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The situation of coal as the stabilizer guarantee the energy safety in China cannot be changed in the short term, and it will continue to face the problems of coal resource protection and the low utilization rate of coal-based solid waste. Through innovative mining methods, improving the recovery rate of coal resources and the large-scale disposal of coal-based solid waste, a new path is being paved for the green and sustainable development of the coal industry. Based on the in-depth research on the development status of coal mining technology, a new roadway excavation method of “excavation-backfill-retention” is proposed. This paper systematically discusses the scientific problems and key technologies of the “excavation-backfill-retention” construction method from three aspects: rapid excavation, continuous and efficient backfilling and safe construction of large-section roadways. The research results show that ① aiming at the engineering problems such as the fast excavation of large section roadway and the stability control of surrounding rock of heading face, three scientific problems are summarized: the matching mechanism between coal and rock characteristics and cutting parameters of roadway boring machine, the spatial transfer mechanism of overburden load and the deformation mechanism of surrounding rock, the interaction relationship between anchor/cable roof and support mechanism. The technology system has been built, which is based on the real-time sensing of the geological environment in the excavation area, the intelligent cooperative operation of the multi-process of falling, loading and transporting coal, the aging control of surrounding rock of the drilling anchor support together with excavation, the anti-leakage and ventilation optimization of the large section roadway. ② The scientific problems of continuous and efficient backfilling are summarized from the two aspects of timely construction of large section roadway bearing system and its bearing performance regulation, including the co-bearing mechanism of background coal anchor/cable, the hydration consolidation mechanism of multi-component solid waste base backfill materials, and the space-time evolution law of physical and mechanical characteristics of backfill are clarified. A continuous and efficient backfill key technology system with the core of safe and efficient backfill space construction, backfill material performance control and backfill material flow-consolidation perception has been established. The breakthrough of relevant theories and technologies can provide a theoretical basis for raw material selection and ratio design of backfill materials, additive development/selection and working performance control, excavation rate and backfill step optimization design, consolidation monitoring of backfill body, etc. ③ Based on the key problems of roadway safety and surrounding rock easy to break, sheet and damage in the whole life cycle, the paper elaborates three scientific problems: the spatial and temporal distribution characteristics of stress field of roadway surrounding rock, the evolution mechanism of roadway deformation and damage, the engineering quality monitoring and stability regulation theory of roadway surrounding rock. The key technology system is formed with the intelligent stability warning of the rock surrounding the roadway and the deformation control of the rock surrounding the roadway as the core. It is of great significance to conduct the scientific research and technical demonstration of the “excavation-backfill-retention” construction method in coal mines, and to realize the synergy of large-scale solid waste disposal, efficient coal pillar section recovery and rapid roadway excavation, which can promote the green and low-carbon transformation and development of the coal industry.

In order to systematically understand the various types of water hazards and standardize the management of water prevention and control work in coal mines, the National Mine Safety Administration in June 2022 extended the “three zones” management methodology for old goaf water prevention and control to more types of water hazards, such as roof water, floor water, and structural water. However, in the process of dividing the “three zones” of water prevention and control in coal mines, it is revealed that the water damage causing factors and water damage management situation are not closely linked with the division standard, and that technically different divisions are not made for different coal seams and mining areas, and there are inconsistencies in the scope of the division area, and the standardization and timeliness of the division results. Accordingly, combined with the purpose of water hazard prevention and control “three zones” division, compared the similarities and differences between the new and old “three zones” division work, this paper clarifies the degree of hydrogeological conditions survey, water hazard analysis, water hazard management as elements of the division principles, and determines the technical path of the division of the “three zones”. Combining the characteristics of five common types of water hazards in coal mines, the paper puts forward the division method of different types of water hazards, that is: surface water hazard should be divided according to the distribution and development characteristics of surface water bodies in the mining area and the degree of influence of atmospheric precipitation, landslides and other geological disasters in mining. The roof water hazard should be divided according to whether there is a strong water-rich aquifer, a medium water-rich but hydrostatic reservoir-rich aquifer, a loose aquifer. The floor water hazard should be divided according to the relationship between the thickness of the floor water barrier and the depth of the floor mine pressure damage zone in the coal seam pressure mining area, as well as the size of the floor water inrush coefficient. The old goaf water hazard should be divided according to the distribution range and amount of water in the mine and the surrounding mines. The structural water hazards should be divided according to the water-richness, water content, and water source conduction of geological structures and bad geological bodies such as faults, trap columns and caves in the mining area. The key points and difficulties of the division work include the clear division of time and space scope, the comprehensive analysis of division standards, the clear management responsibilities for the “three zones”, and the dynamic transformation of division results. On this basis, typical coal mines with various types of water hazards and complex hydrogeological conditions are selected as case studies. Following the principle of division, according to the division standard, the mineable zone, the slow mining zone and no-mining zone are divided by the method of separating coal seams and mining areas, and detailed explanations are given. The significance of carrying out the division of the “three zones” for water hazard prevention and control is clarified, which can enhance the comprehensive detection level, strengthen the prediction ability, and identify the direction of water hazard management in order to guide and standardize the division of the “three zones” for water prevention and control in the coal mines of China.

With the development of arid and semi-arid regions in China, the hazards posed by collapsible sands to engineering construction have become increasingly significant. In order to investigate the collapsibility regularity and its influencing factors of sand soils, this paper focuses on the wind-blown sands at the southern edge of the Maowusu Desert. Initially, by controlling the single factor laboratory compression tests, the collapsibility regularity of wind-blown sand under different working conditions was investigated. Subsequently, using PFC3D (three-dimensional particle flow software) for numerical simulation of the laboratory compression tests on wind-blown sands, the paper explores the effects of different porosities and particle compositions on the collapsibility of sandy soils. The research results indicate that the collapsibility coefficient of sandy soils shows a trend of first increasing and then decreasing with pressure, reaching its maximum value at 150 kPa. With the increase in dry density or moisture content, the collapsibility coefficient of sand decreases. Compared to moisture content, dry density has a greater impact on the collapsibility of sandy soils. There is a positive correlation between the collapsibility coefficient of wind-blown sand and its porosity. The initial porosity of the collapsibility of the wind-blown sand on the southern edge of the Maowusu Desert is 0.425. When the ratio of particle content between 0.075～0.25 mm and 0.25～0.5 mm is 0.35∶0.65, the collapsibility of sandy soils is maximized. The research results comprehensively describe the entire process of laboratory compression tests on sand from macro to micro levels, revealing the collapsibility regularity and its influencing factors on wind-blown sand from multiple scales. This can provide a reference for engineering construction in the Maowusu Desert and provide certain ideas and basis for the research on particle flow numerical simulation of sand.

Convolutional neural network (CNN) models are widely used in landslide susceptibility assessment due to their powerful feature extraction capabilities, and traditional CNN is no longer able to meet the requirements. Therefore, this paper proposes a multi-scale convolutional neural networks (MSCNN) model that can take into account deep and shallow features. By increasing the depth of the model and expanding the receptive field of samples, the MSCNN can tap deeper and more stable features to improve the reliability of landslide susceptibility assessment in complex scenarios. In this study, Shenzhen City is selected as the research area, and 12 landslide conditioning factors of landslides in Shenzhen City were selected based on systematic and representative principles. A multi-scale convolutional neural network landslide susceptibility assessment model is constructed and compared with methods such as multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF). The results show that the AUC value (0.99) of the MSCNN model constructed in this paper is higher than that of MLP (0.97), SVM (0.91), and RF (0.85), which proves that the proposed MSCNN model has excellent prediction ability. The area of extremely high susceptibility in Shenzhen City is approximately 105.3 km², accounting for 4.98% of the total area of the study area, mainly distributed in Longgang District with steep slopes, sparse vegetation cover, and frequent human engineering activities. Slope, surface roughness, and surface relief are identified as the main conditioning factors affecting landslides in Shenzhen City. The landslide susceptibility mapping implemented in this paper reflects the current distribution of landslide disasters in Shenzhen City, providing data support and key technical support for future landslide disaster prevention and control in Shenzhen City.

This paper presents a preliminary investigation of the instability and landslide of a road subgrade slope that occurred on May 1, 2024 along Mei–Da Expressway. The investigation method is on the basis of past investigation results and findings about instability and landslide of road subgrade slopes in Hong Kong. The Mei–Da Expressway subgrade was constructed by cutting and filling on mountainous slopes. The landslide occurred at a fill slope along a gully. The fill soil was excavated from local soil of completely decomposed granite (CDG). The paper tests the particle size distribution and liquid and plastic limits of the three CDG soil samples that were excavated from adjacent natural slopes. It then examines the stability of the fill slope with a simplified geological slope model. It further investigates the catchments before and after the road construction. It then presents a possible mechanism for the slope instability and landslide. The field observations by others can confirm this mechanism. The cutting and filling of the hillside slopes significantly changed the runoff paths of the three natural catchments above the road. The road can intercept the runoff along the three gullies and direct all the runoff into the fill slope. The large volume of rainfall water can erode and liquefy the fills, which can cause the instability and landslide of the road subgrade slope. There is an urgent need to further investigate this mode of road subgrade instability and landslide since it is not uncommon.

