Approximately 2 million hectares of coal mining subsidence areas have formed in China, of which about one-third are permanently or seasonally waterlogged. Subsided cropland not only loses its grain production function but also gives rise to a series of ecological, environmental, and social problems, especially in mining areas with a high groundwater table. Using laboratory model simulations, in-situ experiments under different scenarios, space-air-ground-network integrated monitoring, and engineering applications, this study innovatively integrates green governance and utilization pathways and technical models for high-groundwater-table coal mining subsidence areas under the coordinated goals of energy and food security. The main innovations are as follows. The nitrogen and phosphorus cycling mechanisms under rice cultivation on subsided water surfaces were systematically revealed. The fluxes of nitrogen and phosphorus absorbed by rice from the water body were 77.5% and 62.7% higher, respectively, than the fluxes released from the substrate into the water body, thereby clarifying the internal mechanism of “rice-based water purification”. A complete set of key technologies and models for rice-fish co-culture and fishery-photovoltaic complementary utilization in waterlogged coal mining subsidence areas was established for the first time. A specialized substrate for floating cultivation on subsided water surfaces was developed to balance sustained nutrient supply and environmental control. An adaptive lifting device for floating planting plates based on a fixed-pulley and counterweight system was also developed, enabling free vertical adjustment under a maximum water-level fluctuation of 1.0 m. In addition, fully automated equipment integrating substrate cup filling and transplanting, as well as bank-side harvesting equipment, was invented. Floating photovoltaic layout schemes and optimized anchoring technologies were proposed. A governance pathway characterized by “dynamic restoration, integration of three types of planning, and three-category governance” was established. An ecological restoration and multifunctional utilization model was developed for grain-coal overlapping mining areas with a high groundwater table and was applied and demonstrated over an area exceeding 2.0 × 107 m2. An intelligent assessment and dual-terminal collaborative management and control platform for the soil-water environment in mining areas was established, forming a key technical chain of “soil-water environmental damage diagnosis, cropland productivity assessment, and multi-objective optimal regulation” under coal mining disturbance restoration scenarios. These findings fill the technical gap in the green governance and utilization of high-groundwater-table coal mining subsidence areas, and provide theoretical support and technical guidance for ecological restoration, cropland protection, and high-quality sustainable utilization of coal mining subsidence land in grain-coal overlapping regions.
Zhaogu No. 2 Coal Mine is in the eastern area of Jiaozuo Coalfield, at the southern foot of the Taihang Mountain. The primary mineable coal seam of the mine is buried at a depth of more than 700 m, with an average thickness of 6 m and a hardness coefficient of 2−3. Influenced by orogenic movement, the thickness of the overlying bedrock is only 0−120 m, above which lies an alluvial formation with a thickness of more than 600 m, coupled with well-developed fault structures in the strata, all of which bring severe challenges to roof control in thick coal seam mining. To provide scientific guidance for the safe mining of deep-buried thick coal seams with thin bedrock, the mining practice of Zhaogu No. 2 Coal Mine is taken as the engineering background, and the research progress of thick coal seam mining and surrounding rock control technology under deep-buried weakly cemented overlying strata is systematically summarized. Zhaogu No. 2 Coal Mine has formed a mining layout progressing from east to west (from shallow to deep). In the slicing mining stage, the upper slice mining had a high concentration degree of advanced mining-induced stress, but the mining thickness was small, so the failure degree of surrounding rock was low. In contrast, the lower slice mining had a low concentration degree of advanced mining-induced stress, but the fractured roof affected by upper slice mining had a large subsidence, resulting in roof leakage and caving problems. In addition, slicing mining required a large width of coal pillars, leading to a high roadway drivage rate. To solve the problem of tight mining and drivage succession in the mine, the large mining height mining technology for deep-buried thick coal seams with thin bedrock was developed, and the three-stage movement characteristics of the full overburden were identified, including the progressive fracture stage of bedrock, the development stage of caving arch in thick alluvial formation, and the development stage of surface fissures. A composite load-bearing structure model of overburden caving arch and towering roof beam at the arch foot was established, the formation mechanism of full-thickness fracture of thin bedrock and dynamic load impact effect of roof was revealed, and a multi-element synergistic surrounding rock control technology for the working face was developed, integrating “high-strength and high-stiffness support, pre-split blasting of hard roof, and advanced grouting of coal wall”. To resolve the contradiction between thick coal seam mining and coal wall reinforcement, innovative practice of top-coal caving mining for deep-buried thick coal seams with thin bedrock was carried out. The roof pressure and the failure degree of coal wall were significantly reduced, but problems such as hanging of hard top-coal and caving of large coal blocks still existed, with the measured top-coal recovery rate of only 65%. To improve the cavability of top-coal, the ZFG17600/29.5/50D top-coal caving hydraulic support was developed. By increasing the cutting height (with a mining-to-caving ratio of 2∶1), widening the roof control area, and optimizing the caving mechanism, the fragmentation process of top-coal was effectively promoted.
