot. Firstly, orienting to the specific working environment and design requirements, a feasible configuration was deduced by the configuration synthesis method. Then, the topology optimization was carried out to output a new stable configuration for underground heavy-load robot with good flexibility and stability. Secondly, the modular design idea was applied to realize the optimal scale synthesis and function expansion of underground heavy-load robot. Finally, based on the kinematic analysis model, a reasonable and effective performance evaluation system was established to verify the performance of underground heavy-load robot. Simulation and experimental results indicated that the underground heavy-load robot developed in this paper had a more reasonable structure and more comprehensive functions. It can fully meet the design requirements of flexible operation and high carrying capacity in the confined underground space. The research in this paper provides new ideas for the structural development of heavy-load robot, effectively enhances the design efficiency of spatial multi-freedom degree industrial robot, and lays a foundation for the coordinated control of modern intelligent robots.

Amplitude variation with offset inversion is a crucial step in estimating subsurface elastic parameters. However, the inversion is always implemented by a single trace, and there is no connection between adjacent gathers to ensure the lateral accuracy. Although there is not much consideration for lateral inversion, traditional total variation (TV) regularization based on model constraints can improve the accuracy of vertical inversion. To address this issue, we propose a new prestack inversion method, multi-trace exact Zoeppritz equation inversion with TV joint Diff constraints (MEZTD), which adds lateral data difference (Diff) constraints to multi-trace simultaneous inversion with TV regularization. The Diff is the difference between the groups of adjacent common depth points, ensuring that the synthetic and observed data exhibit consistent lateral variations. By constraining the inversion results based on the lateral variation of seismic data, the method enhances both lateral continuity and accuracy. To validate the effectiveness of the MEZTD method, we conducted inversion experiments on a selected portion of the Marmousi model and field seismic data. A comprehensive analysis was performed on the effects of TV regularization and the Diff constraint individually, demonstrating that the incorporation of the Diff constraint significantly improves lateral accuracy and noise resistance in the inversion results. The results confirm that the MEZTD method provides superior noise resistance, enhanced lateral inversion accuracy, making it a robust approach for high-resolution prestack inversion.

Liquid nitrogen, as a kind of ultra-low-temperature medium, has an important application in the process of fire prevention and extinguishing in the goafs. The change of ventilation conditions will affect the efficiency of liquid nitrogen fire prevention and extinguishing. Therefore, this paper builds a large-size experimental platform to study the influence of ventilation conditions on the mass and heat transfer of liquid nitrogen vaporization within a loose medium and explores the influence mechanism of the mass and heat transfer coupling effect. The results show that the mass transfer effect is the main reason for the cooling of the loose medium body, and at the same time, the cooling radius of liquid nitrogen is much smaller than the inerting radius. In addition, the wind speed showed a significant negative logarithmic relationship on the cooling amplitude and inerting time of the loose medium. Finally, the development process of heat and mass transfer coupling effect in the pore space of loose medium was explored through theoretical analysis. The study provides a basis for improving the efficiency of fire prevention and extinguishing in the mining area and helps to solve the safety and environmental problems caused by spontaneous combustion of coal left in the goafs.

Mining of gently inclined coal seams is characterized by asymmetrical fracturing of key strata and complex movement and deformation. The 15,205 panel of Fuda Coal Mine was selected as the research background. A combination of theoretical analysis, field measurements, and numerical simulations was employed to investigate the characteristics of support resistance distribution under the breaking law of overlying key strata in gently inclined coal seams. The research shows that: (1) As the coal seam dip angle increases, the horizontal force within the key strata gradually intensifies, and the reduction rate of the fracture angle at the lower end of the working face exceeds that at the upper end. Consequently, the uncompressed area of the goaf migrates as a whole towards the upper end of the panel. (2) The support loads on inclined coal seams displays a “saddle-shaped” distribution. The load ratio of the non-solidified area B1 to area B increases with the dip angle of the coal seam. (3) As the compaction degree of the lower end of the goaf gradually increases, the maximum vertical displacement of the overburden, the vertical stress reduction zone, and the fracture propagation shift towards the upper end of the panel.

