In order to explore the dust deposition characteristics on the surface of photovoltaic(PV) modules. For the dust accumulation problem of ground-mounted photovoltaic, the deposition characteristics of dust particles with different particle sizes were investigated from two factors, namely, tilt angle and wind speed, by using CFD numerical simulation method. The results show that as the tilt angle of the PV module increases, the deposition rate of dust on the surface of the PV module gradually decreases, in addition, it is found that when the PV module is facing the wind, the rate of dust deposition increases with the increase of wind speed, and the maximum particle size of dust deposition will become larger with the increase of wind speed. At the same time, with the increase of particle size, the deposition of dust on the surface of the PV module is the first to increase and then decrease. The study is of great significance in solving the problem of dust accumulation in photovoltaic power plants.

Reliability analysis and allocation were conducted on the propulsion system of multi rotor electric vertical takeoff and landing (eVTOL) aircraft. Firstly, to solve the problem of insufficient accumulation of reliability historical data of multi-rotor eVTOL aircraft, a reliability analysis model was established by using fuzzy Bayesian network (FBN) to supplement the reliability prior data, and reliability posterior inference was carried out to assist the key link of the positioning system. Secondly, based on the FBN reliability analysis model of the system, an improved advisory group on reliability of electronic equipment(AGREE) reliability allocation method was proposed. Reliability distribution of eVTOL propulsion systems with different configurations was carried out. The results show that the FBN reliability analysis model supplements the propulsion system reliability data and can effectively identify the system weak links. The reliability allocation results of the improved AGREE allocation method meet the reliability requirements for eVTOL aircraft in SC-VTOL-01, while the reliability allocation results obtained by this method are more reasonable, reflecting the differences between different configurations, subsystems, and components.

With the increase of air cargo volume, cargo plans are frequently interrupted due to disruptions in cargo demand, so rescheduling flight schedules is the core issue for air cargo recovery. An air cargo recovery model based on spatio-temporal network method was proposed with the goal of maximizing the profits of airlines under the disturbance of temporary increase in demand. Aircraft routes, cargo routes and flights were reorganized in the model and the initial flight plan was preserved as much as possible by adding penalty factors. In order to verify the effectiveness of the model, the model was solved using CPLEX solver. The proposed spatio-temporal network-based air cargo recovery model was compared with the model in reference. The results show that the proposed model has significant advantages in computational efficiency and finding optimal values, and the advantages become more apparent with the increase of the case size. The sensitivity of the model's solution results to the time window width and aircraft carrying capacity was analyzed. The results show that the narrower the time window, the slower the solution speed, while as the time window width increases, the solution speed accelerates and tends to stabilize. As the carrying capacity of the aircraft gradually increases, the solving speed of the model becomes faster and tends to be stable.

Hyperspectral remote sensing widely uses unmanned aerial vehicles (UAV) as flight platforms for data collection, which has the advantages of flexibility and efficiency. However, due to UAV performance and environmental conditions, it is difficult for sensors to maintain a fixed shooting posture during the collection process, resulting in data misalignment, distortion, and deformation. While UAV positioning systems and inertial measurement devices provide real-time position and posture for hyperspectral cameras, achieving high accuracy often necessitates numerous ground control points for auxiliary geometric correction, which is time-consuming and labor-intensive. Therefore, it is necessary to study an efficient and time-saving data processing method to correct distortions in hyperspectral data acquisition. In order to efficiently and time-saving eliminate distortions in hyperspectral data during the acquisition process, an unmanned aerial vehicle (UAV) push scan hyperspectral camera data acquisition system was designed based on the principle of collinearity equations. The system integrates a high-precision inertial measurement system and synchronously collects LiDAR point cloud data in the measurement area. The high-precision terrain information contained in the LiDAR point cloud was used for geometric correction of hyperspectral data, and the influence of different density point cloud data on the geometric correction results was studied. Experiments have shown that using LiDAR point clouds improves accuracy by 67% compared to using average elevation geometric correction results. The use of LiDAR and hyperspectral cameras for synchronous acquisition has a significant effect on improving the accuracy of hyperspectral data.

The offshore environment is complex and volatile, and the combined wind and wave loads can generate large vibrations on the floating wind turbine platform and tower top, posing a serious threat to the structural safety of the wind turbine system. To cope with this challenge, a tuned mass damper (TMD) was installed in the nacelle of the barge floating wind turbine to form a hybrid mass damper (HMD) using active driving force. The H∞ algorithm was used for the drive force control. The effects of no control, passive control, and H∞ control were compared through simulation. The results show that the H∞ control can effectively reduce the longitudinal angle of the platform and the longitudinal displacement of the top of the tower, with obvious vibration suppression effects.