Early detection and distinguish of mine fires can avoid or reduce casualties, property damage, and secondary accidents. There are no natural light sources such as sunlight, moonlight, starlight, and lightning underground, and the main factor affecting the recognition of mine fire images is the mine light source. Circularity can eliminate interference from circular light sources, but it is difficult to exclude interference from non-circular light sources. Rectangularity can eliminate interference from rectangular light sources, but it is difficult to exclude interference from non-rectangular light sources. In engineering practice, due to the different shooting angles of the camera, the image of the mine light source may deform and cannot present an ideal regular shape. It is difficult to eliminate the interference of the mine light source using circularity and rectangularity algorithms. It has been revealed that the area of the external connection graphic area of the flame image is significantly larger than the actual area of the image, and the external connection graphic area of the actual light source image of the mine, such as circular lamps, rectangular lamps, and square lamps, is approximately equal to the actual area of the light source image. In this study, a mine fire recognition and anti-interference method is proposed based on the internal concavity of image, the ratio of the target image area to the external connection graphic area of the image (i.e. internal concavity of image) is calculated, and the flames and mine light sources are distinguished based on the small concavity value in the flame image and the large concavity value in the mine light source image. The internal concavity method proposed in this paper is not affected by the distance from the camera to the detection target and the size of the image, the installation position and angle of the camera to capture the detection target, and the shape of the mine light source. It has strong adaptability and high recognition accuracy. The experiment shows that the internal concave recognition method calculates the maximum average difference between the mine interference light source and the flame image, with the smallest fluctuation and the best discrimination. It is also least affected by the camera’s shooting angle and distance, and has the strongest anti-interference ability, with an accuracy of 91.6%. The rectangular recognition method calculates the average difference between the mine interference light source and the flame image, with small fluctuations and good discrimination. It is less affected by the camera’s shooting angle and distance, and has average anti-interference ability, with an accuracy rate of 72.5%. The roundness recognition method calculates the minimum average difference between the mine interference light source and the flame image, with the highest fluctuation and the worst discrimination. It is less affected by the camera shooting distance and more affected by the camera shooting angle, and has the worst anti-interference ability, with an accuracy of 12.0%. Therefore, the internal concave recognition method proposed in this paper is superior to rectangular and circular degrees, with the best discrimination, minimal influence from camera shooting angle and distance, and the strongest anti-interference ability.

In order to further improve the intelligent control level of fully mechanized mining equipment in coal mines and achieve the normalized operation of intelligent mining face, this paper proposes the related concepts and system architecture of intelligent mining face driving control based on digital twin. The digital twin system of intelligent mining face is composed of physical equipment, virtual twin and virtual and real interaction model. The virtual model mapped with physical equipment is established by digital method to achieve the purpose of virtual and real interaction, intelligent decision, accurate control and dynamic evolution in fully mechanized mining equipment during operation. The paper expounds the normal operation requirements of intelligent mining face and related control difficulties of shearer, hydraulic support and scraper conveyor, and proposes the single-machine digital twin driving control architecture of smart mining face, including mechanism model, control model, twin data model and digital twin model synchronization and evolution. The method of digital twin virtual-real interaction is described, the Cyber-Physical System is used to guarantee the information interaction ability, and the knowledge model is used to solve the data congestion problem, which provides a real-time virtual-real interaction for the digital twin control system of intelligent mining face. A three-machine cooperative control method driven by the digital twin of intelligent mining face is proposed, including three-machine correlation, intelligent coal mining control, intelligent support control and intelligent transportation control. Finally, taking the practical application of digital twin in mines as an example, the intelligent control of digital twin is verified by establishing the relevant model and designing the relevant experiment scheme. By carrying out theoretical research on digital twin intelligent control architecture and mode, the paper aims to solve the current problems of low environmental perception, poor equipment prediction accuracy and high manual intervention intensity in fully mechanized mining face, realize an adaptive control and human-computer interaction of equipment under complex environmental conditions, and provide a reference for the intelligent construction of coal mines.

Significance The micromigration of shale oil refers to the phenomenon in which oil is generated in organic-rich layers and expelled at short distances to adjacent, preferable porous and permeable, organic-lean layers in shale systems. Micromigration can effectively improve the oil content and quality of organic-lean layers, even surpassing some organic-rich shale layers based on the exploration practices. Therefore, it is necessary to conduct a systematic study on the micromigration phenomenon of shale oil. Progress Based on the current research progress, this paper first identifies the main tracers of shale oil micromigration, which include rock pyrolysis parameters, hydrocarbon components, biomarkers, NSO compounds, as well as isotopes. The fundamental principle relies on fractionation between migrated hydrocarbons and retained hydrocarbons based on their geochemical properties. Analysis revealed that micromigration can lead to a dispersed distribution of hydrocarbon generation activation energy in organic-lean shale layers, resulting in an earlier hydrocarbon generation threshold. Moreover, the accumulation of light hydrocarbons in a free state in organic-lean layers can further increase the difference of hydrocarbon components between generative units and in-source reservoirs, thereby affecting the oil-bearing and mobility characteristics of shale. Based on the effects of petroleum migration and geological zonation, this paper reveals that micromigration occurs throughout the entire process of hydrocarbon generation, expulsion, and retention. It serves as a bridge connecting all elements of petroleum accumulation within shale systems, influencing the differential enrichment of shale oil. Conclusions and Prospects Comprehensive geochemical and geophysical methods are effective ways to identify micromigration in shale systems and will provide a new perspective for revealing the dynamic differential enrichment of lacustrine shale oil.

Land subsidence is a worldwide geological hazard. Differential land subsidence has posed the major threat to urban infrastructure, linear rail transit and underground space development and utilization, and also restricted the sustainable development of the economy and society. This paper systematically elaborates on the research progresses on land deformation acquisition, evolution mechanism and simulation of land subsidence, and focuses on the land deformation acquisition technology based on InSAR monitoring and multi-source deformation data fusion, as well as the correlation analysis, statistical analysis, machine learning and other methods to analyze the relationship between the evolution of land subsidence and various influencing factors based on geotechnical experiment and long time series observation data. On this basis, the advantages and disadvantages of land subsidence simulation models such as groundwater flow field-land deformation model, mathematical statistical model and machine learning model are explored. It is found that multi-source deformation data fusion can improve the spatiotemporal resolution of land deformation. The differences in geological structure, lithology, groundwater exploitation, and dynamic and static loads are factors contributing to the differential evolution of land subsidence. The difficulty in balancing the computational efficiency and interpretability of mathematical models for land subsidence is the main problem in simulation. According to the literature review, the current researches mainly focus on land subsidence caused by groundwater over-exploitation. This paper further proposes the future research directions for land subsidence, under the background of climate change, new hydrological condition and dataset, and based on the fusion of data through remote sensing and field observations, integrating the latest progress of InSAR, GeoAI, cloud platform and other technologies to reveal the evolution mechanism of land subsidence considering the climate change and anthropic activities and provide technical support for regional land subsidence prevention and urban safety.

Surface mining is an important way of mining mineral resources. The state and local governments have put forward higher requirements for surface mining in China. Therefore, it is particularly urgent to take surface mining as a science to carry out systematic research, reveal the laws of mining process and phenomenon occurred, and make scientific explanations. First of all, the major technical achievements in the field of surface mining of solid mineral resources in China in the past 40 years were summarized from three aspects: the basic theory of surface mining, the development of key complete sets of equipment and blasting engineering technology. Then, the modern scientific metrology and information metrology technologies were used to conduct a multivariate dynamic analysis of 7128 papers and reports in the past 40 years, and a multi-dimensional quantitative description of the development and evolution process of the main research topics, including the time dimension, was carried out by the cluster analysis. It is found that the evolution of research topics is the result of the coupling effect of many factors, such as technological development, mining status, policy environment, etc. Based on the sorting of the existing major scientific and technological achievements and the objective literature measurement results, it is pointed out that the goal of the future surface mining science is to form a systematic and comprehensive safe, green, efficient and intelligent surface mining technology system, and the realization path is given, that is, to form a hot research topic of surface mining technology system and major equipment, and to strengthen the deep cross integration between the existing hot research and surface mining technology system and major equipment. It also provides some useful suggestions on how to jointly tackle major scientific and technological problems with the advantageous resources of various themes inside and outside the industry to achieve a substantial collaborative innovation among multiple themes. Finally, from the perspective of energy and ecology, the paper looks forward to the development direction of major basic theories and technologies of the future surface mining science from seven aspects: mining area planning theory, intelligent mining design principle, intelligent cluster scheduling theory, safe and efficient mining technology of coal mining in spontaneous combustion prone extra thick coal seams, high slope stability control technology, efficient belt conveyor transportation technology under complex working conditions, and intelligent surface mine system engineering. The development direction of the future surface mining equipment is prospected from five aspects: high efficiency mobile crushing equipment, modular semi-fixed crushing equipment, continuous mining process system equipment, large inclination transportation equipment and large dump machine. It is expected that the study can be used as a reference for scientists and engineers in the surface mining field.

Intelligent recognition technology for underground safety violations in coal mines has become the primary means of safety management and information acquisition. However, the accuracy of intelligent recognition is reduced by factors such as low illumination, point light sources, and high dust in the underground spatial environment. To overcome those problems, this paper proposes a multi-weight fusion image enhancement method, which achieves the fusion enhancement of image brightness and illumination balance. The monitoring image brightness is increased by using the Gamma algorithm. Based on the brightness enhancement, the HSV spatial transformation is carried out to keep the hue component and saturation component unchanged, the illumination component is extracted by using a multi-scale Gaussian function, and then the regions where the illumination component is too strong and too weak are adjusted by using an improved two-dimensional gamma function to achieve an illumination equalization. Combining the three weights of Laplacian contrast, luminance, and saturation and fusing the luminance-enhanced and illuminance-balanced images by Gaussian and Laplacian pyramids, the intelligent surveillance image enhancement is achieved. Through the experimental verification of the intelligent recognition of helmets in mine monitoring, the image enhancement method proposed in this paper and the MSR, MSRCP, MSRCR, and AMSRCR algorithms are evaluated in terms of image evaluation indexes such as standard deviation, peak signal-to-noise ratio, and information entropy, and the peak signal-to-noise ratio is improved by 32.44% on average compared with other algorithms, the standard deviation is improved by 115.38% on average compared with the original image, and the average improvement in standard deviation is 115.38% compared with the original image and 47.30% compared with other algorithms, and the accuracy of helmet recognition reaches 86.7%, an average improvement of 47.52% compared with other algorithms. The results show that the algorithm in this paper can effectively improve the contrast and clarity of mine images, reduce the halo phenomenon, and significantly improve the accuracy of target recognition in intelligent mine monitoring. It can lay a solid foundation for the intelligent identification of safety violations in underground coal mines.