To enhance the permeability of low-permeability coal seams, we conducted supercritical carbon dioxide (Sc-CO2) cyclic soaking experiments. The impact of Sc-CO2 cyclic soaking time on the seepage properties and stress sensitivity of coal was comprehensively examined in conjunction with X-ray diffractometer and Fourier transform infrared spectrometer experimental analyses. The results showed that, after Sc-CO2 treatment, coal exhibited an increase in mineral content, a decrease in organic content and matrix mass, both of which leveled off with extended soaking time. Additionally, the total pore volume of coal augmented and subsequently stabilized with the progression of soaking cycles. Under Sc-CO2 cyclic soaking conditions, coal permeability was positively exponentially related to gas pressure and negatively exponentially related to effective stress. Notably, with increasing soaking time, permeability initially rose and then declined, attributed to the accumulation of residual extracts within coal seepage pores. Sc-CO2 significantly mitigated the effects of gas pressure on coal permeability, causing gas pressure sensitivity coefficient to shrink by 1–2 orders of magnitude. This coefficient exhibited a linear increase with gas pressure and a negative exponential change pattern with soaking time. Moreover, Sc-CO2 effectively intensified the affect of effective stress on coal permeability, resulting in a 2–5 times increase in effective stress sensitivity factor of treated coal. This coefficient decreased linearly with increasing effective stress but followed a pattern of initial increase followed by decrease with the progression of soaking cycles. Therefore, the permeability-enhancing effect of Sc-CO2 on coal seams can be enhanced by altering the effective stress.

Mining-induced surface subsidence often causes buried oil-gas pipelines deform, and the potential leakage risk can pose a safety hazard. In this work, a novel model for predicting the influence range of potential leakage risk from deformed pipelines was developed. First, the pipe instability deformation limit was corrected by the multi-indicator optimized screening method proposed in this paper. Then, the leakage risk influence radius of the pipe segment was defined by the failure probability. Next, the pipe segment' deformation and strength were assessed sequentially using the ratio and point methods. Combining the fuzzy logic inference method with the assessment results as input variable, and the failure probabilities as output variable , a quantitative assessment model for the pipeline leakage risk was established. Accordingly, the risk range and level of adjacent coal mines and surfaces were divided, and the verification method and forward countermeasures were proposed. Finally, an engineering case was used for analysis and verification. The results show that the gas pipeline with 650 m length was divided into seven regions and four risk levels. The influence radius of the risk levels from low to high were 12.75 m, 25.5 m, 38.25 m, and 51 m, and the influence widths on the surface were 25.28 m, 49.84 m, 76.34 m, and 101.84 m, correspondingly. The nearest distances from the risk area to the mine and village were 212.65 m and 329.08 m. The assessment of potentially threatened areas is significantly simplified by the assessment model combined with pipeline deformation, which has great practical importance for risk management and disaster prevention in adjacent space.

The oxidation of propane (C3H8) was investigated in a jet-stirred reactor under equivalence ratios (Φ) of 0.5.3.0 within 675–1025 K at 1.2 MPa. Mole fraction profiles of 14 species were identified and quantified by online gas chromatographs (GC) and gas chromatography-mass spectrometry (GC-MS). The alkenes including n-butene (C4H8-1) and 1,3-butadiene (1,3-C4H6) were newly identified compared with previous oxidation studies of C3H8. A detailed kinetic model consisting of 426 species and 1933 reactions was developed with reasonable predictions against the experiment data. In general, the peak mole fractions of light alkanes shift toward higher values with increasing Φ, while opposite trends are observed for inorganic species. The species of light alkanes increase with the increasing Φ. Rate-of-production analysis indicates that C3H8 is mainly consumed by H-abstractions with OH radicals to produce normal-propyl (nC3H7) and iso-propyl (iC3H7) radicals under all conditions. Sensitivity analysis shows that H2O2(+M)=2OH(+M) plays a promoting role in C3H8 consumption, while reaction 2HO2=H2O2+O2 plays an inhibiting role. Particular attention was paid to the effect of pressure and Φ on C3H8 consumption at 1.2.10.0 MPa and with Φ ranging from 0.1 to 3.0. It is found that the onset reaction temperature of C3H8 decreases with increasing pressure. The Rate-of-production (ROP) analysis indicates that the reactions related to pressure-dependent result in decreased onset reaction temperature and C4 species would be more formed at lower pressure. In addition to the present experiment data, the model can reasonably predict the ignition delay times and laminar burning velocities reported in the literature.