To address the surrounding rock large deformation and support instability of deep large-height mining gob-side entry driving under high in-situ stress, strong mining-induced disturbance, complex roof strata and water inflow, the 20103 return airway in Dahaize Coal Mine was taken as the engineering background. Field investigation, mechanical testing of support components, FLAC3D numerical simulation and industrial tests were adopted to investigate coal pillar width optimization, asymmetric damage evolution, the thick-layer transboundary anchoring mechanism and the double-layer flexible thick anchoring control technology. The results show that the average burial depth of the 20103 return airway is 596.81 m, the maximum vertical in-situ stress reaches 16 MPa, and the roadway section is 6 240 mm × 4 550 mm. Under the superimposed influence of lateral abutment pressure from the adjacent goaf and advanced abutment pressure from the working face, the shallow roof damage is mainly concentrated within 0-4 m, while a deep damage zone still exists within 6-10 m, resulting in obvious asymmetric deformation. Orthogonal tests and the comprehensive evaluation of stress, displacement and plastic zone indicate that coal pillar width is the primary factor controlling surrounding rock stability, and the reasonable coal pillar width is 6 m. Different from conventional long cable support or simply strengthened bolt-cable support, thick-layer transboundary anchoring is based on surrounding rock damage zoning. Flexible high-strength members are used to cross the shallow fractured zone and plastic expansion zone and anchor into relatively stable deep strata, thereby forming a continuous bearing structure composed of a primary thick bearing layer and a secondary reinforcement layer. The optimized support scheme consists of 4.5 m flexible bolts and 8.3 m large-diameter cables in the roof, and 2.6 m threaded steel bolts combined with 4.5 and 3.8 m flexible bolts in the ribs, with the primary support spacing of 0.9 m. Field monitoring shows that the average roof subsidence, coal-pillar rib displacement and solid-coal rib displacement are 99.92 mm, 112.50 and 87.40 mm, respectively, and the deformation process can be divided into severe deformation, stabilization and stable stages without continuous late-stage increase. The proposed support system can effectively control the asymmetric large deformation of deep large-section gob-side entry driving.
Surface energy is a key factor governing the storage states of gaseous and liquid fluids in shale reservoirs. To investigate the effects of supercritical CO2-water-rock interactions on shale surface energy under reservoir temperature and pressure conditions, this study takes shale collected from the Niutitang Formation in northern Guizhou as the research subject. Utilizing the contact angle measurement method and the van Oss-Chaudhury-Good (vOCG) theory, combined with analytical techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy and energy-dispersive spectroscopy (SEM/EDS), the evolutionary patterns and influencing mechanisms of shale surface energy under supercritical CO2-water-rock interaction were systematically studied. The results indicate that the contact angles between shale and the non-polar test liquid (diiodomethane) are significantly smaller than those with polar test liquids (glycerol and distilled water), demonstrating that the tested shale samples possess strong non-polar characteristics. After supercritical CO2-water-rock interaction, the shale surface energy showed a significant increasing trend, with the polar component increasing more markedly than the non-polar component. The change in the non-polar component of the shale surface energy mainly stems from the increased percentage of non-polar minerals such as albite and quartz in the shale, while the change in the polar component is controlled by alterations in the surface electron-donating capacity resulting from changes in functional groups. The increase in shale surface energy after supercritical CO2-water-rock interaction enhances its adsorption capacity for CO2, CH4, and H2O molecules, which would lead to CO2 and CH4 being more likely to exist in adsorbed states within the shale reservoir, and the water-blocking effect caused by residual water molecules in the micro-nano pores of shale would also be intensified. This is beneficial for the long-term stable sequestration of CO2, but may adversely affect shale gas recovery. The research findings provide support for the efficient extraction of shale gas and CO2 geological storage in Guizhou.
A comprehensive research approach integrating field measurements, theoretical analysis, numerical simulation, and engineering practice is adopted to address roadway roof instability and water inrush during excavation under a confined aquifer. The instability mechanisms of roadway roofs with a thin aquifuge and the key prevention and control technologies are systematically investigated. The results indicate that water inrush disasters in roadway roofs require the simultaneous presence of three fundamental conditions: a water source in the aquifer, stable water supply conditions, and through-going fractures formed by the coupling of engineering disturbances and hydro-mechanical effects.Based on an elastic–plastic roof beam model, a theoretical formula for calculating the height of the plastic zone in the roof is derived. This reveals that the plastic zone height expands with increasing roadway burial depth and cross-sectional width, and highlights the significant influence of the internal friction angle of the surrounding rock on plastic zone development. A mechanical model of the surrounding rock, considering different aquifuge thicknesses, is established through numerical simulation, and the effects of aquifuge thickness on stress distribution, displacement response, and plastic zone extension are systematically analyzed. Simulation results show a critical threshold (5.0 m) for aquifuge thickness. When the aquifuge thickness falls below this threshold, roof displacement exhibits a nonlinear, sharp increasing trend, the plastic zone in the surrounding rock rapidly expands and eventually penetrates the aquifuge, forming a water-conducting channel connected to the upper aquifer, thereby significantly increasing the risk of water inrush.Based on the mechanistic findings, a comprehensive control strategy centered on “drainage and pressure reduction” and “dynamic reinforcement support” is proposed. Specific measures include: constructing upward-inclined drainage holes in the roadway sides to actively relieve roof water pressure and reduce the softening and splitting effects of water on sandy mudstone; and concurrently implementing a synergistic support system of “zonal support – layered grouting – frame support” to dynamically reinforce the roof bearing structure. Grouting reinforcement is primarily applied to the shallow fractured rock mass to enhance the integrity and cohesion of the surrounding rock. The support system flexibly selects structures such as anchor cables, steel straps, and I-beam frames based on the relationship between the plastic zone and aquifuge thickness, achieving the control objective of “combining blockage and drainage, integrating consolidation and support”. Field applications demonstrate that this comprehensive control strategy effectively manages surrounding rock deformation and roof water inrush, ensuring safety and stability during roadway excavation. This study not only reveals the intrinsic mechanisms of roof instability and water inrush under thin aquifuge conditions, but also provides theoretical foundations and practical references for water hazard prevention and roof stability control in roadway engineering under similar hydrogeological conditions.