Pulverized fuel ash (PFA) is a by-product from coal-fired power plants. The generation of PFA is huge and increases yearly. A large amount of untreated PFA is harmful to the environment, and it is also a waste of resources. Recycling PFA as construction materials would improve resource utilization efficiency, reduce environmental risks, conform to the demand for high-efficient and low-carbon utilization of solid waste and help to achieve the national strategy goals of carbon peak and carbon neutrality. The utilization efficiency of PFA as construction materials could be improved by optimizing production processes and developing new technologies, which would promote its large-scale and high-value utilization. In this paper, the general situation and physical and chemical properties of PFA are summarized. Various value-added utilization technologies of PFA as construction materials, including raw materials for cement production, supplementary cementitious materials, bricks and blocks, artificial aggregates, glass-ceramic materials, fire-resistant insulation materials, and new intelligent construction materials are comprehensively reviewed. This paper also introduces the research status of the utilization of PFA in construction materials, analyzes the applicability of different technologies, summarizes the latest technologies for preparing the PFA-based green construction materials and challenges faced in future research, provides detailed introductions to the mechanism of PFA application, and proposes thoughts on the problems existing in the utilization of PFA as construction materials. Finally, the further perspectives of the development of the PFA-derived low-carbon construction materials are highlighted. The study suggests that the “traditional large-scale consumption of PFA” and “high-value utilization of PFA” should be researched in parallel, and theoretical research and engineering practice should support each other, which would provide some scientific references for the sustainable management of PFA.

With the extension of coal mining in China, fault water inrush has become one of major disasters threatening the safety of coal mine production. Based on the research results related to the mining-induced fault water inrush, this paper proposes a conceptual model of water inrush caused by the erosion synergy of mining-induced rock mass damage rupture and fractured rock mass (fault), derives the permeability evolution equation of the two media, and systematically constructs the cooperative disaster causing mechanism model between mining failure and particle erosion inside faults. The numerical simulation is conducted to study the deformation and failure of rock mass, the particle transport in faults and the evolution characteristics of seepage channel, and systematically explain the temporal and spatial evolution mechanism of seepage catastrophe caused by mining-induced fault inrush. The results show that: ① With the continuous advancement of working face, the damage field of mine floor rock mass is connected with the fault erosion fracture, forming a seepage path of aquifer-fault-mining fracture-working face, and with the increase of erosion time, it finally develops into several dominant water diversion channels, resulting in a sharp increase in water inflow at the working face and a lagging water inrush. ② With the increase of seepage time, the water inflow and fracture opening degree inside faults all show three stages: slow change, sudden increase and stable, and the erosion particle concentration shows a trend of first increasing and then decreasing. ③ Under the geological conditions of the mining area studied in this paper, in order to prevent the occurrence of fault water inrush, the methods such as advanced grouting or leaving water prevention coal pillars can be adopted, and the advance grouting time should be before the bottom plate fracture zone connects faults, if grouting is not applied, the width of the reasonable water prevention coal pillar should not be less than 20 m.

Objective In geothermal exploration, a clay cap is a typical hydrothermal geothermal system, and its depth and distribution range can provide crucial information for delineating the scope of geothermal resources and determining the location of geothermal drilling. Clay caps are usually composed of a clay layer formed through hydrothermal reactions and are characterized by low resistance. The low-resistivity cap can be effectively imaged using the audio-frequency magnetotelluric method. To obtain uncertainty information about the distribution of clay cap layers and imaging results, this paper employs the 1D trans-dimensional Bayesian inversion method to investigate the detection capabilities of low-resistance cap layers in geothermal areas through audio electromagnetic data. Methods In this paper, a model test is first carried out to establish a geoelectric model of a typical geothermal system.Subsequently, a 1D trans-dimensional Bayesian algorithm is used to invert the synthetic data to obtain the uncertainty information of the subsurface electrical structure and interface position. Then, the method was applied to the processing of measured audio frequency magnetotelluric data in the Yanggao geothermal area of Shanxi Province. Results This method has relatively accurate identification ability for low-resistivity clay caps, and the obtained uncertainty analysis results of the upper and lower interfaces of low-resistivity caps are also relatively reliable according to numerical tests. It was found that this method has a good ability to identify shallow low-resistivity caps and can provide an uncertainty evaluation of the clay cap interface position via field data tests. The 2D inversion results of this survey line verify the reliability of the 1D inversion. Conclusion This method has relatively accurate imaging capabilities and uncertainty analysis capabilities for shallow geothermal clay caprocks and has strong application prospects in geothermal detection.

Objective Thrust faults and their associated folds are important structures of continental tectonic deformation, widely distributed at plate boundaries and within plates. The activity of these thrust faults can trigger severe seismic disasters, such as the 1999 Chi-Chi earthquake in Taiwan and the 2008 Wenchuan earthquake. However, research on surface ruptures and associated disasters caused by thrust faulting is relatively limited, mainly due to the complexity of their fault propagation processes. Studying thrust faults and their associated folds could enhance the capability of seismic hazard risk assessment and better predict earthquakes and potential secondary disasters. Methods This paper first introduces the meanings of fold-related faults and fold scarps and explains the impacts of surface uplift and lateral extension deformations on topography. Taking the Tian Shan active fold zone as an example, the paper focuses on analyzing the structural characteristics and landform deformation patterns of the Hejing thrust-and-fold belt in the northern margin of the Yanchi Basin and the Mingyaole anticline in the southern piedmont of the Tian Shan. It also discusses various types of structures, such as thrust faults, fold-related faults (flexural faults, flexural slip faults, and conjugate shear faults), and their effects on landforms. Based on this, the paper explores the relationship between the growth process of active folds and the formation of seismic geological disasters. Results and Conclusion It is believed that in a compressive tectonic environment, the growth of active folds and the formation of fault-related folds cause building displacement, tilting, and damage, thereby generating geological disasters. In particular, it emphasizes that the tilting of the ground on both sides and the footwall of active anticlines during the process of crustal shortening, vertical uplift, and lateral expansion poses a threat to the safe operation of major engineering structures. Simultaneously, the bending deformation caused by regional crustal shortening presents potential seismic risks and triggers geological hazards for significant linear engineering projects spanning active anticlines, warranting attention.

Coal-rock interface recognition technology is one of the key technologies for intelligent mining in coal mines. Based on high-frequency radar wave detection technology, high-precision detection of coal-rock interfaces can be achieved with mining, but there are still safety risks for equipment caused by rib spalling and roof caving in ultra-high mining heights (≥6 m) in mines, as well as spatial restrictions on equipment passing through during sudden changes in mining height (mining height ≤2 m). Based on previous work, this paper proposes a rapid dynamic detection system and method for coal-rock interfaces in mines using nodal GPR. The main contents include: ① Explaining the principle of the nodal GPR observation system in mines, designing a coal-rock interface recognition observation system plan and radar antenna sensor installation method based on the actual environment of the mine working face; ② Studying and proposing a nodal acquisition control system and information interaction transmission design plan to achieve dynamic data acquisition, control, and storage; ③ Studying and proposing enhanced processing methods for sensor detection data and coal-rock interface recognition algorithms based on nodal acquisition methods and radar reflection echo characteristics of coal-rock interfaces, which can effectively achieve intelligent recognition and tracking of coal-rock interfaces, as well as calculation of coal seam thickness and spatial coordinates. To verify the feasibility of this method, multiple geological radar antenna sensors with a center frequency of 1.5 GHz were used for physical model verification experiments, and a comparative analysis of nodal data acquisition and continuous data acquisition results was conducted. The experimental results show that both nodal and continuous acquisition methods can effectively identify coal-rock interfaces. Compared with continuous acquisition methods, the nodal detection method proposed in this paper can achieve rapid and dynamic repetitive data acquisition, with a single acquisition time controlled within 10 seconds, an average error of 1.07 cm for coal seam thickness detection results, a maximum error of 1.47 cm, and an average error percentage of 7.64%. This method provides technical support for dynamic high-precision detection of coal-rock interfaces in intelligent mining in mines.

With the continuous increase of coal mining depth, the occurrence and prevention of deep rockburst in China have become normalized. In order to improve the effectiveness of deep rockburst prevention and control technology, starting from the technical difficulties of deep rockburst prevention and control in on-site engineering, combined with practical data statistics of disaster prevention and control engineering, this study demonstrates that the deep rockburst in China is due to its high geological stress and large range of human mining disturbance. The stress recovery of surrounding rock is fast after rock stress unloading during the disaster prevention and control process. The low effectiveness of rockburst prevention and control can be attributed to the new requirements of “three highs and one low” prevention and control technology in deep mining compared to that in shallow mining, including high-strength large-sized drilling to relieve pressure, in order to solve the collapse prone problem of thick and hard coal seams; small spacing high-density drilling to solve the problem of disconnected pressure relief range in drilling; multiple rounds of repeated high-frequency construction to solve the problem of rapid stress recovery after unloading pressure in deep coal seams; and the mining face is advancing at a low speed to solve the problem of high mining disturbance intensity. In response to the new requirements of “three highs and one low” prevention and control mode for deep rockburst, in order to further improve the safety and reliability of rockburst prevention and control, and based on the limitations of optimizing development and mining deployment for conventional source rockburst prevention and control, this paper proposes the technology of actively regulating the structure and load of overlying rock layers in the deep rockburst prevention and control areas, and presents some further scientific problems that need to be solved. Against the background of several typical rockburst accidents in recent years with the problem of “missed targets” in the prevention and control plans, a local targeted prevention and control technology for deep rockburst mining space has been developed, and the scientific challenges that need to be solved in the future have been pointed out. Against the background of the difficulty in evaluating safety issues after the implementation of coal mine rockburst prevention and control measures, a deep rockburst prevention and control unloading standard evaluation technology is proposed, and the scientific difficulties that need to be solved in the future are pointed out. The coal industry vigorously promotes intelligent mining, but the disaster control still relies on manual labor and personnel to operate in a high-risk environment. This paper also explores the emerging research direction and scientific challenges of intelligent mining and intelligent prevention and control of deep rockburst. Finally, it is objectively pointed out that the prevention and control of rockburst is not purely a theoretical and technical issue, and the human understanding of technical issues is also one of the important reasons for rockburst accidents. Combining with the on-site engineering practice, this paper discusses the concept and mechanism of rockburst, whether rockburst can be predicted, whether rockburst can be prevented and controlled, and how to deal with rockburst mines and other industry focused technical issues. It is pointed out that the problem of rockburst engineering is a struggle between humans and nature, which requires practitioners to objectively understand, objectively accept, and conduct in-depth research. The current achievement is of significance.