Since ultra-deep hole loosening blasting uses significantly larger hole diameters and charges than shallow hole blasting, determining the optimal stemming length is crucial. This study investigates the optimal stemming length for ultra-deep hole loosening blasting. Numerical simulations analyze the effectiveness of different blasting methods, showing that single-point forward blasting ensures rock mass loosening while minimizing damage in the plugging section. Based on this, a theoretical calculation method is developed for ultra-deep holes, indicating an optimal stemming length of 2.9–4.35 m for a 0.08 m diameter hole. The minimum stemming length is 3.04 m when using the limit value of stemming strength. Numerical simulations verify these findings, confirming that a 0.08 m diameter hole requires at least 3 m of stemming. Field tests at a coal mine driving face validate the theoretical and the simulation results, proving their reliability. This research guides selecting appropriate stemming lengths, improving blasting efficiency, and ensuring construction safety.

As shallow coal resources deplete, coal mines are rapidly shifting to deep mining, and coal‒rock‒gas composite dynamic disasters are inevitable. However, the triggering mechanism, monitoring, early warning, and prevention technologies for these disasters need exploration and improvement. This paper reviews the latest research on these aspects of coal‒rock‒gas composite dynamic disasters. Three major triggering modes are proposed: rock burst induction, coal and gas outburst induction, and multifactor coupling induction. Based on the concept of structural control disaster prevention, disasters are categorized into three types: geological structure induced, coal–rock structure induced, and gas reservoir structure induced. Then, the triggering mechanism of each type is described in detail. In terms of monitoring and early warning, a systematic summary of international advanced techniques is discussed. An energy evaluation standard that integrates macro and micro aspects is presented, and an energy identification standard that is based on thermodynamic principles is proposed for the first time. A comprehensive monitoring and early warning model and system is established, which features full spatiotemporal, multiscale, and multiparameter coupling. In terms of prevention and control, existing approaches are carefully considered. A multifunctional hierarchical continuous control framework for boreholes is proposed for the first time. This framework integrates drilling, pressure relief, extraction, cavitation for energy absorption, and grouting functions, which can achieve structural adjustment, stress release, gas energy dissipation, and optimal control. Finally, it predicts the advanced development trends and research directions of international composite disasters and proposes five key scientific problems for further investigation.

Utilizing real-time acoustic emission monitoring data to predict the creep failure of salt rock has emerged as a crucial method for ensuring the smooth operation of salt cavern storage facilities. This article integrated real-time acoustic emission monitoring data from the creep process of salt rock to analyze the dynamic evolution of internal structural damage. It was discovered that the relationship between damage rate $\dot{D}_{t}$ and cumulative strain closely resembles the Weibull distribution function. By incorporating the Weibull probability distribution function and Drucker–Prager strength criterion, a damage evolution model that considers elastic stress threshold and cumulative damage effect was established. Based on the damage evolution characteristics observed during the creep process of salt rock, the linear solution values of the damage evolution model were revised and validated. The cumulative damage D from the salt rock creep-acoustic emission test was integrated into deformation modulus $E_{D}$ and viscosity coefficient $\eta_{D}$ of the Maxwell creep model, thereby creating a new Maxwell creep model that considers compression-creep coupling and mutual feedback damage. This model was then extended to three-dimensional stress conditions. The research findings reveal that the new creep model adeptly describes the entire creep process of salt rock. The derivative order $\beta$ of the model reflects the geometric structure state and creep strain participation rate $\zeta$ of salt rock during the creep process. The sudden increase in strain during the accelerated creep stage of salt rock is attributed to the compressive strain resulting from rapid structural degradation.