Flocculation and sedimentation of coal slurry are critical solid–liquid separation processes in coal preparation, and the floc structure and rheological properties of the slurry affect subsequent dewatering performance. Fine coal slurry is treated with cationic polyacrylamide (CPAM), anionic polyacrylamide (APAM), and the synthesized flocculant GgB14 to investigate the effects of flocculant dosage on settling, dewatering, and rheological properties.The results show that CPAM promotes rapid settling and forms large, compact flocs with significantly higher yield stress and consistency index. The elasticity and structural strength of the slurry are enhanced with increasing dosage, whereas the filter cake moisture content remains as high as 30.08%. In contrast, APAM and GgB14 produce relatively loose flocs with lower yield stress and loss factor, resulting in filter cake moisture contents of approximately 18% and superior dewatering performance. Regression analysis indicates that the consistency index (K) is strongly correlated with filter cake moisture content (R2 = 0.89), suggesting that it can serve as an indirect indicator of dewatering performance. These findings clarify the relationship among floc structure, rheological properties, and dewatering performance of coal slurry and provide a theoretical basis for flocculant selection and dewatering process optimization.
To enhance the automation level of electric shovels and promote the transition of open-pit mining from “manned shovel + unmanned haul truck” to “unmanned shovel + unmanned haul truck,” this paper proposes an embodied-perception–driven autonomous excavation method for electric-shovel robots based on a digital twin system. A Transformer model is developed using spatiotemporal consistency and deformable attention mechanisms to recognize surrounding targets from multi-view images and perform 3D environmental reconstruction, while LiDAR point clouds are integrated to compensate for image depth and improve reconstruction accuracy. A parallel hybrid neural network is then constructed to model the relationships among hoist-motor current, crowd-motor current, and excavation resistance, enabling real-time resistance perception during excavation. A digital twin system integrating modeling, embodied perception, autonomous excavation, and continual learning is established, within which a deep reinforcement learning (DQN)-based excavation policy is trained through virtual excavation simulations. To ensure generalization and transferability, a goal-driven DQN model is introduced. Furthermore, to address efficiency degradation when deploying the virtually trained DQN model to real machines, a force-sensing control strategy is proposed. This strategy continuously optimizes control commands based on real-time excavation resistance, thereby improving excavation efficiency. Experiments show that the 3D reconstruction error in object position and orientation is 5.3% and 1.1%, respectively, while the root-mean-square error in predicting tangential and normal excavation forces is 1.9% and 1.2%. In the digital twin environment, the DQN-based autonomous excavation reduces energy consumption by approximately 10% compared with constant-speed excavation, and the trained DQN model can be successfully transferred to a physical electric-shovel prototype to achieve the target bucket-fill rate. The proposed force-sensing control strategy further improves excavation performance by about 5% on top of the DQN model. These results demonstrate that the embodied-perception electric-shovel robot can effectively sense its surroundings, learn through virtual interaction within the digital twin system, achieve autonomous excavation, and continually improve its excavation performance in real scenarios.
Addressing the support challenges of roadways with high-stress broken roofs during mining in the lower slice of thick coal seams. Taking the upper entry of the 14022 working face in Zhaogu No. 2 Mine as the engineering background, a roof mechanical model for the failure characteristics of broken surrounding rock under high-stress conditions was established. The stress distribution characteristics of the floor in an elastic state were obtained, and the rotational characteristics of floor stress distribution were clarified. The plastic zone equation of surrounding rock under a three-dimensional stress environment was derived, and the plastic distribution characteristics of roadway surrounding rock were obtained. The research results show that: under the disturbance of mining in the upper coal seam, the stress distribution of the surrounding rock exhibits significant directional deflection, with the principal stress direction changing markedly. This principal stress deflection leads to an obvious asymmetric distribution of the plastic zone in the surrounding rock, with the plastic zone concentrated in the roof and left rib of the roadway, inducing asymmetric failure of the surrounding rock. The combined effect of principal stress deflection and the fragmentation of the overlying strata is the fundamental cause of severe asymmetric failure of the roadway surrounding rock. Furthermore, due to mining disturbances, the floor of the overlying strata becomes broken, further exacerbating the failure degree of the roadway roof, resulting in anchor cable anchorage failure and a significant decrease in the support effect of steel sheds. Based on this, a new type of two-component grouting material was developed, and a combined support scheme of “grouting reinforcement + asymmetric anchor cables” was proposed. Field application shows that the deformation of the roadway roof and floor decreased by 36%, and the deformation of the two ribs decreased by 51%, significantly restraining surrounding rock deformation and improving roof stability, providing a reliable technical reference for roadway support under similar conditions.