In order to improve the production of coalbed methane vertical wells in the central and northern Zhengzhuang block, southern Qinshui Basin, Shanxi, China, this paper analyzes the reasons for the poor stimulation effect of medium-deep coalbed methane vertical wells, based on the ground stress test data and fracturing monitoring data of these evaluation wells in the study area, proposes targeted stimulation techniques, designs and carries out field comparative pilot studies and analyzes their results. The results show that there are three main reasons for the low production of these vertical wells in the study area. Firstly, the vertical fracture is dominant, resulting in the shorter length of hydraulic fractures. With the increase of burial depth, the length and width of fractures decreases at the same fracturing scale. Secondly, with the increase of burial depth, the embedment depth of proppants into coal rock increases and the closure of hydraulic fractures speeds up. As a result, the stable production time is short, and the main form of gas production curve is “single peak” type. Thirdly, after the initial fracturing, the coal body structure is much more broken, and new fractures are easy to enter the initial fractures, which increases the difficulty of creating new fractures, resulting in poor stimulation effect. In view of the above reasons, the paper proposes an innovative technology of pre-plug, large-scale and remote-support re-fracturing. Pre-plug means that relatively low displacement, sand ratio and scale are first used to fill initial fractures, and then large-scale re-fracturing is carried out to create new fractures. Large-scale fracturing refers to the fracturing with large displacement, large fluid volume and high sand ratio. In order to improve the stimulation effect of middle-deep reservoirs, the fracturing fluid volume is increased from 600−800 m3 to more than 1 300−2 000 m3, the displacement is increased from 6−8 m3/min to more than 10−14 m3/min, and a low viscosity fracturing fluid system combined with low density proppants is used to increase the sand ratio from 7%−8% to more than 10%−15%. Remote-support is a combination of self-suspended proppants and large displacement to increase proppants migration distance and increase the proportion of the propped fractures. The average daily production of a single well reached 1 380 m3, which was 1 190 m3 higher than that before, and nearly 1 000 m3 higher than the stable gas production of adjacent wells, realizing the production breakthrough of vertical wells in the low-production area of the middle-deep reservoir in the north of Zhengzhuang block. Results of the comparative pilot studies showed that the average net construction pressure increased by 3.3 MPa after pre-plug, compared with the initial fracturing, which means that new fractures were formed and resulted in the production increase by 1 000 m3 compared with that of the wells without the Pre-plug. The pilot results show that, in general, the larger the technical parameters of pre-plug, large-scale and remote-support re-fracturing, the better the production performance.

This paper briefly summarizes the importance, current situation and existing problems of earthquake science popularization in primary and secondary schools, and focuses on the development path of earthquake science popularization based on STEAM education concept. On the basis of clarifying the main purpose, service target group of earthquake science popularization education, and effective popular science content and form, this paper applies the concept of STEAM education to propose the effective path of earthquake science popularization in primary and secondary schools. Taking the junior high school section as an example to make a specific case analysis, this paper suggests to build an earthquake science popularization ecosystem from the perspective of STEAM education. STEAM education is an interdisciplinary education concept that integrates science, technology, engineering, arts and mathematics, emphasizing the integration of disciplines. It is a new form of learning in which taking projects as the main line, teachers as the lead, and students as the main body. This study argues that STEAM education needs to be integrated into the earthquake science popularization, and a high-quality science education system should be constructed, covering both on- and off-campus educational activities and active learning ability, so as to create an ecosystem suitable for the development of science popularization education.

Under the dual carbon goal， the focus and difficulty of the petroleum and petrochemical industry transition lie in exploring low-cost transition development paths. This needs to conduct systematic research on the development foundation and potential of various transition technologies， coordinate the development and application timing of these technologies， and thus form a technology portfolio and comprehensive plan supporting the optimal transition path. Carbon capture， utilization， and storage （CCUS） has high technological maturity and sound coupling with the petroleum and petrochemical industry and is a key technology for petroleum and petrochemical transition. However， the high cost remains the main obstacle to large-scale development. Analyzing the economy and development mode of CCUS plays an important role in determining the future development layout of the CCUS industry， and studying the potential of CCUS for the petroleum and petrochemical industry transition. To conduct an in-depth analysis on the economy of future CCUS technology and its potential in the transition of the petroleum and petrochemical industry， this paper focuses on CCUS with enhanced oil recovery （CCUS-EOR） and proposes a new analytical approach. Firstly， by comprehensively reviewing the entire process of CCUS-EOR， the costs including carbon capture， transportation， oil displacement， and storage are analyzed in detail， with the cost reduction of each in the future evaluated. Secondly， by the prediction of future oil prices and carbon prices， the economic benefits brought by oil displacement and carbon emission reduction are analyzed， and a cost-benefit comparison is conducted. Based on the cost-benefit analysis results， this paper further carries out a comprehensive economic evaluation of CCUS-EOR projects under different modes in China， which covers different carbon capture technologies， transportation modes， and storage strategies， revealing the profitability and sustainable development potential of CCUS-EOR projects under different scenarios. The results show that the CCUS-EOR economy is deeply affected by multiple factors such as carbon price， oil price， and oil displacement efficiency. In the medium and long term， carbon price changes have a greater influence on future CCUS-EOR returns. Under the high level of both carbon price and oil price， the profitability of CCUS-EOR projects is greater and more attractive. Meanwhile， the improvement of oil displacement efficiency can significantly increase the economic benefits of the projects. Currently， there are significant differences in the economy of various projects in China， which cannot fully guarantee significant profits. However， there is great room for improving the future economy. For the future CCUS-EOR development in China， it is necessary to break through the technological bottleneck in carbon capture links and focus on developing and applying pre-combustion capture technology to reduce capture costs and improve capture efficiency. Additionally， it is necessary to optimize the industrial layout to form a source-sink matching industrial cluster and thus achieve a synergistic effect in the industrial chain. At the same time， it is important to promote the development of the carbon trading market， guide carbon emission reduction behavior via the market mechanism， and create a favorable external environment for the promotion and application of CCUS-EOR technology in the petroleum and petrochemical industry.

Glutenite reservoirs in the north region of Lijin， Dongying Sag have complex mineral components， resulting in the low accuracy of the interpretation of physical parameters and the difficulty of defining the boundary of oil and dry layers. Based on the data of logging， mud logging， production test， and analysis testing， this paper combined crossplot chart identification with radar pattern recognition mode to effectively distinguish glutenite lithology in the area. Based on the lithology identification， oil-bearing occurrence analysis， and testing data analysis， this paper established the lower limits of physical and electrical properties of effective conglomerate and carbonate reservoirs. Combining with the production test data， this paper constructed the interpretation chart of classification and evaluation standard of the effective reservoir of glutenite in the north region of Lijin， Dongying Sag， and built the porosity and permeability parameter models of conglomerate and carbonate reservoirs， respectively， which provided a quantitative evaluation method for complex glutenite reservoirs in the north region of Lijin， Dongying Sag. The application has verified the research in the production wells of glutenite reservoirs in the north region of Lijin， Dongying Sag， and the results are promising.

Shale oil reservoir is a typical unconventional oil and gas resource that plays an essential role in the international energy supply market. Due to the complex pore structure and crude oil composition of shale oil reservoirs， the flow of crude oil in organic-rich shales has a certain complexity， and its flow behavior still needs to be further studied. Based on the stochastic simulation method， the flow characteristics of fluid in mixed-wet nanopores were considered， and an apparent oil permeability （AOP） model of shale oil reservoirs was established in this paper. The results show that the AOP of shale oil reservoirs is directly related to the molecular structure of alkanes， and its influence decreases with the increase of pore radius. The organic matter can improve the flow capacity of crude oil when the boundary slip length is large， and its AOP is about ten times the absolute permeability. At the same time， the pore radius reduction and wetting reversal effect triggered by adsorbed organic matter significantly impact the flow capacity of alkane molecules， and these effects cannot be ignored. The AOP model of shale oil reservoirs considering mixed-wet nanopores established in this paper helps understand the fluid flow mechanism of shale oil reservoirs and can provide theoretical support for productivity evaluation， dynamic analysis， and production system optimization of shale oil reservoirs.

Objective Black carbon is a carbonaceous mixture formed by the incomplete combustion of biomass and fossil fuels. Since black carbon has a high carbon content and an aromatized molecular structure, it can persist in the natural environment, suggesting that black carbon is an important component of the global carbon cycle. Although pioneering studies have advanced the understanding of nature, circulation fluxes, and reserves of black carbon in the geosphere, it is still necessary to further clarify the source-sink processes of black carbon and explore the importance of black carbon in the global carbon cycle. Methods Here, this study reviews the available data on pathways, fluxes, and time scales of the global black carbon cycle and analyses and summarizes the migration mechanisms and constraints in the source-sink process of marine black carbon. Results This paper concludes that marine sediments serve as a large reservoir for black carbon, with a reserve of 569-1 380 Pg. Black carbon can persist over millennia in marine sediments, which is associated with a long turnover time as an "effective carbon sink" in the context of "carbon neutrality". Moreover, black carbon exerts a negative feedback effect on global warming due to its longer turnover cycle time than biomass carbon. The deposition of black carbon into the sea is an effective means to enhance carbon sequestration in the ocean and could be an effective way to implement the carbon capture, utilization, and storage (CCUS) strategy. Conclusion In this paper, we propose that human-induced production of black carbon from biogenic combustion may be actively regulated and that the deposition pathways and burial areas of black carbon into the sea should also be optimized given the premise of ecological and environmental friendliness based on a summary and assessment of the strategic value and climate significance of black carbon in marine sediments in the context of "carbon neutrality". Therefore, the positive role of black carbon in "negative ocean carbon emissions" can provide a basic theoretical framework for achieving the goals of "carbon neutrality".

