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Based on the elastic–plastic theory, the analytical formula of the second invariant J 2 of deviatoric stress at any point around the circular roadway under the non-uniform stress field is derived. The distribution law of J 2 of surrounding rock under the three-dimensional non-isobaric stress field is studied by theoretical analysis and numerical simulation. Combined with the butterfly failure theory of surrounding rock of roadway, the close relationship between the distribution pattern of J 2 and the distribution pattern of plastic zone is found, and the failure mechanism of surrounding rock is revealed. The results show that the distribution form of the second invariant J 2 of deviatoric stress is closely related to the distribution form of plastic zone. When the distribution of J 2 of surrounding rock shows ‘round’, ‘oval’ and ‘butterfly’, the plastic zone shows the corresponding consistent form. When the second invariant J 2 of deviatoric stress produces stress concentration, the surrounding rock of roadway will produce large-scale damage. When the stress concentration is high, it may lead to malignant expansion of surrounding rock of roadway. The distribution of the second invariant J 2 of deviatoric stress is directional. When the principal stress rotates over a certain angle, the second invariant J 2 of deviatoric stress rotates over the same angle as the plastic zone. Under the influence of superimposed mining, the second invariant deviatoric stress J 2 of the wind tunnel of Yangchangwan 160,206 working face presents butterfly distribution, and the stress butterfly leaves present a certain degree of rotation. Based on the failure mode of plastic zone, the corresponding optimization support scheme is proposed, and the engineering effect is good.

Because an open-pit mine is an open operating environment, mining and stripping equipment inevitably pollutes the environment to some extent during the operation process. Therefore, the current dust concentration monitoring methods and technologies are relatively simple, and the dust distribution characteristics and diffusion laws of each production link in open-pit mines are not clear. Taking the transportation link of the Anjialing open-pit mine as the research object, a set of integrated monitoring methods combining ground and space and fixed and mobile technology is proposed. First, aiming at the complex transportation system of an open-pit mine, a physical model of dump truck movement in an open pit mine was constructed. On the basis of the principle of gas‒solid two-phase flow, a starting model of dust particles under impact and a dynamic model of dust particles under wind pressure were constructed, and the dusting, movement and diffusion mechanisms of dust particles were defined. Second, in view of the missing data and noise caused by the stability of the acquisition system and the coverage of the mining area signal, a method of dust concentration prediction based on time series and sample data correction processing of background noise was proposed. To fully restore and characterize the characteristics of the induction and influence of mining trucks on dust particles under different environmental conditions, a simulation method based on fluid mechanics, which effectively reveals the characteristics of air flow field migration and dust diffusion during the driving of mining trucks, was . Finally, on the basis of field monitoring data and numerical simulation data, the law of dust diffusion and migration of mining trucks under different speed conditions was revealed, and the characteristics of dust diffusion and migration prediction models were constructed. The relative error of the model prediction accuracy was 1.2% ~ 10.6%. The mean square error in the z-axis direction was 13.8%, whereas in the x-axis direction, it was 52.0%. The research results provide data support and a theoretical basis for follow-up dust concentration prediction in open-pit mines and the formulation of dust control programs.

Ceiling beams at the top of tunnels are more common in actual projects. Under the influence of thermal buoyancy, the ceiling structure significantly affects the diffusion characteristics of fire smoke within the tunnel. This study performed several sets of model experiments and numerical simulations to investigate the impact of the height and spacing of ceiling beams on the diffusion of smoke in tunnel fires, which results show that the maximum temperature rise and temperature decay patterns of fire smoke follow exponential changes. The increased height of the ceiling beams and the reduced spacing correspond to higher maximum temperatures on the ceiling. Furthermore, as the height of the ceiling beams increases and the spacing decreases, the longitudinal attenuation of ceiling temperature accelerates within the tunnel. A predictive model for ceiling temperature rise and a dimensionless temperature attenuation model were developed to characterize this phenomenon. The relative error between the predicted results and experimental findings falls within ± 15%. This study broadens the application scope of fire smoke diffusion models, which can provide technical support for smoke prevention and exhaust design of tunnels with similar structures.

Focusing on the issues of severe mining pressure and discontinuous surface deformation caused by the large-scale mining of multiple coal seams, and taking into account the research background of Shigetai Coal Mine in Shendong Mining Area, this study adopts physical similarity simulation, theoretical analysis, and on-site verification methods to carry out research on rock migration, stress evolution, and overlying rock fracture mechanism at shallow burial depths and in multiple-coal-seam mining. The research results indicate that as the working face advances, the overlying rock layers break layer by layer, and the intact rock mass on the outer side of the main fracture forms an arched structure and expands outward, showing a pattern of layer-by-layer breaking of the overlying rock and slow settlement of the loose layer. The stress of the coal pillars on both sides in front of and behind the workplace shows an increasing trend followed by a decreasing trend before and after direct top fracture. The stress on the bottom plate of the goaf increases step by step with the collapse of the overlying rock layer, and its increment is similar to the gravity of the collapsed rock layer. When mining multiple coal seams, when the fissures in the overlying strata of the current coal seam penetrate to the upper coal seam, the stress in this coal seam suddenly increases, and the pressure relief effect of the upper coal seam is significant. Based on the above laws, three equilibrium structural models of overlying strata were established, and the maximum tensile stress and maximum shear stress yield strength criteria were used as stability criteria for overlying strata structures. The evolution mechanism of mining damage caused by layer-by-layer fracturing and the upward propagation of overlying strata was revealed. Finally, the analysis of the hydraulic support working resistance during the backfilling of the 31,305 working face in Shigetai Coal Mine confirmed the accuracy of the similarity simulation and theoretical model. The above research can provide support for key theoretical and technological research on underground mine safety production, aquifer protection, surface ecological restoration, and source loss reduction and control.