To address the challenges of intelligent analysis and precise decision-making in the process of intelligent mining in coal mining faces, By leveraging the Hadoop big data platform, integrates analysis and decision-making technologies, machine learning methods, and distributed storage architectures, and designs and implements a set of intelligent mining face planning systems for coal mines that integrate data collection, storage, processing, and analysis.This system achieves full lifecycle management of data such as mine pressure, gas, and equipment status through a multi-layer data architecture.Specifically, the data collection layer uses underground sensor networks, Sqoop, Flume, and Kafka components to achieve real-time collection and transmission of multi-source heterogeneous data; the data storage and processing layer uses distributed technologies such as HDFS and HBase to achieve classified storage and efficient processing of structured, semi-structured, and unstructured data, and uses MapReduce and Spark frameworks to complete data cleaning and aggregation; the decision planning layer combines principal component analysis to reduce the dimensionality of high-dimensional data, selects key indicators such as mine pressure, gas, and equipment status, and based on the K-Means clustering algorithm divides the data into clusters with different characteristics, further processes the clustering results through the CART decision tree model to precisely identify the key factors affecting the safety of the mining face, processes continuous and discrete monitoring data, and realizes real-time monitoring and early warning of the safety status of the intelligent mining face.During the experiment, the accuracy of the model test set reached 92.3% and the F1 score was 0.91, demonstrating high reliability and practicality.Finally, the system builds a closed-loop intelligent planning system covering perception, analysis, and decision-making through multi-source information fusion and dynamic iterative optimization mechanisms, providing reliable technical support for the safe and efficient production of coal mines.
In the Central Plains mine–agriculture composite region, extensive overlap of coal resources and high-quality farmland has led to mining-induced farmland fissures, subsidence waterlogging, slope changes, and soil degradation, hindering coordinated coal extraction and farmland protection. To support green mining with reduced land damage, this review summarizes the characteristics and control technologies of mining-induced farmland damage. Three typical geological and mining conditions are considered: thick coal seams with “three-soft” strata, thin bedrock overlain by extremely thick unconsolidated layers, and multiple-seam occurrence. Overburden failure, surface movement and deformation, and farmland damage features (tensile fissures, subsidence basins, slope changes, soil degradation) are analyzed. On this basis, the research status and applications of relevant technologies are reviewed from three aspects: surface restoration, overburden control, and underground subsidence reduction, while the farmland damage evaluation system is summarized in terms of evaluation indicators and methods. Future research directions are also discussed. The results indicate that farmland damage is strongly controlled by geological and mining conditions. Soil degradation typically progresses from physical structural damage and reduced biological activity to chemical property changes. Farmland damage control has evolved from sole post-mining restoration to multi-level damage reduction integrating surface restoration, overburden control, and underground subsidence reduction. Concurrent mining and reclamation and overburden separation grouting have been applied for farmland restoration and subsidence mitigation. Damage degrees are currently classified mainly using surface deformation and hydrological indicators to guide graded management. Overburden failure and surface damage differ significantly under different conditions, while the adaptability and effectiveness evaluation of damage-reduction mining technologies remains insufficient, limiting effective control of farmland damage. Further research should target technology matching, refined design of grouting parameters for overburden separation, seepage prevention, green solid-waste-based grouting materials, and dynamic regional farmland damage assessment, to improve the theoretical basis for farmland protection and green damage-reduction mining in mine-agriculture composite regions.
To address the high risk of rock burst and the limited pressure relief effect of large-diameter boreholes in front of the roadway during tunneling toward the goaf, which are caused by the superposition of the advanced abutment pressure of the roadway and the lateral abutment pressure of the goaf, this study takes the excavation of 72303 transportation roadway toward 72301 goaf in Tianchen Coal Mine as the engineering background. By combining theoretical analysis, numerical simulation, and field monitoring, the mechanism of rock burst induced by abutment pressure superposition is systematically investigated, and a collaborative pressure-relief and rock-burst-mitigation approach integrating “head-on pressure-relief boreholes and roof loosening blasting” is proposed. The results show that as the roadway approaches the goaf, a “peak-peak superposition” of the advanced abutment pressure and the lateral abutment pressure occurs, forming a high-stress concentration zone that accumulates substantial elastic energy and significantly increases the risk of rock burst. Theoretical calculations and simulations indicate that the influence range of the lateral abutment pressure is about 172 m, with its peak located approximately 95 m outside the goaf. After entering the zone within 50 m from the goaf, the stress concentration coefficient rises sharply. Roof loosening blasting enhances the overall pressure-relief effect by generating strong disturbances that promote the collapse of adjacent coal-seam pressure-relief boreholes, thereby optimizing the pressure-relief boundary. Field application demonstrates that after implementing the synergistic measures, microseismic energy and frequency decrease significantly, dynamic phenomena are markedly reduced, and safe roadway excavation is achieved. The research outcomes provide a theoretical basis and engineering reference for rock burst prevention and control in roadways excavated toward goafs under deep and complex stress conditions.