Objective Palaeomagnetic methods can be used to quantitatively constrain the Early Palaeozoic palaeo-position of the North China Block (NCB), which provides a crucial scientific basis for researching the evolution of the Proto-Tethyan Orogeny and the affinity of the NCB for Gondwana. However, the NCB has undergone considerable tectonic activity since the Early Palaeozoic, and the Ordos Basin in the western part of the NCB is rich in hydrocarbon resources. Late tectonic activity and the migration of hydrocarbon resources may have caused remagnetization of Early Palaeozoic strata. Methods Thus, in this paper, to determine the main magnetic minerals in various rocks and their ability to record the primary remanent magnetization, we carry out a series of detailed petrography, rock magnetism and stepwise demagnetization experiments on the limestone and tuff samples of the Upper Ordovician Zhaolaoyu Formation in the Fuping area of the southern Ordos Basin, including optical microscope identification, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), saturated isothermal remanent magnetization (SIRM) acquisition curve, three-axis isothermal thermal demagnetization test, κ-T curve test, hysteresis loop experiment, first-order reversal curve (FORC), and thermal demagnetization and hybrid (TD+AF) demagnetization. Results The results indicate that the main magnetic minerals in the limestone and tuff samples are magnetite, pyrrhotite and/or greigite, and some samples also contain a tiny quantity of haematite with impurities and goethite. Mineral particles possess single domains (SDs) as well as multiple domains (MDs) within their magnetic domains. Combining petrographic and demagnetization data, this paper suggests that the main magnetic minerals in the samples are likely secondary minerals associated with later fluid alteration (maturation and migration of organic matter). Conclusion The remanent magnetic signals conveyed by these rocks cannot be directly used to constrain the Early Palaeozoic palaeoposition of the NCB but may be used to constrain hydrocarbon migration and accumulation in the Lower Palaeozoic strata of the southern Ordos Basin.

Objective Machine learning has been widely applied in the fields of collapse, landslide and debris flow susceptibility analysis. The selection of nonhazard samples is a key issue in landslide susceptibility analysis. Traditional random sampling and manual labelling methods may involve randomness and subjectivity. Methods In view of the potential randomness and representativeness of noncollapse samples, this paper considered soil collapse susceptibility evaluation a positive-unlabelled (PU) learning problem and proposes a two-step convolutional neural network framework (ISpy-CNN) that combines an information value model and the Spy technique. First, 15 collapse-related factors were selected for modelling based on the geomorphological, geological, hydrological, and artificial environmental conditions of the study area. Low-information-value samples that were able to map the distribution structure of noncollapsing samples were screened by the information value model. Then, through the Spy technique and training the CNN model, negative samples with high confidence were identified from low-information-value samples that were classified as noncollapsed samples. Finally, based on the framework and traditional random sampling, we used support vector machine (SVM) and random forest (RF) models to compare and verify the reliability, prediction accuracy and data sensitivity of the proposed learning framework and other models. Results The results illustrate that the proposed ISpy-CNN method can improve the accuracy, F1 value, sensitivity and specificity on the validation set by 6.82%, 6.82%, 6.82%, 8.23%, respectively compared to random sampling and 2.86%, 2.89%, 2.86%, 2.31%, respectively compared to the traditional Spy technique. The prediction accuracy of step 2 in PU learning using the CNN model is higher than that of the RF and SVM models. The sample set screened by the ISpy-CNN framework exhibited greater stability, prediction accuracy and growth rate than those screened by the traditional Spy technique by adding the same number of training samples. Conclusion The ISpy-CNN framework proposed in this paper can better assist in the selection of nonhazard samples and real collapse spatial distribution maps, and the results of the framework are more consistent with the actual collapse distributions.

Coal has made important contributions to the industrialization process of human society, and has played a key supporting role in ensuring China’s energy security and stable economic development. Since the mid-19th century, the coal-based fuel of coal, kerosene, gas and coal electricity has gradually entered the era of large-scale use. However, the traditional use of coal produces high carbon emissions, which has become a major problem in energy transition. Facing the development of ecological civilization society, the clean and efficient use of coal is imminent, and the innovation of modern coal-based energy technology is imperative. This paper proposes the definition and connotation of modern coal-based energy technology system, which is defined as the production of low-carbon energy products such as coal-based gas, coal-based oil, coal-based hydrogen and coal-based electricity, and the in-situ absorption of carbon dioxide in mining areas to form a clean and low-carbon energy production system with carbon neutrality. Its technical connotation includes coal-based gas, coal-based oil, coal-based hydrogen, coal-based electricity and dynamic carbon neutrality in mining areas, with a total of 5 technical modules, 19 technical units and 61 key technologies. The modern coal-based energy technology system will play an important role of “one main body, three supports and one breakthrough” in the future new energy system. Coal-based electricity provides the main body of electricity system stability. Coal-based oil supports the China’s oil safety. Coal-based gas supports the China’s gas safety. Coal-based hydrogen plays a supporting role in the development of hydrogen energy in China. The major breakthrough is the dynamic carbon neutral technology of coal-based energy. The paper supposes that when the ratio of non-fossil energy and low-carbon coal-based energy is maintained in the range of 2.5−3.0, coal-based energy, oil and gas and wind, water, nuclear energy can be reasonably integrated to form a new quality energy system with strong complementarity, high reliability and low carbon emissions. Based on the major breakthrough and practical application of modern coal-based energy technology, it is predicted that China’s low-carbon coal-based energy production will reach 1.02 billion −1.46 billion tons of standard coal equivalent (tce) in 2060, equivalent to 18%−24% of the national energy demand, and carbon dioxide emissions will be controlled below 500 million tons. Compared with the current energy transformation planning path based on “de coal” planning, the share of coal in our energy system can increase from 10% to more than 20%, and carbon dioxide emissions will reduce by 50%. At that time, the modern coal-based energy system has great technological innovation significance for China’s energy security and carbon dioxide emission reduction, and helps China to become a country with independent energy supply.

During the coal mining process, the change in the floor stress state of coal seam will produce deformation and failure. The seam floor failure in different coal mining processes has a certain law. At present, the water disaster monitoring of coal seam floors based on the DC resistivity method mainly focuses on the resistivity response characteristics of floor deformation and damage. To investigate the temporal changes in the electrical properties of the coal seam floor during mining, this study employs the inter-hole DC perspective observation system and the time-lapse resistivity reflection coefficient method. Through numerical simulation and field tests, the study uncovers the temporal variation law of the resistivity of coal seam floor induced by mining activities. First, this paper compares the results of individual inversion and time-lapse resistivity change rates for a typical geoelectric model to validate the reliability of the inter-hole DC perspective time-lapse method. Next, considering the mining-induced damage to the coal seam floor, this paper analyzes the electrical response patterns and charac-teristics of the rise of confined water and the damage zone in the floor during the mining process. It also discusses the feasibility of using a time-lapse resistivity reflection coefficient to assess the depth of coal seam floor damage, offering a theoretical basis for field construction. Finally, , the on-site monitoring tests reveal the electrical change characteristics of coal seam floor during the coal mining process. The time-lapse resistivity reflection coefficient R is utilized to determine the damage depth of the rock layer of the working face floor, which is found to be 15 m. The study results demonstrate that the time-lapse characteristics of the resistivity of coal seam floor mining damage obtained by the inter-hole DC perspective method can mitigate the influence of formation factors and random noise in the monitoring data to a certain extent. Additionally, the time-lapse resistivity reflection coefficient can be utilized to determine the depth of coal seam floor failure. This method transforms the detection target from the single study of geological anomalies to the full life cycle dynamic monitoring of the floor damage of the working face in the process of coal mining and then realizes the detailed depiction of structural damage to the working surface floor.

Based on the green development trend and requirements of China’s coal industry, this paper analyzed the factors that coal mines consider in choosing filling mining methods and the constraints that affect the promotion of filling mining technology. According to the geographical distribution characteristics of different mining areas and the differences in filling demands, four types of priority principles of “protecting the ecological environment, protecting surface buildings, addressing coal gangue and solid waste, and improving economic efficiency” for coal mine filling mining were defined. The ecological mining goal of “building the whole process holographic intelligent ecological mine by adopting filling mining as a regulation tool to protect the ecological environment in coal mines” was put forward. Based on the finite deformation mechanical model of the roof in filling mining, the factors affecting the subsidence of target rocks in filling mining were expounded, and the supporting strength calculation and overburden deformation control equations under three filling engineering modes such as ecological environment protection, ground building protection and gangue treatment were established. In addition, the paper introduced the development status and direction of universal filling technology in coal mines in China, including solid filling of raw gangue waste, modified solid filling, gangue concrete filling, integrated mining-filling-charging, large amount of gangue filling, filling method in thin coal seam, filling method for regional protection, filling method in continuous mining roadway and other filling technologies that meet various needs of coal mines. The material preparation and transportation of different filling technologies, the characteristics of filling process and the adaptive filling equipment were described in detail. In order to realize the intelligent filling of coal mines, a comprehensive data perception system was established, which realized the intelligent process from unit to whole filling working face through spatial planning and filling effect judgment. The sensor network and artificial intelligence algorithm were combined to monitor and control the solid filling process of coal mine in real time, and improve the filling quality and filling efficiency. Coal mine filling mining will play a more important role in the long-term planning of China’s green mine construction. Strengthening the scientific and technological research of the whole process of coal mine production based on active filling, the construction of universal filling technology and process system, the development of new solid filling materials, and the research of intelligent filling mining, will help the filling mining technologies in China’s coal mines have a very broad prospect.