The traditional Mohr–Coulomb and Hoek–Brown strength criteria exhibit limitations in characterizing the strength behavior of layered sandstone under dynamic loading. Specifically, these criteria fail to adequately account for the coupled effects of confining pressure, bedding angle, and impact pressure on the dynamic evolution of sandstone strength parameters, including the internal friction angle (φ), cohesion (c), and Hoek–Brown parameter (m). To address this issue, this study systematically integrates experimental investigations and theoretical modeling to establish a dynamic strength criterion that incorporates multifactorial coupling effects. Using a modified split Hopkinson pressure bar (SHPB) system, uniaxial dynamic impact tests and three-dimensional dynamic-static combined loading tests were conducted on sandstone specimens with varying bedding angles (0°, 30°, 45°, 60°, 90°), confining pressures (0, 5, 10, 20 MPa), and impact pressures (0.8, 1.2, 1.6 MPa). Key experimental findings include: (1): As the impact pressure increased from 0.8 to 1.6 MPa, the cohesion (c) rose from 65.43 MPa to 80.99 MPa, the internal friction angle (φ) increased from 28.63° to 36.39°, and the Hoek–Brown parameter (m) surged from 5.81 to 12.23. (2): When the bedding angle increased from 0° to 90°, the cohesion (c) nonlinearly decreased from 65.43 MPa to 64.24 MPa, the internal friction angle (φ) declined from 28.63° to 26.01°, and the Hoek–Brown parameter (m) decreased from 5.81 to 5.68. Building on these results, enhanced strength criteria were proposed to explicitly integrate the coupling effects of confining pressure, bedding angle, and impact pressure. Theoretical strength values calculated using the improved criteria were compared with experimental measurements. Validation demonstrated that the modified Mohr–Coulomb criterion achieved an accuracy of 15%, while the refined Hoek–Brown criterion attained an accuracy of 10%. These findings conclusively demonstrate that the proposed criteria effectively describe the dynamic strength characteristics of sandstone under the combined influence of confining pressure, bedding angle, and impact pressure, providing a robust framework for stability analysis in deep rock engineering applications.

The coal-forming environment in deep coal seams are the basis for studying enrichment of deep coalbed methane. The classification and predictive evaluation of coal facies types have become the topic of current research. In this paper, coal facies of coal seam 8 are divided by using submicroscopic component test. The nano-pores volume distribution under different coal facies are studied, and adsorption performance difference among different coal facies are studied. Meanwhile, principal components analysis is used to predict coal facies. The conclusions are as follows. (1) Coal facies includes water-covered herbaceous swamp facies, moist herbaceous swamp facies, and moist forest swamp facies. Effected by vegetation type, ash content of moist forest swamp phase is the highest, resulting in smaller micro-pore volume and stronger pore distribution heterogeneity, methane adsorption capacity of this coal facies is weaker than other two types of coal facies. (2) Natural gamma, acoustic time difference, and the compensated neutron log could be used to achieve accurate characterization of coal facies by using principal component analysis. In the same coal seam, coal facies at the bottom of coal seam 8 are moist forest facies while those in the middle and upper parts are moist and covered with water herbaceous swamp facies. (3) The distributary bay subfacies affect planar distribution of water-covered herbaceous swamp facies. Under this type of coal facies, macroscopic coal lithotypes are semi-bright and bright coal, which is prone to form thick coal seams (with a thickness greater than 8 m) and underdeveloped dirt bands inclusions within the coal seams. Water-covered herbaceous swamp facies should be regarded as a favorable coal facies.

During the excavation of a deep‐buried tunnel by the drilling and blasting method, the dynamic stress of blasting may cause the disorderly release of high energy in the rock mass during the blasting process of deep high‐energy rock. Blasting vibration is one of the main factors inducing dynamic disasters (such as rockbursts) in the surrounding rock. An impact‐induced rockburst occurred in the Gaoloushan deep‐buried tunnel. In this paper, the simulation experiment of this type of rockburst was carried out by using the impact rockburst experimental system. The two rockbursts that occurred during the experiment formed “V” type pits, which were consistent with the on‐site rockburst situation; therefore, it proved the rationality of this experiment. The results showed that the total displacement characteristics of impact‐induced rockbursts had obvious suddenness, and the intensity of impact‐induced rockbursts showed characteristics from weak to strong. In addition, it was also found that the rupture parameters of the rock mass in rockbursts showed a compound exponential growth relationship with time. As a typical mode of instantaneous rockburst failure, the mechanism of impact‐induced rockburst could be regarded as the result of the combined action of shear crack and tension‐shear crack, which played a dominant role, reflecting the characteristics of sudden fracture development. The generation of impact‐induced rockbursts occurred when the peak value of static load and disturbance stress wave reached a certain value. On this basis, the rockburst criterion was proposed.