Coal-rock cutting event localization is performed to determine the start and end times of cutting events that are both audible and visible and to identify their categories using video sensors. The development of video sensors capable of localizing coal-rock cutting events is crucial for safe and efficient coal mining. However, the accuracy of audio-visual event localization is affected by the interference from coal dust and audio noise. Furthermore, the real-time localization performance of video sensors is significantly affected by the high latency caused by multimodal audio-visual data processing. To solve these problems, a Swin-LAVFA method based on a lightweight audio-visual fusion adapter (LAVFA) is proposed. LAVFA is adapted to the pretrained Shifted Window Transformer (Swin-T) model to enable the real-time and efficient localization of coal-rock cutting events. Specifically, a modality-specific compression module is introduced.Using an asymmetric cross-attention mechanism, the high-dimensional input visual and audio features are compressed into visual and audio features that representing coal-rock cutting event cues, respectively, under the guidance of low-dimensional latent tokens.Then,using a cross-modal cross-attention module, the visual (or audio) features containing event cues are fused with the corresponding-modality features, thereby obtaining enhanced visual and audio features. Finally, the enhanced audio-visual features are adapted to each frozen layer of the Swin-T model through a lightweight adaptation module. During this process, the asymmetric attention mechanism is used to iteratively extract the input data into a compressed latent bottleneck, thereby reducing the computational complexity of the model while perserving its performance. The quadratic complexity of the self-attention computation in the Swin-T model is also eliminated, and the inference speed of the model is consequently improved. The results show that excellent coal-rock cutting event localization performance is achieved by the proposed method on the self-built mine shearer cutting states (MSCS) dataset, with the accuracy of 80.3%, the influence speed of 33.5 fps, and 4.6×106 trainable parameters, thereby assisting video sensors to accurately localize coal-rock cutting events in real time.
Coal and gas outburst is one of the most severe coal-rock dynamic disasters in deep coal mining. The extreme geological conditions of “three highs, one low and one complexity” (high gas content, high ground stress, high structural destruction, low permeability, and complex geological structures) in Guizhou Province, formed by typical karst landforms, have made the outburst disaster mechanisms increasingly concealed and complex. Conventional contact-based static single-indicator prediction methods are no longer adequate for meeting the demands of continuous, dynamic and advanced early warning in deep mining operations. To overcome the technical bottleneck of precise early warning under complex geological conditions, this study, taking typical high-outburst coal mines in Guizhou as the engineering background and leveraging microseismic dynamic responses and artificial intelligence fusion technologies, proposes a comprehensive microseismic dynamic early warning technical system for coal seam outbursts, encompassing “fine data processing, geological anomaly identification, risk grading evaluation, and intelligent multi-source early warning.” At the signal processing level, a high-fidelity extraction and intelligent waveform recognition method for low signal-to-noise ratio microseismic signals is proposed, based on a cascaded architecture of frequency-domain fast singular value decomposition (FSVD) and hidden Markov model (HMM), achieving automated classification and elimination of operational interference signals (drilling, blasting, coal mining, etc.) from genuine coal-rock microseismic waveforms, with P-wave arrival picking errors reduced by over 70%. At the knowledge support level, a large language model (LLM) combined with a BiLSTM-CRF deep network is innovatively introduced to construct a gas outburst precursor knowledge graph encompassing four core dimensions (geological structures, gas parameters, microseismic responses, and manual observation phenomena), enabling high-precision extraction and structural transformation of outburst precursor entities from unstructured text. At the fusion decision-making level, a multi-source information deep fusion early warning algorithm based on the transferable belief model (TBM) is established, which quantitatively synthesizes microseismic dynamic physical indicators, gas monitoring time-series data, and knowledge graph prior knowledge through belief-level fusion and decision-level transformation mechanisms, effectively addressing the challenges of multi-source evidence conflicts and incomplete information conditions in reasoning and decision-making. A six-month field industrial trial was conducted at the No. 9 coal seam of Linhua Coal Mine in the northern Guizhou mining area. The results demonstrate that the FSVD denoising algorithm improves the signal-to-noise ratio of microseismic signals from below 5 dB to above 10 dB. The TBM-based multi-source fusion early warning model achieves an overall accuracy of 92% (23 out of 25), with 23 effective warnings issued and a zero missed alarm rate. In the scenario of crossing a concealed fault zone, the system achieved precise early warning 2.5 days in advance, successfully interrupting the disaster incubation chain. The proposed intelligent early warning method demonstrates significant advantages in early warning accuracy, advance response capability, and engineering practicality, providing reliable technical support and an engineering paradigm for continuous, dynamic and advanced prevention and control of coal and gas outburst disasters under deep complex geological conditions.