A skeleton-based architectural point cloud fusion method was explored to address the challenges of model incompleteness in real-world 3D architectural models. The process begins with reverse modeling of the architectural scene using 3D point clouds. The acquired reverse point cloud data was combined with the original architectural design data to generate a forward point cloud model. A method based on the rotational symmetry axis (ROSA) was then applied to extract skeleton lines from both the reverse and forward point cloud models. The fusion of the forward and reverse point cloud models was achieved by skeleton matching, resulting in a reconstructed 3D model with improved completeness. Experimental validation shows that this method significantly reduces areas of model incompleteness, providing new insights and methods for 3D modeling and reverse engineering in architectural reality capture.

In order to study the deformation problem of the top coal area during the mining process of the fully mechanized top coal caving face, taking the fully mechanized top coal caving face of the Dongxia coal mine project as the engineering background, based on the specific coal seam characteristics of the fully mechanized top coal caving face, the support type and the parameters of support strength of the fully mechanized top coal caving face were analyzed. At the same time, combined with on-site monitoring data, the rated working resistance of the hydraulic support meets the on-site requirements of the working face. The discrete element software simulation analysis method was used to numerically simulate the deformation and support of the top coal during the mining process of the fully mechanized caving face in Dongxia coal mine project, and its application effect was verified. As the working face continues to move forward, the overlying basic roof undergoes periodic collapse, with an average cycle of about 20 m in step distance. In addition, the support effect of hydraulic support on the fully mechanized top coal caving working face did not change significantly with the increase of the advancing length. According to on-site monitoring data and calculation results, it is known that the selected hydraulic support can meet the support requirements of the fully mechanized mining face in the project.

To comprehensively and deeply analyze the overall benefits of provincial-level construction of new type of power load management system, a study on the comprehensive evaluation system for such systems was conducted. Firstly, an evaluation index system that considers technical, social, environmental, and economic benefits was established. Secondly, the subjective weights of the comprehensive benefits were determined through an improved analytic hierarchy process. Given that the index system encompasses both qualitative and quantitative indicators, the objective weights were determined based on the concept of intuitionistic fuzzy numbers, and the comprehensive weights were determined through cooperative game theory. Finally, the concept of perpendicular distance was introduced to enhance the traditional technique for order preference by similarity to ideal solution (TOPSIS) method, thereby improving the accuracy of the evaluation results. By applying the proposed evaluation system to evaluate the construction of new power load management systems in different provinces, the results show that the studied system exhibits strong systematicity, scientificity, accuracy, and feasibility in the comprehensive and multidimensional benefit evaluation of the construction of new power load management systems.

To promote occupational health and prevent musculoskeletal disorders among occupational drivers, the current status of functional movement ability of professional drivers was evaluated through functional movement screen (FMS), and the effect of exercise intervention was further explored. A stratified convenience sampling method was utilized to select 145 occupational drivers as participants, with their functional movement abilities rigorously evaluated using the FMS. Subsequently, 20 female drivers underwent an exercise intervention, with their exercise load monitored throughout, followed by a post-intervention FMS assessment. SPSS 29.0 software was used to analyze the FMS results, gender differences, and the effects of the exercise intervention. The results show that the FMS total scores of occupational drivers are generally below 14 points. Among the individual tests, the active straight leg raise scores highest, while the in-line lunge scores lowest. Gender differences are found in the scores for deep squat, hurdle step, active straight leg raise, and trunk stability push-up movements (P<0.05). Post-intervention, the basic functional movements, lower limb flexibility, and trunk stability patterns of female drivers show significant improvement, with all differences being statistically significant (P<0.05). The exercise intervention load is generally classified as moderate-intensity aerobic exercise. It is concluded that the functional movement capacity of occupational drivers is generally inadequate, and moderate-intensity exercise intervention is an effective means to improve the functional movement capacity of female drivers and prevent musculoskeletal disorders.

According to the fault data of a certain type EMU traction system in China in 2022, the location and frequency distribution of key faulty equipment were analyzed, and the impact duration caused by various failure problems was counted. These two are combined as the spatio-temporal characteristics of EMU traction system faults. The distribution model was selected to compare the duration distribution characteristics of various faults, and the K-S test method was used to analyze the fitting effects. The results show that the fault influence time of pantograph, traction converter and roof high-voltage cable is the most suitable for the logistic distribution model fitting, while the lognormal distribution is most suitable for the traction transformer, main circuit breaker and traction motor. It is of great significance to predict the failure time of EMU traction system, point out the optimization direction of system equipment maintenance, and improve the efficiency of train operation and scheduling.