To address the problems of lagging fault response and insufficient accuracy in the traditional operation and maintenance mode of mine main hoists, a fault diagnosis model for mine main hoists based on BO-XGBoost was constructed, and the SHAP method was integrated to improve the model interpretability. The Bayesian Optimization (BO) algorithm was used to optimize the hyperparameters of the eXtreme Gradient Boosting (XGBoost) model. Based on the monitoring data from an experimental mine main hoist, the XGBoost model combined with the SHAP attribution analysis method was adopted to identify the key influencing factors and their action mechanisms. The results show that compared with the baseline XGBoost model, the BO-XGBoost model increases accuracy by 4.1%, reduces log loss by 41.9%, and shortens model training time by 80.1%. Compared with traditional decision tree, random forest and LightGBM algorithms, the BO-XGBoost model improves precision by 26.5%, 11.9% and 13.6%, respectively, demonstrating excellent test accuracy.Wire rope tension, lower sheave temperature and motor voltage are the three key causal factors of faults. Different fault types are affected by different factors; for instance, excessively high main shaft vibration, motor temperature and excessively low hoisting speed provide greater positive gain for main shaft fault prediction. Three-factor interaction analysis reveals the dominant role and influence patterns of various factors during wire rope faults. The probability of wire rope faults is mainly dominated by tension, motor current and hoisting speed. Excessively low tension or current significantly increases the risk, and rising hoisting speed further aggravates the fault probability, whereas lower sheave temperature has a weak influence.

To address the degraded detection performance of insulated glove wearing status caused by small hand regions in complex distribution network operation scenarios, a small-object-oriented detection algorithm, termed LN (LLC (Light-weight, Light, Coordinate) +NWD(Normalized Wasserstein Distance)), -YOLO is proposed.First, an LLC module was designed by integrating lightweight spatial pyramid pooling, a receptive field fusion attention mechanism, and coordinate convolution, thereby enhancing spatial perception through multi-scale feature aggregation and coordinate embedding.Subsequently, the Mixup data augmentation strategy was introduced to improve model robustness, and a NWD loss function is incorporated to optimize small-object detection.Finally, the effectiveness of LLC module was validated through controlled experiments to determine the optimal baseline, followed by ablation and comparative experiments on the proposed method.The results demonstrate that the proposed algorithm achieves a detection accuracy of 90.1%, representing a 2.0% improvement over the baseline, with a detection speed of 56 frames per second and a memory footprint of 15.7 MB, meeting the requirements for accuracy, real-time performance, and edge-device deployment in distribution network operation scenarios.

To enhance the importance of buildings and bridges as physical hazard-bearing bodies for hazardous chemical accidents in regional risk assessment. In this paper, a physical vulnerability assessment model was established, and a risk assessment method was proposed, which considered the hazardous chemical accident consequences and the physical vulnerability of hazard-bearing bodies. Firstly, areal locations of hazardous atmospheres (ALOHA) was used to simulate the possible risk footprints of hazards. Secondly, a physical vulnerability assessment model including exposure, sensitivity and adaptability was established. Density of structures and distance from the accident center supply were selected as the exposure dimension layer. The age of the structures, building height, seismic grade of building and bridge length were selected as sensitivity dimension layer. Emergency shelter area, road area and infrastructure maintenance funds were selected as the adaptability index layer, and the driving force factors of physical hazard-bearing body vulnerability were analyzed through the geographical detector. Finally, arc geographic information system (ArcGIS) was used to superimpose the accident consequence map and the physical vulnerability map to generate a comprehensive risk map to realize the comprehensive risk visualization of hazard-bearing body. This method was applied to the risk assessment of physical hazard-bearing bodies in a town of Tianjin. The results show that the density of structures and the distance from the accident center have the strongest explanatory power for the vulnerability of physical hazard-bearing bodies. The explanatory power of these two factors is 0.515 and 0.464, respectively. High-risk areas result from the spatial overlap of high hazard and high vulnerability. The comprehensive regional risk resulting from the combination of accident consequences and vulnerability exhibits significant spatial variation. On the accident consequence map, the eastern part of the town near the hazard release point is the most dangerous area. However, owing to the low vulnerability of disaster-bearing bodies in the surrounding area of the release point, it is classified as a medium-risk zone on the comprehensive risk map.