The MILD combustion is a combustion mode that occurs in a moderate or extremely low oxygen environment, combining the advantages of high combustion heat utilization and very low NOx emissions, and is considered by the international combustion field to be one of the cleaner combustion technologies with great potential for application. Since the relevant research began around 1990, the technology for achieving a MILD combustion of gas fuels has been relatively mature, while the research on the MILD combustion mechanism and implementation conditions of solid fuels such as coal powder and biomass is still relatively lacking. Based on the high momentum oxidizer jet, internal recirculation is achieved, eliminating the need for external high-temperature preheating to establish MILD combustion, greatly expanding the application range of MILD combustion. This paper provides an overview of the basic characteristics of MILD powder fuel combustion from the aspects of particle dispersion, heating, ignition, combustion, and pollutants. Due to the uneven dispersion and reaction of particles, the MILD combustion process of carbon-based solid fuels such as coal powder is more complex than that of gas fuels. High speed jet MILD combustion not only increases ignition delay but also expands ignition and reaction zones, requiring systematic research on the characteristics and mechanisms of each combustion stage. This paper introduces the research achievements in the theoretical design and equipment development of solid fuel MILD combustion. It is recommended to improve the existing coal-fired boiler burner, adjust the process parameters to match the MILD combustion mode, increase the residence time of coke particles to improve combustion efficiency, improve combustion stability, and suppress various pollutant emissions, including fine particulate matter, through high-precision numerical simulation. Based on the overall approach of interconnected energy systems, the coupling research between MILD combustion and various new combustion technologies should be promoted, especially strengthening the research on the co-combustion characteristics of coal powder, biomass and hydrogen, ammonia and other combustible gases, and assisting in energy transformation. Exploring the characteristics of turbulent two-phase flow, turbulent interphase heat transfer, and turbulent chemical coupling in the powder MILD combustion is crucial for deepening the understanding of powder MILD combustion. It involves multivariate analysis and high-precision simulation, which will be the focus and difficulty of future research.

The safe, green, efficient and low-carbon coal mining is the common goal of surface coal mines around the world. The development intensity and ecological carrying capacity of surface coal mine resources in China show the reverse development characteristics, and the vulnerable ecological environment areas in northwest China have become the main surface coal production areas, which makes surface coal mining and ecological environment protection become important scientific problems, ecological problems and development problems to be solved urgently. On the basis of the development situation, natural conditions and main influencing factors of surface coal mines, the connotation characteristics and overall structure of realizing the safe-green-efficiency-low-carbon mining of surface coal mines were explained. Aiming at the characteristics of the whole life cycle of pre-mining, mid-mining and post-mining of surface coal mines, in terms of four levels: safe mining technology, green mining technology, efficient mining technology and low-carbon mining technology, this paper puts forward eight key technologies including the time-limited slope control technology, the intelligent early warning decision-making technology, the new mode of transportation link, the ecological construction of mining area, the coordinated mining of adjacent mines, the intelligent mining design, the application of electric mining trucks and the ecological damage reduction at mining sources. The key work and direction of safe-green-high efficiency-low carbon cooperative mining in surface coal mines are clarified. In terms of the measures of safety-green-efficiency-low carbon co-development, regarding strengthening a top-level design, accelerating the distributed implementation, enhancing key researches, promoting personnel training, and improving standards and regulations, the paper proposes the target tasks to be accomplished in different stages in 2025, 2030 and 2035. In the new era, surface coal mines should firmly follow the development path of safe-green-high efficiency-low carbon, and realizes the high-quality development goal of surface coal mines.

Coal mining machine is the core equipment of completely automated working face, and the research and development of intelligent coal mining robot is crucial for achieving the intellectualization of fully mechanized working face. This paper comprehensively analyzes the current research status of sensing detection, position and attitude control, speed control, cutting trajectory planning, and tracking control in the coal mining machine roboticization process, and proposes five key technologies that must be solved in the development of intelligent shearer robots, including sensing and detection, pose control, velocity control, cutting trajectory planning and tracking control. Aiming at the problem of intelligent perception, this paper proposes the construction thought of a coal mining robot intelligent perception system, as well as the architecture of a coal mining robot intelligent per-ception system. The architecture of the intelligent perception system for coal mining robots is outlined, enabling a comprehensive sensing of running state, posture, environment, and so on, thereby ensuring the safe and reliable operation of intelligent coal mining robots. In terms of the position and attitude control problem of intelligent coal mining robots, the intelligent PID position and attitude control thought is proposed, along with an improved genetic algorithm-based PID pose control method, enabling precise pose control for the coal mining robot. As to the problem of velocity control, the thought of cutting load measurement based on the fusion of “force-electricity” heterogeneous data is proposed. Additionally, a neural network-based algorithm for cutting load measurement is presented, achieving an accurate load measurement. Furthermore, a traction and cutting speed adaptive control approach is proposed, including an artificial intelligence-based decision-making method for traction and cutting speed and a sliding mode control method for traction and cutting speed with disturbance rejection. This approach enables a precise and adaptive speed control for the coal mining robot. Regarding the problem of cutting trajectory planning and tracking control, the precise cutting trajectory planning thought is proposed, incorporating geological data and historical cutting data into a cutting trajectory planning model. The precise cutting trajectory tracking control thought is proposed, and an intelligent interpolation algorithm-based cutting trajectory tracking control method is given, achieving a high-precision trajectory planning and accurate tracking control for the coal mining robot. Considering the “position-attitude-velocity” collaborative control problem, the intelligent optimization idea of "position-attitude-velocity" collaborative control parameters is proposed, which utilizes an improved particle swarm optimization method based on multi-system constraints to optimize the coordinated control parameters, resulting in intelligent and efficient operation of the coal mining robot. The in-depth investigation of these five key technologies for intelligent coal mining robot provides some valuable insights for accelerating the development of high-performance, efficient, and reliable intelligent coal mining robot.

In view of the intelligentization of coal mine roadway excavation, this paper discusses the current development status of four major categories of intelligent fast excavation equipment, including continuous mining machine, excavation and anchor machine, full-section excavation system, and anchor excavation machine, analyzes the applicability of the four major categories of intelligent fast excavation equipment with the geological conditions, proposes some key technological issues for the realization of intelligent coal mine excavation which need to be resolved, and also explores the information transmission and intelligent analysis technology, intelligent perception technology, precise positioning and navigation technology, autonomous stereotyped directional cutting technology, remote and autonomous cutting control technology of road-header and multi-level and multi-process intelligent cooperative control technology, as they are the basis for the realization of intelligent roadway excavation. Based on the key technological issues needed to be solved in the mine roadway excavation under the complex geological conditions, the paper puts forward the design method of systematic analysis, modular design and optimal combination of functions, according to the functional requirements of the excavation operation and the requirements of the excavation process. A multi-level digital twin architecture of virtual control and virtual-reality combination is studied based on the multi-dimensional information reproduction of heading equipment, environment, and geological structure to realize the remote control of road-heading machine. A control method that integrates single-machine intelligence, system synergism, and synergism of underground intelligent control and surface remote monitoring is proposed. A new type of flexible advance support technology without repetitive crushing, multi-stage telescopic cutting technology of cutting section, and multi-rig parallel operation technology of intelligent anchoring unit have been developed, and a new type of combined unit for rapid roadway heading operation with a parallel operation of excavating, supporting, anchoring, transporting, and exploring processes has been also developed, and a flexible parallel operation technology of excavation robot, advance support robot, anchoring robot, and auxiliary transportation robot group has been proposed. A data-driven multi-machine, multi-process collaborative control behavior planning and decision-making method is proposed. In addition, it is proposed to construct a complete coal mine underground cross-system full-temporal-spatial information digital sensing system, build a data sensing intelligent monitoring platform with multi-parameter, multi-scale and full-temporal-spatial characteristics, that integrates the production state of underground site, spatial information of roadway, state of heading equipment, and risk information, etc., and realize a real-time communication between virtual system and actual tunneling system, so as to realize the intelligent and less-manned heading through data-driven planning and analysis.

The safety in the coal-producing mines in China is continuously improving, but coal and gas outburst accidents still occur. The prediction of coal and gas outbursts allows the scientific application of outburst prevention measures, which can ensure the safe coal mining to a certain extent. Machine learning is an interdisciplinary field involving probability theory, statistics, and computer science, which can explore the nonlinear relationship between outburst accidents and its associated indicators. The application of machine learning in coal and gas outburst prediction has received relatively widespread attention, and with the rapid progress of artificial intelligence and computer technology, it will play a greater role in the field of outburst prediction. Therefore, this paper provides a comprehensive review of the research on machine learning in coal and gas outburst prediction, analyzes the difficulties in outburst prediction and prospects its development direction. Firstly, the paper provides a brief overview of the research status on the hypothesis, occurrence mechanism, and prediction index selection of coal and gas outbursts. Then, it summarizes the research progress in the field of outburst prediction, including the application of support vector machines, neural networks, extreme learning machines, and ensemble learning algorithms. In addition, it also points out the existing problems in the current research, such as imbalanced samples, missing data indicators, and small sample sizes. Finally, the paper gives an outlook on the developments of coal and gas outburst prediction based on machine learning, including improving algorithm performance, optimizing feature engineering, and increasing sample size. With the continuous improvement of computer performance, more powerful models may be proposed, which can further improve the prediction accuracy of outburst accidents.

The fragile ecological environment in the western coal mining areas of China, compounded by intensive mining activities, has led to water and soil erosion, soil degradation, and damaged root systems. With a low plant water use efficiency, the ecological restoration becomes challenging, making the improvement of water use efficiency a key aspect in the ecological restoration or reconstruction of western mining areas. Soil water is a critical factor limiting the ecological restoration of arid and semi-arid coal mining areas, as it connects atmospheric water, surface water, groundwater, and vegetation growth, serving as an important carrier for water circulation and nutrient transport. Efficient and rational utilization of soil water is crucial to the success of ecological restoration. Therefore, investigating plant root water utilization strategies plays a significant role in the ecological restoration of western coal mining areas. This paper analyzes the main research methods of plant water use at home and abroad, compares the advantages and disadvantages of different methods, and reviews the corresponding research progress. In the damaged ecological environments of arid and semi-arid coal mining areas, the application of plant-microbe combined microbial remediation technology can improve plant water use efficiency and enhance plant water use strategies. At the same time, the microbial inoculation reduces the proportion of water absorption by plants from shallow soil layers, effectively increasing the absorption and utilization of water from deep soil layers by plants, thereby enhancing plant water use efficiency. This enables the inoculated plants to exhibit a higher ecological adaptability in the arid and semi-arid coal mining areas. This paper analyzes the current research progress and existing problems of plant water use in the western coal mining areas, discusses the improvement of water use strategies through microbial remediation in mining areas, and proposes the impact of different plant combinations on water use strategies and their research focuses in the ecological restoration of western arid coal mining areas. This lays a solid foundation for achieving green, sustainable, and high-quality development in the arid and semi-arid coal mining areas, and has important ecological application value.

