When a train set operates at high speeds, significant vibration and noise are generated in the outer door due to external airflow and road surface excitation, which directly impacts ride stability and train operation safety. To address the significant vibration of the thin-walled backplate structure of the outer door at the first five modal frequencies, particle damping was applied to mitigate vibration and noise. Firstly, a discrete element model of the particle damper for the outer door was established to analyze system energy consumption through simulations under various filler parameters. Based on these simulation results, an optimized design of the filler parameters was conducted, and experiments were performed to assess sound insulation with each filler material. The results show that the installation of particle dampers achieves a sound insulation improvement of 5.33 dB, significantly optimizing the radiated noise from the outer doors. These findings demonstrate the effectiveness of particle damping for vibration and noise reduction in the outer door of a moving train set.

With the continuous integration of urban Bridges into a variety of traffic forms, various traffic vehicles and pedestrians interfere with each other, affecting the safety and comfort of pedestrians. To research the pedestrian response on single-level rail-cum-road bridges, a pedestrian-road vehicle-train-bridge coupling vibration model was established. The acceleration difference between the bridge panel and pedestrian SMD model was researched, and the influence of trains and road vehicle passing the bridge in different ways on pedestrians was calculated. The results show that, compared with bridge panel, the amplitude of acceleration fluctuation of pedestrian SMD model is smaller, but the walking pedestrian model may experience abrupt and significant acceleration peaks. Each moving subsystem in the coupling model has a speed-sensitive interval, in which the pedestrian acceleration increases significantly. The further vehicles are away from the bridge center, the greater the acceleration of pedestrians become. When train and road vehicle pass the bridge simultaneously, the peak acceleration of pedestrian caused by them will be superimposed, and the peak acceleration caused by road vehicles increases significantly due to the train.

Road feeling simulation is one of the key technologies for the development of the steer-by-wire system. In order to improve the quality of the road feeling simulation, the road feeling torque of the steer-by-wire system was designed based on the principle of steering resisting torque generation of the traditional steering system and the method of calculating the dynamics model. In order to reduce the torque pulsation of the road feeling motor caused by uncertain system parameters and sensor noise, a vector control strategy for the road feeling motor based on the active disturbance rejection control algorithm was designed, and the control parameters in the active disturbance rejection control algorithm were optimized using the particle swarm optimization algorithm. Based on the steering wheel middle position maneuvering stability test and the steering-effort test, the road feeling simulation effect was verified. The results show that the active disturbance rejection control based on particle swarm optimization algorithm has strong adaptability, and can effectively realize the accurate simulation of road feeling. It can effectively reduce the burden on the driver. The relevant research can provide a reference for the design of the steer-by-wire.

To address the bottleneck issues in vehicle access efficiency for horizontal shifting mechanical parking garages, an access vehicle scheduling optimization model based on the PSO-OBL algorithm was proposed. The model aims to shorten vehicle access operation time and reduce user average waiting time by precisely controlling vehicle access strategies and time management. To enhance the optimization performance and convergence rate of the traditional particle swarm optimization algorithm, an innovative approach incorporating inter-particle collaboration and information exchange mechanisms was embedded into the algorithm framework, along with the integration of an opposition-based learning mechanism for efficient problem-solving. Experimental data indicates that, compared to the traditional particle swarm optimization algorithm, the PSO-OBL algorithm achieves significant improvements in customer average waiting time, average service time, average queue length, and average energy consumption. The findings of this study are expected to provide theoretical support and practical reference for optimizing access efficiency in horizontal shifting mechanical parking garages.

In order to scientifically assess the operational efficiency of airport surface movements, a departure flight taxi time prediction method considering runway and taxiway system configurations was proposed. Firstly, the definition of surface taxi time was provided, and an analysis of the historical operational data at the airport was conducted to identify more accurate factors influencing surface taxi-out time. Based on the conclusions drawn from correlation analysis, a random forest prediction model for departure flight surface taxi time was constructed. The method was illustrated using actual operational data from Shijiazhuang Zhengding Airport and Shenzhen Bao'an Airport, analyzing the characteristics of surface movement time under different runway system configurations. The results indicate that: Apart from taxi distance, the correlation results of factors influencing surface taxi-out time at airports with different runway and taxiway system configurations are generally consistent. When considering the same factors, the prediction of surface taxi time is better for single-runway airports compared to dual-runway airports. Surface taxi time at single-runway airports approaches unimpeded taxi time, while at dual-runway airports, there is a significant difference from unimpeded taxi time. The research findings are of significant importance for enhancing airport surface operation efficiency and achieving energy savings and emissions reduction.

In order to improve the trajectory tracking accuracy and stability of the aircraft in the traction process, taking the four-wheel steering aircraft traction system as the research object, the kinematics model of the aircraft traction system is established, and the four-wheel steering trajectory tracking control method of the tractor based on the model predictive control was proposed. Taking the double lane changing condition as the reference trajectory, the motion control simulation model of the aircraft traction system was built in MATLAB/Simulink, and the four-wheel steering trajectory tracking controller was established by combining the speed of the tractor and the angular distribution relationship of the four wheels. The controller was compared and analyzed with the traditional PID control to derive the superiority of the controller, and the tractor four-wheel steering and front-wheel steering trajectory tracking controllers were simulated and compared and analyzed at the speeds of 1.5 m/s, 3 m/s and 4 m/s, respectively. The designed controller was simulated and verified by changing the initial positional attitude of the aircraft traction system at a speed of 1.5 m/s. The results show that at three different speeds, the airplane lateral error, the heading angle error, and the tractor heading angle error under the four-wheel steering trajectory tracking control of the tractor are smaller than those under the front-wheel steering trajectory tracking control. In the case of initial deviation, the four-wheel steering trajectory tracking controller can enable the aircraft to complete the correction of the initial deviation in time, reduce the trajectory tracking error, and at the same time improve the stability of the aircraft's traction system in the driving process.