To prevent safety accidents such as bursting and leakage caused by wear in mine filling pipelines, CFD-DEM was employed to investigate the wear characteristics of filling slurries on pipelines. An L-shaped pipeline and a solid-liquid two-phase flow model were constructed to conduct numerical simulation experiments. Particle size (0.001-0.1 mm), slurry solid volume fraction (60%-80%), and slurry flow velocity (2-6 m/s) were used as variable parameters to explore the maximum wear rate of the pipeline under different conditions. The results indicate that both particle size and solid volume fraction exhibit a nonlinear relationship with the maximum wear rate. At a particle size of 0.1 mm, the maximum wear rate is 13.4 × 10^-5 kg/m². There is a critical solid volume fraction of 70%, at which the maximum wear rate was 7.15 × 10^-5 kg/m²; beyond this value, the wear rate tended to stabilize. The slurry flow velocity shows a linear relationship with the maximum wear rate; at a flow velocity of 7 m/s, the maximum wear rate is 8.25 × 10^-6 kg/m². The influence of each parameter on pipeline wear was ranked as follows: particle size > solid volume fraction > slurry flow velocity. The interaction between particle size and solid volume fraction has the most significant impact, followed by the interaction between solid volume fraction and slurry flow velocity, while the interaction between particle size and slurry flow velocity had the least effect.

Focusing on the path planning problem for the resolution of high-risk head-on flight conflicts, a UAV resolution path model based on minimum energy consumption was proposed. Multiple factors, such as paths and turns, obstacles, and safety separation, were comprehensively considered in this model. In the model solution, an improved SSA with multi-strategy integration was proposed by improving the chaotic mapping, the golden sine and the follower position update strategy. Its effectiveness was demonstrated by comparing it against 3 other mainstream swarm-intelligence algorithms on 8 standard benchmark functions. For the issue of flight conflict resolution, multi-aircraft conflict scenarios and reduced conflict scenarios were constructed, and 4 algorithms were applied for multiple trials. The comparison was made from two aspects: convergence performance and running time. Simulation results show that, in 4-UAV head-on conflicts scenario, a fitness of 8.86 with a runtime of 4.06 s are achieved by the improved algorithm, while a fitness of 1.26 and a runtime of 3.03 s are obtained in the 3-UAV induced-conflict scenario. All results are optimal, indicating that reasonable resolution paths for head-on conflicts among multiple UAVs can be rapidly provided by the proposed approach. When dealing with complex conflict problems, both computational efficiency and accuracy are taken into account. The new algorithm can quickly plan paths for the resolution of multi-machine head on flight conflicts.

To optimize the aerogel structure and reduce the effective thermal conductivity of the aerogel, the force field, atomic model, heating and cooling calculation modules were added to large-scale atomic/molecular parallel simulator(LAMMPS) to accurately simulate the adsorption of water molecules by silica aerogels and heat transfer processes. The results show that the adsorption capacity of silica aerogels to water molecules increases as the water content increases, showing a significant rise followed by an equilibrium state. With the increase of temperature, the thermal movement of water molecules intensifies, and the adsorption capacity of silica aerogels to water molecules decreases. However, the free water molecular weight increases. As the pressure increases, the collision frequency of water molecules and silica aerogels increases, resulting in an increase in adsorption capacity. When the water content increases and the temperature decreases, the mutual squeezing among water molecules promotes more water molecules to penetrate into the interior of silica aerogels, meanwhile, the thermal motion of water molecules slows down, which is not conducive to their escape from the aerogels pores, resulting in an increase in the number density of the silica aerogels system. Silica aerogels form water films by adsorbing water molecules, and the water films constitute "water bridges". With the increase of water content, the connectivity among "water bridges" is enhanced, and the contact area increases, leading to an increase in effective thermal conductivity of silica aerogels and significant degradation of thermal insulation.

To address the issues of low accuracy and weak robustness in existing detection algorithms due to insufficient lighting, scale differences among personnel, and frequent obstruction by equipment in coal mine environments, as well as the challenges posed by high parameter and computational requirements of some models, which make them difficult to adapt to edge devices underground, an improved YOLOv8n model was proposed to optimize personnel detection tasks in complex mine environments. An enhanced SPDs-Conv module was introduced to enhance the extraction of small target features and improve the recognition accuracy of low-pixel personnel in distant views. Cross stage partial feature fusion + selective kernel attention (C2f_SKAttention) module was designed to strengthen the model's focus on targets of different scales and cope with the scale differences of underground personnel. A dynamic detection head was constructed to adapt to the diversity and complexity of targets, and to improve robustness to occlusion and other scenarios. The WIoU loss function was improved to increase the bounding box localization accuracy and reduce the localization deviation caused by low illumination. The results show that the proposed improved YOLOv8n model achieves an mean average precision (mAP) @0.5 of 83.5% and an mAP@0.5:0.95 of 39.0% on the mine personnel detection dataset. Compared with the original YOLOv8n, the P is improved by 8.5%, the R by 11.9%, the mAP@0.5 by 4.7%, and the mAP@0.5:0.95 by 3.3%. The number of parameters only increases from 3.1M to 3.2M, and the Giga Floating-point operations per second (GFLOPS) rises from 14.0G to 14.4G. The proposed model maintains a lightweight structure while improving detection accuracy and robustness. It effectively alleviates missed detection of small underground targets, insufficient multi-scale adaptation and weak anti-interference capability in complex environments, making it suitable for the limited computing power of underground edge equipment.