Zhaoxian mining area is an important mining area in the Huanglong coal base. During the mining of high-strength coal resources, the problem of coal seam roof water disaster is prominent, and water inflow prediction is a crucial part of water disaster prevention and control in the mining area. Coal seam mining disrupts the original stress equilibrium state of the overlying strata and is a key factor inducing changes in aquifer permeability. To explore the evolution characteristics of aquifer permeability and the dynamic prediction of water inflow under mining conditions, multiple-group pumping tests conducted in the mining area are used as the basis, and research methods such as numerical simulation and mathematical statistics are comprehensively applied to analyze the variation characteristics of the aquifer permeability coefficient and groundwater flow field at different stages of coal mining. A numerical model of the study area is established to dynamically predict water inflow. The results indicate that during coal seam mining, the permeability coefficient of the aquifer first increases and then decreases. After mining activities cease, the increase in the permeability coefficient continues for a period of time, the variation range of the aquifer permeability coefficient during the mining process is 4.3 to 22.0 times. Changes in aquifer permeability affect the distribution of the groundwater flow field, and groundwater levels are more uniform in areas with higher permeability. In aquifers affected by mining activities, groundwater activity increases, and the groundwater level recovers more rapidly. By combining the variation characteristics of aquifer permeability during the mining process and adopting a segmented simulation method for water inflow, the water inflow of the pre-mining working face is predicted. The research results can provide a reference for understanding the evolution characteristics of aquifer permeability during mine exploitation and provide a basis for mine water disaster prevention and control and safe production.
In the shallow coal seam area at the border of Inner Mongolia and Shaanxi, most of the upper coal groups have been mined out after long-term large-scale mining, and the lower coal groups are currently being mined. Following repeated mining disturbances, the mine water inflow in the study area exhibits characteristics of water quality changes and increased water volume. Investigating the causes of the impacts of repeated disturbance conditions on the hydrochemical characteristics and water volume changes of roof mine water in the working faces of the lower coal group is a prerequisite for conducting water prevention and control work and water resource protection. A total of 56 water samples were collected, including surface water, Quaternary loose layer groundwater, bedrock groundwater, goaf water, and mine water. Based on the complete water quality analysis results, mathematical statistics, hydrochemical characteristics analysis, ion proportional coefficient analysis, and hydrogen-oxygen isotope analysis were applied. Combined with the changes in river flow monitoring values, the evolution characteristics of mine water quality were qualitatively analyzed, and the recharge proportions of water-filling sources were quantitatively evaluated. The results show that the hydrochemical type of groundwater in the northern wing changes from HCO3—Ca·Na type to HCO3—Na type with increasing burial depth. The hydrochemical types of mine water, aquifer groundwater, and surface water in the southern wing are similar, all being HCO3—Na type. The formation of their hydrochemical components is mainly controlled by water-rock interaction and also affected by reverse cation exchange adsorption, with the main ionic components derived from the dissolution of silicate minerals. The main recharge sources of mine water in Coal Mine 2 are the bedrock aquifer (66.2%) and the Quaternary aquifer (21.5%). The main recharge sources of mine water in Coal Mine 3 in the southern wing are surface water and shallow groundwater, with corresponding recharge proportions of 23.6% and 29.6% respectively, while the bedrock aquifer recharge proportion decreases to 46.8%. The water-conducting fractured zone formed by repeated disturbances has connected the surface, becoming the main water-filling channel for surface water recharge to mine water. This study presents a recharge path and intensity model for groundwater and mine water applicable to shallow coal seam areas under repeated disturbance conditions, and proposes targeted water disaster prevention and control suggestions integrating “normalized monitoring - flood season early warning - post-mining reconstruction”. The research has important guiding significance for promoting regional water resource protection and ensuring the safety of regional coal mining. In subsequent research, the advancing speed and lateral recharge intensity should be included as research variables to comprehensively consider their influence laws on the quality and quantity changes of mine water inflow.