With the rapid development of China's civil aviation, the air traffic flow in terminal areas is experiencing a consistent and significant increase. The accurate forecast of short-term air traffic flow is of great significance for the efficient implementation of air traffic flow management. To enhance the accuracy of short-term air traffic flow forecast, a model combining EMD (empirical mode decomposition) and LSTM (long short-term memory) based on data differential processing was proposed. Firstly, the model performed empirical mode decomposition on short-term air traffic flow sequences. Secondly, to improve prediction accuracy, data difference was utilized to stabilize the time series. Finally, the processed sequences were input into the LSTM network model for prediction, and the final short-term traffic prediction value was obtained through data reconstruction. Experimental verification was conducted using the data from Zhengzhou Xinzheng International Airport. The results demonstrate that the model achieves a significant improvement in prediction accuracy, as indicated by the typical indexes RSME, MAE, and R², which are 0.29, 0.08, and 96.40%, respectively. This approach outperforms other methods and provides valuable reference for short-term air traffic flow prediction.

Yuehai is the largest wetland in Yinchuan of poor water quality during spring, with a significant contribution from agricultural non-point source pollution. In order to gain a deeper understanding of the distribution characteristics of nitrogen and phosphorus in the Yuehai Lake and its eutrophication status, water samples from 28 representative sites in Yuehai Lake and its outflow river were collected during the spring irrigation period of 2021.The distribution characteristics and regularities of TN (total nitrogen) and TP (total phosphorus), as well as different forms of nitrogen and phosphorus in Yuehai Lake were analyzed. The differences in nitrogen and phosphorus concentration between Yuehai Lake and its outflowing river were revealed. The results showed that during the spring irrigation period, the TN concentrations at 78% of the sampling points in Yuehai Lake was lower than the Class III surface water standard, and the TN concentration at 57% of the sampling points belonged to the heavily eutrophic type. During the spring irrigation period, the TP concentration at all sampling points was lower than Class III surface water standard, and the TP concentration at 70% of the sampling points belonged to the heavily eutrophic type. There were differences in the sources and transformation processes of different nitrogen fractions in the water of the Yuehai Lake. pH and TDS (total dissolved solids) affect the concentration of nitrogen and phosphorus in the water, and DO(dissolved oxygen) does not have a significant effect on the nitrogen and phosphorus forms in the water of the Yuehai Lake. The distribution characteristics of nitrogen and phosphorus in the outflow river of the Yuehai and the Yuehai water were different, and the differences in nitrogen concentration and non-orthophosphate phosphorus concentration between the Yuehai Lake and its outflow river were not significant in the direction of river and lake water flow (north-south direction). The nitrogen and phosphorus pollutants in the Yuehai converged into the Yellow River along with the rivers out of the Yuehai Lake, and the nitrogen and non-orthophosphate phosphorus in the Yuehai Lake might impact on the water of the Ningxia section of the Yellow River and increase the risk of pollution of the Yellow River, and the control of the nitrogen and non-orthophosphate phosphorus in the Yuehai Lake should be strengthened. This work provides a reference for continuously and accurately improving the water quality in the middle and upper reaches of the Yellow River Basin.

Bismuth ferrite has become an effective semiconductor photocatalyst for the degradation of various wastewaters due to its narrow band gap, high chemical stability, and good visible light response. Pure phase BiFeO₃ nanofibers were prepared by electrospinning method. The optimal degradation conditions for Congo Red were obtained through single factor experiments such as calcination temperature, PVP (polyvinyl pyrrolidone)concentration, collection distance, spinning voltage, and pushing speed. Four factors that significantly affect photocatalytic efficiency were selected for response surface analysis experiments with four factors and three levels. After optimization, the optimal PVP concentration was 12.17 wt%, collection distance was 14.07 cm, and spinning voltage was 12.03 kV The pushing speed is 0.74 μm/s, and under this condition, the efficiency of BiFeO₃ photocatalytic degradation of Congo red can reach 90.43%. The phase analysis and morphology characterization of bismuth ferrite nanofibers were carried out using X-ray diffraction, scanning electron microscopy, Raman spectroscopy, and Fourier transform infrared spectroscopy. The results show that the pure phase BFO nanofibers prepared by electrospinning has a rough surface and obvious particle sensation, presenting a one-dimensional rod-shaped structure with a size of about 300 nm. This nanorod-shaped structure has a larger specific surface area and more active sites, Can improve the photocatalytic degradation efficiency of BFO.

Manual grinding with hand-held tools generates a lot of dust, currently, it is common to use negative pressure trapping device to limit the dust in the confined space, and make the dusty airflow directed through the dust removal device to be purified to solve the problem of dust dissemination. In order to solve the problem of ineffective ventilation and protection facilities in an aluminum grinding workshop, which led to the uncontrolled spread of dust between operations, a structural design of a “U-shaped slit” dust collection device for the grinding process of small aluminum parts was proposed.Finite element simulation and analysis method was used to investigate the dust prevention and control effect of the device. The results show that: when the device on both sides of the slit width is 2 cm, the rear side of the slit width is 5 cm, the air volume is 3 600 m³/h, and the internal airflow channel structure is an asymmetric slanting closure structure, the control surface of the wind speed is more uniform, average wind speed of personnel breathing zone reaches 1.3 m/s, in the same time, the noise of the internal airflow channel is relatively small and the dust particle trapping effect is better. It is concluded that the size of the device's “U-shaped slit” and the internal airflow channel structure design can effectively capture the dust generated during the sanding process, reduce the concentration of dust in the workplace, and provide a reference for the protection of dust in the sanding place.