To address the issues of high water consumption and the limited dust suppression range of traditional spray-based dust control technologies, a 1∶1 geometric model of the discharge port in an open-pit mine was established using numerical simulation software. Based on the Realizable k-ε turbulence model, the velocity distribution of induced airflow at the discharge port was investigated. According to the flow field characteristics, a swirling air curtain dust control method was proposed. This method utilizes induced circulation to encapsulate dust particles and employs a dynamic pressure barrier to suppress their diffusion, thereby forming a closed airflow barrier that prevents dust escape. By combining numerical simulations with schlieren observations, the velocity distribution of the induced airflow was analyzed, and the integrity of the swirling air curtain under varying jet angles and airflow velocities was compared. The results indicate that the formation of the swirling air curtain is jointly governed by the jet angle and airflow velocity. As both parameters increase, the vortex core structure becomes more distinct, and the degree of flow field closure is significantly enhanced. When the jet angle ranges from 10° to 20° and the airflow velocity from 15 to 25 m/s, a stable closed reverse-pressure swirling forms at the discharge port, where induced entrainment and circulation effects are most pronounced. When the jet angle is 15° and the airflow velocity is 20 m/s, the negative pressure core remains most stable, and the swirling structure is most fully developed. In contrast, excessively large jet angles or overly high airflow velocities may lead to increased turbulent dissipation and vortex instability, resulting in the breakdown of the air curtain structure. Schlieren observation further confirm that the swirling structure is most complete under the condition of a 15° jet angle and 20 m/s airflow velocity, thereby verifying the reliability and effectiveness of the proposed swirling air curtain dust control method.

To study the influence of initial temperature on the combustion behavior of pool fires, pool fire tests at different initial temperatures (5, 10, 20, 40, 60 and 80 ℃ ) were conducted using a self-built initial temperature controlled pool fire test platform. The characteristics of variations in combustion process, mass loss rate, flame height, and plume temperature were analyzed. The results show that when the initial temperature ranges from 5 to 60 ℃, the combustion process of oil pool fire is divided into three stages: growth, steady and decay. When the initial temperature increases to 80 ℃, the combustion process is divided into five stages: growth, steady, boiling transition, boiling and decay. The mass loss rate, flame height and plume temperature are all positively correlated with the initial temperature. When the initial temperature increases from 5 ℃ to 80 ℃, the mass loss rate, flame height and plume temperature increased by 12.13 g/(s·m²), 170.4 mm, and 130 ℃, respectively. The mass loss rate decreases nonlinearly with the temperature difference between the boiling point of n-heptane and the initial temperature. The ratio of flame height to pool diameter follows a power-law function of the ratio between the initial temperature and the boiling point of n-heptane point.

With the global transition of civil aviation navigation systems from magnetic north to true north reference, a dynamic risk assessment model integrating STPA and FBN was proposed to quantify, identify, and effectively control systemic risks induced by the navigation reference transition. A four-level control structure-covering strategic, regional, organizational, and equipment layers-was established to identify seven categories of system-level hazards and twelve types of unsafe control actions. Expert uncertainty was quantified via fuzzy sets, and a Bayesian network (BN) was constructed using the Leaky Noisy-or Gate model. Furthermore, a dynamic Bayesian network (DBN) was developed to simulate risk evolution across five phases (t₀ to t₀+28 years). The results show that technological lag and insufficient policy coordination are the major risk drivers in the early stage (e.g., airspace conflict probability up to 0.852). However, through phased implementation of technology upgrades, policy alignment, and redundancy design, key risks can be reduced to below 0.01 by t₀+28. This study proposes an original strategy integrating the 'phased compliance-fund disbursement' policy linkage mechanism, aircraft service life-based technical iteration path, and the 'inertial navigation + low-orbit satellite' dual-redundancy artificial intelligence (AI) governance system, to systematically resolve policy delays, intergenerational equipment conflicts and operational risks in the true north transition.