This paper collected the data of death and loss of contact in Luding MS6.8 earthquake, quantitatively analyzed the characteristics of the number of deaths and loss of contacts over time, and compared with typical destructive earthquakes in recent 10 years. Combing the actual emergency rescue work, this paper sort out and summarized the main reasons, systematically analyzed the impact of geological disasters on personnel mortality and loss of connection rate, discussed the characteristics of earthquake disasters and disaster relief in mountainous areas. At the same time, we propose suggestions for the verification and submission capabilities of earthquake disaster information and the improvement of personnel search and rescue capabilities in complex mountainous environments.

This paper establishes a microchannel model based on the pore scale distribution characteristics of natural cores from Daqing Oilfield. It considers the deformation and flow characteristics of the dispersed and continuous phases in the heterogeneous system， builds a flow model by the phase field method， and solves it by the finite element method. The paper also simulates the generation of dispersed phase particles in the microchannel， realizes particle sorting， and studies the effect of the matching coefficient and pore-throat ratio on the plugging performance of particles in the microscopic pore-throat structure. The results show that when the particles are elastically plugged in the microscopic pore-throat structure， the pressure at the entrance of the pore throat changes periodically with the migration of the particles through the pore throat. The optimal matching coefficient between the particles and the pore throat is ［1.0， 1.4）. In this interval， the particles can be temporarily plugged at the entrance of the pore throat and recover their original shape after deformation and migration through the pore throat. When the pore diameter is the same， a larger matching coefficient and pore-throat ratio indicate greater pressure of particles through the pore throat， and larger particle size reflects a smaller critical value of particles through the pore throat.

Objective Landslide dams are a geological body of key concern for engineering construction in alpine canyon areas. This paper takes the Dalongchi landslide dam in the South Tianshan Mountains as the research object to explore the origin and evolution process of the landslide dam in alpine canyon areas of the South Tianshan Mountains. Methods Based on satellite remote sensing images, regional data, field investigation, and geological drilling data in the Dalongchi region, combined with theoretical calculations and finite element discrete element simulations, this paper systematically delved into the deposit characteristics and the formation and evolution process of the Dalongchi damming body. Results The results show that (1) Many landslide scratches and grooves can be seen on the steep mountain surface on the North side of the Dalongchi damming body, of which the packing structure has obvious inverse grading features and a jigsaw structure, and it is speculated that the formation may be caused by the accumulation of the high-speed and long-distance ancient landslide of Dalongchi. (2) By conducting the recurrence of the northern original surface of the Dalongchi landslide and theoretical calculation and numerical simulation on its kinematic characteristics, the results were then induced that there was a high-speed and long-distance landslide on the north side of the mountain that led to the formation of the damming body of Dalongchi. (3) The formation and evolutionary phases of the Dalongchi damming body can be divided into the embryonic stage of ancient landslides, the river-blocking forming stage of the damming stage by ancient landslides, and the overlapping stage of ancient damming bodies. Conclusion The study of the formation and evolution of the Dalongchi dammingbody can provide a reference for the subsequent genetic analysis of similar studies in the southern Tianshan region.

Landslide disasters occur frequently in Fujian Province, and early warning of landslide disasters on a regional scale is an important means of effective disaster prevention and mitigation. Due to the complex mechanism of landslide disasters, the traditional regional landslide early warning methods have such problems as insufficient accuracy. Deep learning mainly refers to the technology of feature extraction, abstraction, representation and learning by constructing the neural network model, which is a kind of machine learning. As a classical deep learning algorithm, convolutional neural network has more powerful classification and representation ability than traditional machine learning. Taking Fujian Province as the research area, this paper introduces the convolution neural network into the field of landslide disaster early warning and constructs a regional landslide early warning model of Fujian Province. The process is as follows: (1) The SMOTE optimization algorithm is used to optimize the sample database of landslide disasters in Fujian Province from 2010 to 2018, enlarging the number of positive samples and expanding the proportion of positive and negative samples from 1∶3.4 to 1∶2, and the total number of samples reaches 18040. (2) Construct a convolution neural network model structure, which includes an input layer, two convolution layers, two maximum pooling layers, a full connection layer and an output layer. (3) Use the convolution neural network to train the optimized samples (80% of the samples from 2010 to 2018 as the training set), and use the Bayesian optimization algorithm to optimize the model parameters to obtain the regional landslide early warning model of Fujian Province. (4) The model is tested with 20% of the samples from 2010 to 2018 as the test set, and the confusion matrix and ROC curve are used to test the model. The results show that the accuracy of the model ranges from 0.96 to 0.97, the AUC value is 0.977, indicating that the model accuracy and generalization ability are good. (5) The actual situation of the landslide disaster in the flood season of 2019 is taken as a positive sample, negative samples are collected through the method of time-space sampling, and the 2019 regional landslide sample verification set (603 samples) is constructed. The model is further verified by using the confusion matrix and ROC curve. The results show that the accuracy of the model ranges from 0.75 to 0.85, and the AUC value is 0.852. Although only the actual landslide samples in the flood season of 2019 is used for verification, good results is also achieved. In this paper, the convolution neural network algorithm is applied to the regional landslide early warning, which provides a new way to establish the regional landslide early warning model. The preliminary verification shows that the model is effective and will be further applied and verified in Fujian Province in the future.

The eastern margin of the Tibetan Plateau is composed of multiple secondary tectonic units which constitute typical “multi-level extrusion-rotation active tectonic system”. It is the tectonic transformation belt that regulates the eastward extrusion of plateau blocks, and contains high-density active faults. This area is characterized by frequent and high intensity strong earthquakes and complex geological and geomorphological features. Therefore, this region is one of the areas in China where the problem of earthquake disaster is particularly significant. In recent years, with the research deepening of the national earthquake disaster risk survey, active fault detection of urban，seismic experimental site construction, seismic safety evaluation of engineering sites, identification of active faults and evaluation of crustal stability in major projects sites and urban areas，and the wide application of high-precision remote sensing, tectonic geomorphology, paleoseismic and Quaternary chronology methods. The investigation of seismogenic structures around the eastern margin of the Tibetan Plateau and its adjacent areas has been significantly improved. In order to timely exchange the latest study results in this field support regional earthquake prevention and disaster reduction and geological safety evaluation of important projects sites and infrastructure construction, the journal editorial department of Progress in Earthquake Science organized the special topic “The strong earthquakes and seismogenic structures in eastern margin of Tibetan Plateau and adjacent areas”. More than 20 representative academic papers such as active faults and earthquakes, Jishishan earthquake in Gansu Province，and research reviews in related fields have been collected. In this issue, 10 papers are selected in the special topic I “The strong earthquakes and seismogenic structures in eastern margin of Tibetan Plateau and adjacent areas”. It is hoped that these newly study results may improve the understanding of characteristics of strong earthquake activity and seismogenic structural mechanism in the region, and provide scientific basis for regional strong earthquake risk analysis and effective prevention of strong earthquake disaster risk.

Daqingshan piedmont fault is located in the northern margin of Hetao basin and has been active strongly since the Late Quaternary. Previous researchers had conducted extensive research on the characteristics of paleoseismic in this area, but limited by the dating techniques and the fact that there were fewer data available on the same fault profile that can effectively constrain paleoseismic events, and fewer profiles that can reveal more paleoseismic events. This paper explores the excavation of an paleoseismic trench on the east side of Lianhuashan in the western section of Tuyouqi of the Daqingshan piedmont fault, using Optically Stimulated Luminescence data, and combineing with the age data of previous exploration trenches. By using the fault successive limit method, it is found that the western section of the Tuyouqi fault has experienced five paleoseismic events approximately 11500 years ago, with an average recurrence interval of 2260 years. The five paleoseismic events in this section of the fault, from new to old, are 1.28 to 1.42 ka, 3.41 to 3.60 ka, 4.08 to 5.01 ka, 8.26 to 9.32 ka, and 10.70 to 11.30 ka, respectively. The latest event of activity should be the earthquake of 849 AD. Meanwhile, the trench exploration revealed that the fault in this section exhibits a normal fault nature, with an inclination angle between 58 and 77 degrees. According to empirical formula, the potential seismic capacity of the Baotou section, the western section of Tuyouqi, and the western section of Tuzuoqi are around MW6.8～7.1, MW6.8～7.1 and MW7.1～7.2, respectively. The magnitude obtained by the empirical formula in this paper is relatively small, and there may be cascade rupture. In the later stage, it is necessary to conduct a comprehensive evaluation of the risk of the western section of Daqingshan piedmont fault combined with other means.

The epicenter of the 2017 Qinghai Zeku MS4.9 earthquake was located near the SN-striking Riyueshan fault, while the focal mechanism solutions and the dominant arrangement of seismic sequence are inconsistent with the Riyueshan fault. In this paper, we have discovered EW- and NW-trending faults near the epicenter, by methods of remote sensing interpretation and field investigation. These faults are western terminal structures of Xiahe fault, in which the EW-trending faults are north-dipping and associated with kinematics including both left-lateral and vertical slip. Meanwhile, we use double differential positioning to relocate seismic sequences of Zeku MS4.9 earthquake. Results show that seismic arrangements consist of two segments striking NW and EW. The seismic profile crossing EW-striking segment indicates a north-dipping fault plane. Well consistence is found between Xiahe fault and seismic arrangements of Zeku MS4.9 earthquake, which leads us to the speculation that the seismogenic fault of Zeku earthquake is Xiahe fault. From a regional perspective, the Xiahe fault might be one strand of dissipating faults in the western end of the West Qinling fault, and the Zeku MS4.9 earthquake represents tectonic activity of the western end of the West Qinling fault. Besides，the northwestward turn of fault striking and reverse slipping of Xiahe fault might also be attributed to the right-lateral shearing effects of Riyueshan fault. Results of this paper highlight the significance of improving active fault traces, especially for the secondary or pre-existing faults in a tectonic active area.