Few-shot learning techniques have enabled the rapid adaptation of a general AI model to various tasks using limited data. In this study, we focus on class-agnostic low-shot object counting, a challenging problem that aims to achieve accurate object counting with only a few annotated samples (few-shot) or even in the absence of any annotated data (zero-shot). In existing methods, the primary focus is often on enhancing performance, while relatively little attention is given to inference time—an equally critical factor in many practical applications. We propose a model that achieves real-time inference without compromising performance. Specifically, we design a multi-scale hybrid encoder to enhance feature representation and optimize computational efficiency. This encoder applies self-attention exclusively to high-level features and cross-scale fusion modules to integrate adjacent features, reducing training costs. Additionally, we introduce a learnable shape embedding and an iterative exemplar feature learning module, that progressively enriches exemplar features with class-level characteristics by learning from similar objects within the image, which are essential for improving subsequent matching performance. Extensive experiments on the FSC147, Val-COCO, Test-COCO, CARPK, and ShanghaiTech datasets demonstrate our model’s effectiveness and generalizability compared to state-of-the-art methods.

Accurately calculating the stress state and its distribution is key to preventing coal burst. Taking a typical mine with extremely thick coal seams and coal bursts as an example, methods such as stress estimation, numerical computation, theoretical analysis, and on-site measurements were used to study the estimation method for coal burst force sources and the quantitative evaluation of coal burst risk under extremely thick coal seams beneath massive gravel rock. The main research content includes: (1) Establishing a coal burst force source estimation model for extremely thick coal seams through the estimation of transmitted stress from massive gravel rock, self-weight stress of the overlying strata, tectonic stress quantitative analysis, and mining disturbance stress estimation; (2) Proposing a calculation method for the fracture angle and strike span parameters required for stress estimation based on microseismic monitoring technology, and comparing and verifying the effectiveness of rapid estimation methods for strike and dip support pressures; (3) Based on the above methods, proposing a quantitative evaluation method for coal burst risk based on stress estimation. The practical results demonstrate that the proposed method enables rapid analysis of impact force sources, accurate assessment of coal burst risk levels, and establishes a foundation for timely and precise early warning of coal burst disasters.

With the wide application of large machinery in coal mining, the influence of mine pressure is large and wide. Therefore, it is very important to retain and maintain the strength of coal pillars in the working face section. But the traditional narrow coal pillar grouting technology often causes grouting failure due to slurry leakage. In order to avoid this situation, the pre-grouting solidification technology is put forward. Through theoretical analysis and speculation, numerical simulation, field test and monitoring and other methods, this article discusses the shortcomings of traditional grouting methods, the causes of grouting failure, and the reasons for grouting failure, the characteristics of fracture distribution in narrow coal pillar, the concrete implementation method of pre-grouting solidification technology and the reasonable selection of grouting time. The results show that the high fracture development within the narrow coal pillar has good grouting permeability, and the coal pillar is pre-grouting reinforced before the excavation of the roadway along the goaf, combined with the flexible thin-layer shotcrete layer and reasonable grouting time, the solidification of narrow coal pillar has achieved good results, and has constructed a good surrounding rock environment for excavation and support of roadway.

As intelligent coal mining continues to advance, the requirements for accurate geological formation detection are increasing, leading to a growing demand for the efficient storage and retrieval of geophysical big data. In this study, we propose a multi-scale spatiotemporal classification encoding (MSTC) method to address the current challenges associated with data fragmentation, heterogeneity, and multi-scale spatiotemporal complexity. MSTC unifies spatial, temporal, and classification attributes into a compact indexing framework, enhancing data storage and query efficiency. Specifically, MSTC includes spatial encoding based on the Hilbert space-filling curve, flexible temporal encoding with multi-scale temporal segmentation, and optimized taxonomic encoding of operational data through a hierarchical classification structure. In experiments, MSTC significantly outperformed the traditional approach in a variety of database systems and demonstrated strong advantages in index construction time, storage overhead, and query efficiency. Additionally, MSTC was successfully applied to a coal mine geohazard transparency platform that provides strong technical support for intelligent coal mining and geohazard monitoring. This study lays a solid foundation for efficient management and transparent decision-making with respect to geophysical big data.