Intellectualization of the flotation process is a key approach to improving the process efficiency of coking coal preparation plants. This paper first conducts an in-depth analysis of the factors influencing coal slime flotation performance, identifies reagent dosage as the core control variable for flotation intellectualization in most coal preparation plants, and then systematically reviews the research status and technical progress of intelligent reagent dosing models and ash content prediction models for coal slime flotation at home and abroad: in the field of intelligent reagent dosing, it elaborates on the modeling proce. Compares a series of models such as linear regression (including Ridge regression and Lasso regression), support vector regression (SVR), BP neural network, long short-term memory (LSTM) network, and gated recurrent unit (GRU), analyzes the prediction accuracy of each model under different application scenarios as well as the adaptability of each model to operating conditions such as feedstock stability and data volume, while in the field of intelligent ash content prediction, it summarizes the modeling logic, model characteristics of the feature engineering modeling method based on machine vision and the transfer learning method based on convolutional neural network (CNN), along with their adaptability to coal preparation plants in terms of data volume, computing power, and feedstock stability. The current mainstream flotation reagent dosing control system adopts a “feedforward + feedback” regulation architecture: in the feedforward link, the reagent addition model constructed based on machine learning or neural networks can make up for the shortcomings of traditional manual reagent dosing, and in the feedback link, the ash content prediction model based on machine vision-based feature engineering and CNN-based transfer learning overcomes the defects of lag and poor accuracy of traditionline ash measurement methods, providing reliable quality feedback for closed-loop control. On this basis, the paper further prospects the intelligent control system for coal slime flotation: supported by the closed-loop mechanism of “feedforward intelligent reagent dosing - feedback ash content prediction”, this system will establish a full-process intelligent regulation system featuring “data-driven - model collaboration - closed-loop optimization”, promote the transformation of the flotation process from experience-driven to data-driven, provide references for the intelligent upgrading of flotation in coal preparation plants, and contribute to the high-quality development of the coal industry.
Aiming at the challenges associated with 0.7–1.0 m extremely thin coal seam mining in China, including restricted working space, poor equipment adaptability, limited intelligent mining capability, and inadequate resource recovery, this study takes an extremely thin coal seam working face in the eastern Heilongjiang mining area as the engineering background and investigates the key technologies and equipment for intelligent high-efficiency mining. A dynamic updating method for the geological model was developed by integrating geological characteristics with multi-source coal–rock interface sensing information, integrating roadway sketching, borehole detection, in-seam seismic exploration and image recognition data, to realize dynamic updating and transparent display of geological information such as coal seam roof-floor fluctuation and fault structures. On this basis, a full closed-loop intelligent ventilation control system featuring “perception-decision-regulation” was constructed to realize dynamic and precise air volume regulation at the working face, forming a collaborative guarantee technology system integrating geology and ventilation. Targeting the narrow space constraints of extremely thin coal seams, a complete set of mining equipment suitable for extremely thin coal seam conditions was developed, including bridge-type low-profile shearer, hydraulic supports with split elastic connecting top beams, permanent-magnet variable-frequency-drive scraper conveyor and intelligent cable towing device with coal-ploughing float coal cleaning function. Key operating parameters such as drum helix angle and rotation speed were optimized, addressing challenges such as low coal loading efficiency and cable jamming during dragging in extremely thin coal seams. A shearer automatic control system based on a dual-DSP architecture and an electro-hydraulic control system based on CAN/Modbus TCP industrial Ethernet were established, implementing core functions such as shearer memory cutting, automatic hydraulic support following, and coordinated operation of the three machines. In addition, an integrated intelligent mining management and control platform incorporating a transparent geological model and intelligent ventilation control was constructed. An engineering demonstration was carried out at Shuangyang Coal Mine. The field application results show that the demonstration working face realized an intelligent mining mode featuring no personnel following the shearer, on-site patrol inspection, and remote centralized control. The monthly output remained above 30000 tons, the longwall extraction efficiency increased by 300%, the fully mechanized equipment operation rate increased to over 85%, the coal recovery rate exceeded 95%, and the direct production cost per tonne of coal decreased by 32.8%, the electricity consumption per tonne of coal decreased by 15.1%, and the number of underground workers per shift reduced by 67%. The developed replicable and scalable technology and equipment system provides an integrated technical approach for intelligent mining of extremely thin coal seams and offers an engineering reference for the safe and efficient extraction of coal resources under similar geological and mining conditions.
The high-value utilization of coal-based solid waste and the confined encapsulation of phase change materials are recognized as effective routes toward thermal energy storage and industrial solid-waste valorization, with the synergistic regulation of phase change materials by porous frameworks as the central theme. Research advances are systematically reviewed regarding the preparation, performance tailoring, and applications of composite phase change materials confined within porous frameworks derived from coal-based solid waste, with particular focus on the synergistic regulatory mechanism that couples geometric confinement effects and interfacial interactions. The physicochemical characteristics of different solid wastes, including Si/Al composition, pore structure, residual carbon, and surface functional groups are analyzed as the fundamental basis supporting the confinement-interface synergy. Coal gasification slag is shown to form a “carbon–silicon” bicontinuous mesoporous carrier upon acid etching, which combines the triple advantages of mesoporous confinement, carbon-based thermal conduction, and oxygen-containing functional groups at the interface. Fly ash can be converted into mesoporous silica after modification; coal gangue exhibits enhanced reactivity after thermal activation; and coal cinder, dominated by macropores, requires surface modification. The quantitative influences of pore size and surface functional-group density on phase-transition temperature, phase-change enthalpy, and crystallization behavior are discussed in the framework of the Gibbs–Thomson equation and its extended form. The pore-size dependence of the confinement effect is characterized by three distinct regimes, within which the mesoporous scale enables a trade-off between thermal storage density and cycling stability. A negative correlation is identified between surface silanol density and phase-change enthalpy; amino functionalization is found to weaken excessively strong hydrogen bonding and restore crystallization capacity. The “carbon–silicon” bicontinuous network constructed by residual carbon simultaneously improves thermal conductivity and cycling stability. Various thermal-conductivity enhancement strategies and long-term cycling stability characteristics are summarized. Coal-based composite phase change materials are demonstrated to achieve combined thermal storage and mechanical performance in building matrices, efficient photothermal conversion in solar energy systems, and active temperature-field regulation via endothermic/exothermic phase-change processes in coal-mine thermal hazard control. The cross-scenario commonalities are distilled as follows: precise matching between the phase-transition temperature and the target temperature window serves as the prerequisite; framework-confined interfacial synergy provides the guarantee; and the spatiotemporal distribution of latent heat storage/release constitutes the core. A “three-step design guideline” is proposed for coal-based solid waste frameworks: selection of mesoporous frameworks for moderate geometric confinement, regulation of silanol density to balance interfacial hydrogen-bonding strength, and construction of thermal conduction networks using intrinsic residual carbon or supplemental additives, thereby enabling synergistic optimization of thermal conductivity and thermal storage density. These guidelines provide a technical framework for the structural design and application-oriented selection of coal-based composite phase change materials.