Lacustrine sediments store a wealth of information and are often used to indicate climate change. Natural disasters such as earthquake, flood, landslide or collapse usually form characteristic disturbances in lacustrine sediments, which can be analyzed and identified using lake geology methods. This paper reviews the research progress of lacustrine sediments, systematically summarizes the characteristics of typical natural disasters in lacustrine sediments, and focuses on the identification methods of natural disaster events in lacustrine sediments. Among them, the comprehensive analysis method integrates various analysis methods for sedimentary identification of lake events at the present stage. ① Identify the endogenous and exogenous origin based on the relationship between sedimentary facies and event-induced deposits(EID)；② Recognize the most likely trigger based on the elimination of impossible triggers；③ Verify the correctness of the most likely trigger according to the existing identification criteria. This method integrates the advantages of typical mark analysis and exclusion method, and is the most effective analysis method at present. This paper also discusses the advantages, disadvantages and constraints of the study of lacustrine sediment disaster events. The continuity, sensitivity and high resolution of lacustrine sediments are conducive to the study of disaster events, but the establishment of sedimentary identification markers of typical natural disaster events in lakes is still the key to restricting the study of lake abnormal events in the future.

The North Mountain landslide in Lijie Town has been in a long-term creeping deformation state and has experienced multiple landslide and debris flow disasters. Monitoring the surface deformation of landslide to grasp the surface deformation pattern of disaster body is a reliable basis for realizing early warning prediction of geological disaster. In this paper, a machine learning model is introduced to predict the relevant data, and a long and short-term memory network is used to predict the landslide deformation by monitoring the displacement data of North Mountain in Lijie, and the prediction results are compared with the actual data and analyzed. In this paper, root mean square error , mean absolute error , coefficient of determination and explainable variance are used to evaluate the prediction results, among which the coefficient of determination and explainable variance reach 0.99. It shows that the long short-term memory network used in this paper achieves good prediction performance in the prediction of landslide deformation in the North Mountain of Lijie.

The Erzhuangke landslide is a typical landslide affected by the rainy season. Rainfall changes the seepage pattern with the pre-existing landslide, weakening matric suction and soil shear strength, leading to the formation of tension cracks internally. This triggers overall sliding and localized extensive deformations. Existing studies seldom considers the interaction between the seepage field and stress field of the Erzhuangke landslide. Therefore, based on the actual engineering geological disaster scenarios, supported by on-site monitoring data and terrain physical parameters, a geometric computational model is established, and hydraulic coupled numerical simulations are conducted. By investigating variations in saturation and pore pressure within the landslide, the paper explores the rainfall infiltration patterns. It examines the impact of rainfall intensity on landslide reactivation from the perspective of stress displacement. In addition, in order to validate the accuracy and feasibility of the method, selected measurement points from the landslide are matched with corresponding positions in the numerical model. Comparative analysis is performed on displacement, soil pressure, and saturation aspects, confirming that the numerical model effectively reflects the actual situation. Through coupling numerical simulations and the study of the reactivation mechanism of the old landslide under rainfall conditions, the paper interprets field data, analyzes the reactivation process, and provides theoretical foundations and technical guidance for subsequent engineering early warning and disaster mitigation works.

Objective 3D geological modelling is a kind of technology that converts multisource geological data into 3D geological models through computer. It reveals the spatial distribution relationship between various underground geological bodies, which helps geologists understand underground geological structures more intuitively, providing certain support for resource exploration, disaster prediction, engineering construction.However, complex geological environment, scarcity of effective geological data, large amount of calculation and other factors make the construction of large-scale complex geological bodies become an urgent problem to be solved in the development of 3D geological modelling. Methods To address these issue, this paper proposes a large range of complex geological body block modelling methods. Based on the model horizontal distribution scope of bounding box, large range of research area will be divided into several relatively smaller ones to perform modelling. At the same time, virtual borehole and stratum partition automatic tracking algorithm will be introduced for the block model at the bottom, top and middle part for the consistency of boundary constraints.At the same time, when modelling each block, the range of modelling data is extended to ensure that the strata between merged blocks can achieve smooth transition at the boundary of block. Results Each block of model is combined into a complete one with coherent and smooth stara so that a large range of complex three-dimensional geological body modelling can be realized. Conclusion Taking the shallow underground model of the Xiamen Maluan Bay New urban area as an example, this paper constructed corresponding geological model to test the modelling effect. The model is dissected and compared with the real borehole. The feasibility of proposed method is verified in terms of modelling efficiency, continuity and smoothness of strata connection.

The central and western coal resources have the highest degree of enrichment and superior development conditions in China. With the improvement of mining efficiency, the disturbance of high-intensity and large-mining-height mining mode to groundwater system also increases. In particular, the groundwater in the aquifer outside the disturbance range of the water-conducting fracture zone gradually participates in the mine water inflow process during the coal mining. Such mode leads to a series of problems such as large deviation of mine water inflow prediction, inaccurate evaluation of water inflow risk and unclear water hazard prevention measures, which brings great hidden risks to the current mine water hazard prevention and control. In this paper, a derivative mode of dynamic water inrush is summarized. With the coal mining, the evolution of groundwater system caused by overburden failure will induce new disaster sources, resulting in different forms of water inrush. Its connotation is to change the basis of defining the derivative dynamic water inrush model from the traditional static analysis before mining to the dynamic evaluation considering the change in the whole mining cycle. The derived dynamic water inrush model of the mine can be preliminarily divided into three categories, namely, “skylight leakage type”, “bed separation disaster type” and “channel permeability increase type”. This paper mainly discusses the derivative dynamic water inrush mode of “skylight leakage type”. Taking the Shanxi Yushen mining area, a shallow buried coal seam mining area with high strength and large mining height, as an example, the disaster-pregnant conditions of “skylight supply type” derivative disasters are discussed in depth. Through supplementary analysis of water-richness and hydraulic connection strength of indirect water-filled aquifer, the comprehensive evaluation of water inrush risk in roof aquifer is achieved, and the evaluation method system of disaster derivative model is put forward. Through the transformation of mining mode, the active prevention and control system is constructed. A passive prevention and control system is constructed by multi-objective advance drainage before mining and local grouting after mining. By further refining the mine water inrush disaster model, optimizing the evaluation system and establishing comprehensive prevention and control technology, it provides a scientific basis for the protection of groundwater resources and safe low-carbon mining in ecologically fragile areas.

In order to improve the modern management level of unattended seismic monitoring stations in cities and counties, standardize the management of observation logs in stations, and improve the display of seismic monitoring work in cities and counties, Jiaxing Seismic Survey and Prevention Center actively explored the implementation of digital management of seismic monitoring stations through the development of the “Digital Observation Log Project of Seismic Monitoring Stations”. This paper mainly introduces the basic ideas and technical approaches of the research and development of the project, and briefly describes the main functions of the system. The implementation of the project can effectively solve the drawbacks of the traditional paper-based observation logs of seismic monitoring stations, and realize the digital management of the basic information of seismic monitoring stations and daily operation and maintenance. The project also builds the QR code for station information, effectively giving full play to the role of city and county monitoring stations in science popularization and publicity in earthquake prevention and disaster reduction, emergency response, disaster prevention culture and other aspects, and expanding the social service function of stations.

Objective With the development of drilling technology for deep strata, the study of the dynamic characteristics and parametric response law of drill bits and deep complex strata during drilling has become a key and difficult point in research. Methods In this paper, a combination of numerical simulation and response surface analysis was used to study the dynamic characteristics of PDC bits and typical complex strata in the drilling process, and parametric analysis was carried out. In this paper, soft-hard-staggered strata with dip angles as a typical complex formation were studied, the dynamic damage finite element simulation model between the PDC drill bit and the soft-hard-staggered strata with the full real size was established based on Abaqus, and the dynamic characteristics of the drill bit subjected to the reaction force of the strata during drilling were derived. Numerical simulation experiments were also conducted by orthogonal tests to investigate the dynamic characteristics of the PDC bit under different formation parameters and drilling parameters. Results The single factor analysis and response surface analysis were used to model and identify the relationship between drilling parameters and stratigraphic parameters and the reaction force on the drill bit by the stratum and to obtain the changing trend and regression model of the reaction force on the drill bit by the stratum under multiple parameters. The results showed that the higher the inclination angle of soft-hard-staggered strata, the higher the average value and peak impact value of the bit subjected to the stratigraphic reaction force. The larger the ratio of softness to the hardness of the strata is, the larger the average and peak reaction forces on the drill bit. Within a certain range, increasing the rotational speed will reduce the impact of the reaction force on the drill bit. Conclusion The research results provide a basis for predicting the bit reaction force during drilling in deep and complex formations and guide the control of the drilling trajectory in deep and complex formations, which is of great significance for deep geological drilling.

Objective Recently, the seismic damage of an actual bridge structure in a frozen soil area has shown that the presence of frozen soil will increase the lateral stiffness of the bridge foundation, which may cause more serious seismic damage to the bridge structure, but there is a lack of research on the frozen soil-pile interaction effect of frozen soil bridge structures under seismic loadings and the corresponding seismic responses. Methods The present paper proposed efficient nonlinear numerical models to consider the effect of the frozen soil-pile interaction on the seismic responses of structures. First, the relationship between the depth of frozen soil and surface temperature was constructed. Then, the p-y spring modelling approach was presented to simulate the seismic behavior of frozen soil. Several as-recorded ground motions were selected as the seismic input. The seismic responses of piers and bearings of regular bridges with different depths of frozen soil under seismic loadings were investigated. Results The results show that the proposed efficient nonlinear numerical model can be adopted to model the seismic behavior of bridges considering frozen soil. And the proposed p-y curves for frozen soil can accurately predict the p-y relationship from the existing tests. When the PGA is relatively small, the pier curvature increases slightly; by contrast, in the case of large PGA, frozen soil can significantly increase the curvature demands, which can make the pier enter into the inelastic behavior. When the depth of frozen soil is small (the temperature is -5℃), the bearing displacement increases significantly, which increases the probability of unseating under seismic loadings. Moreover, frozen soil can transfer to the adverse locations of structural systems under seismic loadings. Conclusion Therefore, the conclusions of this paper can provide the necessary theoretical basis and data support for studying the seismic performance and corresponding seismic design methods of frozen soil bridge structures in China, which is of great significance for promoting the development and engineering application of disaster prevention and mitigation of bridge engineering in frozen soil areas in China.