In the context of urban extreme weather events, the efficacy of the “emergency language” employed by governments and public institutions on social media in effectively reaching and guiding the public in a timely manner necessitates a quantifiable evaluation framework. An indicator system was constructed on the basis of Hovland’s persuasion theory. This system comprised five input characteristics (word count/structural clarity, first/second-person perspective, emotional appeal, evidence and framing, and media format) along with three output indicators (reposts, comments, and likes). A data envelopment analysis (DEA) model that is oriented towards output was employed, with disseminators being categorized into four distinct decision-making units: central mainstream media, other government media, local government media, and other media. It is imperative to note that the outputs were subjected to a process of normalization through the implementation of a scale factor. The data were sourced from the Weibo platform within the specified time window, which was from 10:00 on 24 July 2025, to 12:00 on 19 August 2025, with a sample size of 744. The findings revealed substantial disparities in technical efficiency across different disseminator types. A subset of local government media demonstrated a technical efficiency ≈ 1.00 yet low scale efficiency. Posts exhibiting clear structures, actionable points, and accompanying images or videos achieved higher cross-efficiency scores. It is therefore evident that the proposed DEA model provides a benchmark for maximizing dissemination effectiveness under given information characteristics. It is recommended that posting frequencies be maintained at consistent intervals during periods of heightened activity, that a template structure be adopted in accordance with the “fact–action–assistance channel” model, and that the proportion of rich media content be augmented.

We propose a trustworthy load prediction method for a cantilever roadheader robot without imputation. Specifically, we design a load-trustworthy-boosting (LTB) algorithm for coal and rock cutting loads that accounts for missing data in complex underground environments. We introduce a trustworthy decision tree that integrates mixed-integer programming (MIP) and Missing Incorporated in Attributes (MIA) as the base predictor, which can handle missing data, thereby accelerating load prediction and improving prediction accuracy. Furthermore, we utilize boosting techniques to enhance the prediction performance of the base predictor by incorporating cutting safety–trust constraints during the prediction process. We derive the convergence of the algorithm theoretically and verify the accuracy and reliability of the algorithm through experiments. The experimental results show that the proposed algorithm is superior to state-of-the-art load prediction algorithms both without and with missing data considered. This method can provide a reliable decision-making basis for underground unmanned intelligent excavation.

Steeply inclined coal seams, characterized by their significant inclination angles and complex storage conditions, are globally recognized as challenging seams to mine. An orthogonal test was conducted to study the influence of four key factors, including burial depth, inclination angle, lateral pressure coefficient, and maximum horizontal principal stress direction angle, on the force on the top slab of the sharply inclined extra-thick coal seam. The research findings indicate the following: The normal stress in the hollow area above the working face increases with greater burial depth, and the normal stress in the mining hollow area above the working face increases with an increase in the lateral pressure coefficient. Within the range of 4 m from the top edge of the seam, the normal stress distribution is approximately linear, and the influence of each factor on the average value of normal stress is in the following order: inclination angle > depth of burial > angle between the maximum horizontal principal stress and the strike angle of the seam > lateral pressure coefficient; outside the range of 4 m from the top edge of the seam, the distribution of normal stress is approximately linear, and the influence of each factor on the average value of normal stress is in the following order: angle between the maximum horizontal principal stress and the strike of the formation > inclination angle > depth of burial > lateral pressure coefficient.

Potential faults are common sensitive geological bodies that affect the safe mining of underground mines, often leading to major accidents such as rock instability and rockburst during mining. The failure mechanism of faults has been widely studied. However, due to the spatiotemporal specificity of fault occurrence, there are few theoretical and mathematical methods suitable for effective analysis in mine safety risk management. This study aims to introduce fractal theory to characterize the spatiotemporal activity fractal characteristics of induced faults intersecting the mining site and roadway during the mining process of the Ashele copper mine in China. Using microseismic systems and fractal theory, a spatiotemporal fractal model of the fault slip process is constructed, and a fractal analysis method is proposed. The fractal dimension value is calculated based on the spatiotemporal parameters of different segments and stages. The fractal dimension is used to characterize and analyze the evolution of the fault. The physical formation process of potential faults and the relationship between fractal dimension values and multiple parameters, including spatial clustering, regional distribution characteristics, and energy-release characteristics, were analyzed based on the division of events into different time stages. Discovering fractal dimension’s temporal and spatial–temporal characteristics can provide technical references for mine disaster prevention.

The early warning of disasters such as ground pressure in deep hard rock mines has long constrained the safe and efficient development of mining activities. Based on fractal theory and fractal dimension interpretation, this study constructs a microseismic monitoring system for mining areas, extracting key elements, particularly time and energy elements. Using the box-counting method of fractal theory, the study investigates the fractal dimensions of microseismic time–energy elements, data interpretation, and disaster source early warning. Through parameter analysis, events related to local potential failure are identified and extracted, and disaster characteristics are revealed based on microseismic activity. A time–energy fractal dimension-based analysis method is developed for preliminary fractal analysis and prediction of regional damage. A time–energy-centered early warning model is constructed, narrowing the prediction range to a scale of 10 m. Based on the fractal interpretation of time–energy data, the prediction and early warning of rock mass failure in mining areas are achieved, with the reliability of nested energy warnings ranging between 91.7% and 96.2%. A comprehensive evaluation criterion for fractal dimension values is established, enabling accurate delineation of warning zones and providing scientific decision-making support for mine safety promotion.