The critical stress is a foundation for evaluating the safety of roadways in rockburst coal mines. Currently, theoretical formulas are widely used to estimate the critical stress, possessing limited applicability. The self-developed StrataKing (a GPU parallel computing system for strata movement), undergoing development over a decade, demonstrates high efficiency, high precision, large-scale computational capability, and apparent mining features, and has been combined with the disturbance response instability theory of rockbursts to investigate the critical stress-impact energy index relation of the circular roadway under hydrostatic pressure and without supports, exhibiting a great potential of high-performance computing in rockbursts. Numerical results of the critical stress of the roadway with a combination of bolts and a hydraulic support were obtained by use of StrataKing, in which the bolt is allowed to break and the hydraulic support is allowed to crack. Firstly, the mechanical behaviors of the tensile bolt and the hydraulic support were modeled to validate the correctness of the numerical method for supporting components. Then, for an actual case, the critical stress of the roadway with a combination of bolts and a hydraulic support was calculated, and evolution of the roof subsidence and displacements at two sides were monitored. For comparison, the critical stresses of roadways with bolts and without were also calculated. Finally, to demonstrate the correctness and advantages of the proposed method, the results obtained in this study were compared with the theoretical critical stresses based on the disturbance response instability theory of rockbursts. Results show that the critical stress is the highest for the roadway with a combination of bolts and a hydraulic support, which is more effective for prevention of rockbursts. A combination of the bolts and a hydraulic support provides a better protective effect for the roadway roof, not for two sides of the roadway. The critical stress calculated by StrataKing for the roadway with a combination of bolts and a hydraulic support is significantly higher than the theoretical result without correction, higher than the theoretical result corrected by a fitted curve-based modification coefficient, but lower than the theoretical result corrected by the maximum modification coefficient. Compared with the theoretical calculation, the numerical simulation of the critical stress is more suitable for actual complex cases. Thus, prevention of rockbursts is more scientific. StrataKing can provide a powerful computing power support for the safe assessment of roadways in rockburst coal mines, which is helpful for the digital transformation and high-quality development of the coal industry.
Mining-induced seismicity, a type of non-natural seismic event triggered by mining activities, poses a major threat to the safety of coal mine production due to the rapid release of elastic energy and the potential damage to underground structures and surface buildings. Focusing on a seismic event in a coal mine in Heilongjiang Province, where strong ground vibration was observed at the surface but not perceived at the working face, a combined approach of theoretical analysis, numerical simulation, and field monitoring is employed. The study analyzes the mechanism of mining-induced seismicity associated with cooperative fracture of sub-key strata in overlying goaf areas under repeated mining. A three-zone displacement mechanical model based on spring–Maxwell elements is established to represent the distinct mechanical behaviors of different overburden blocks. Multiple numerical simulation schemes are designed to comparatively investigate the propagation and attenuation characteristics of seismic wave carriers under different overburden conditions. The results show that large-scale retreat mining in the underlying working face creates new migration space for the overlying goaf, disrupting the original stress balance. Fracture of the sub-key strata in the uncollapsed roof of the original goaf then releases a large amount of accumulated elastic energy, triggering mining-induced seismicity. After seismic waves propagate through the goaf, the peak particle velocity and acceleration are attenuated by approximately 84% and 90%, respectively, compared with conditions without an overlying goaf, and both parameters approach zero at the underlying coal seam working face. These results indicate that the goaf acts as an effective buffer and energy-dissipating medium for seismic wave propagation. On this basis, a regional protective technology centered on “blasting-induced roof fracturing combined with coal seam borehole pressure relief ” is proposed to pre-fracture the hard roof and relieve stress concentration in advance. Subsequent microseismic monitoring shows that the frequency of high-energy mining-induced seismic events decreases compared with the period before implementation, and the capability for dynamic disaster prevention and control in deep mining is enhanced.
