In order to prevent the issue of transmission efficiency decline or even failure in universal joint caused by wear，the wear amount was calculated based on the Archard model and Hertz contact theory.the functional relationship between the variation amplitude of the output angular velocity and the wear amount was given by using dynamic simulations，and a reliability and sensitivity calculation model was established.The results show that greater wear leads to greater fluctuation of the output angular velocity，with a significant increase in fluctuations once the wear amount exceeds a certain threshold.As the wear amount increases，reliability gradually decreases，and the sensitivity of reliability to each random variable is negative，with the parameter K H having the highest sensitivity.Therefore，while regularly monitoring the wear amount and the variation amplitude of output angular velocity，appropriate process measures should be taken to improve material hardness and use high-quality lubricants to reduce the mean and dispersion of K H.
In order to investigate the drag reduction characteristics of groove structure，triangular and trapezoidal grooves with different dimensions were selected and simulation comparison on the drag reduction characteristics of flat models with two-dimensional transverse，three-dimensional transverse and three-dimensional longitudinal groove arrangements were carried out. The results show that the groove structure can generate low-speed fluid at the bottom of the groove. The low-speed fluid in the transverse groove can act as a rolling bearing. The drag reduction mechanism of the longitudinal groove can be explained from the perspective of protrusion height theory. The low-speed fluid in the grooves reduces the near-wall velocity gradient，thereby reducing friction drag. The groove structure can effectively reduce the turbulent kinetic energy and shear stress，leading to a reduction in viscous drag. The drag reduction effects of the two-dimensional transverse and the three-dimensional transverse groove model is similar，whereas longitudinal grooves exhibit a higher drag reduction rate than transverse grooves. Moreover，trapezoidal grooves achieve a higher drag reduction rate than triangular grooves. The optimal groove dimensions are a width of 0.1mm and a depth of 0.1mm，yielding a maximum drag reduction rate of 18.57%.
In order to study the impact of the Reynold number on the performance of wind tunnel heat exchangers，the CFD numerical simulation method was employed to analyze a conventional finned-type heat exchanger in a wind tunnel. Firstly，a three-dimensional geometric model of the finned-type heat exchanger was created through NX12.0，and then the mesh was generated through Ansys-Meshing. Numerical simulations were carried out using Fluent 2021R1. The numerical simulation mainly focused on the impact of the incoming flow Reynolds number on the heat transfer performance and resistance performance of the heat exchanger. The calculations revealed that corresponding to 2mm，4mm，and 6mm，the Reynolds numbers are 676.79，1 353.59，and 2 030.39 respectively. As the Reynolds number increases，the pressure drops and temperature difference between the inlet and outlet of the heat exchanger decreases，and the comprehensive heat transfer performance increases by 72.61% and 28.28% respectively. However，the improvement effect tends to be flat. Under identical structural parameters，as the inlet wind velocity increases，the corresponding Reynolds numbers are 1 355.09，2 710.18，4 065.27，5 420.354，and 6 775.44 respectively. As the Reynolds number increases，the heat transfer factor decreases，and the heat transfer characteristics of the wind tunnel heat exchanger show a downward trend. Meanwhile，the friction factor also decreases，leading to a downward trend in the flow resistance of the wind tunnel heat exchanger. The comprehensive heat transfer factor decreases，which decreases by 9.34%，8.96%，4.79%，and 5.34% respectively. Consequently，the comprehensive performance of the heat exchanger demonstrates progressive deterioration.
As one of the critical components of aircraft engine icing，the water droplet impingement characteristics on the rotating fairing surface directly influences the subsequent icing state.To investigate the water droplet impingement behavior under different operating conditions，a three-dimensional water droplet impingement model for the rotating fairing of aero-engine was established by using the Euler method and single rotating coordinate system.The water droplet impingement characteristics of the rotating fairing under stationary and rotating conditions were simulated respectively.The results show that under stationary conditions，as the freestream Mach number increases，both the water droplet collection coefficient and impingement area exhibit significant growth； compared to single-diameter droplets，when considering the Langmuir-D distributionof water droplets，the collection coefficient at the stagnation point decreases，while the impingement zone increases and the downstream collection coefficient also slightly increases.Under rotating conditions，therotational speed has negligible effects on droplet impingement characteristics due to the streamlined aerodynamic profile of the rotating fairing.
Addressing the high-precision modeling requirements of unsteady aerodynamics during complex aircraft maneuvers， a method for modeling non-steady aerodynamic forces based on an adaptive genetic algorithm （AGA） optimized long short-term memory （LSTM） neural network was proposed. Computational fluid dynamics （CFD） simulations were conducted to capture maneuver flight data during rapid turns at varying bank angles and rolling and looping maneuvers at different Mach numbers. An AGA-LSTM model was developed using this data to predict aerodynamic coefficients under non-steady conditions. Specifically， predictions for the aerodynamic coefficients during a 60° bank angle rapid turn maneuver were made， demonstrating accurate estimation of lift coefficient， drag coefficient， and pitch moment coefficient that closely matched CFD simulation results. To further validate the proposed model’s accuracy， predictions were compared with CFD simulation data and a traditional LSTM neural network model for Envelopment maneuvers. The results indicate that the AGA-LSTM neural network model provides closer predictions to simulation data compared to traditional LSTM models， thus offering improved prediction accuracy.
In order to select the characteristic indicator to more effectively characterize the performance degradation of the air compressor bearing，a feature indicator selection method based on game theory combinatorial weighting method was proposed.Through the analysis of the time-domain indicator of the bearing vibration and the preprocessing of redundant information，the time-domain indicator dataset of the bearing was obtained.Three characteristic indicator evaluation methods including monotonicity，robustness and trend were used to complete the selection of performance characteristic indicators.Based on this，the game theory combinatorial weighting method was used to weight three characteristic indicator and sixteen time-domain indicator to complete the selection of bearing performance degradation indicator.The effectiveness of this method was illustrated by example verification.
In order to deeply study the driving performance of ionic liquid gel （ILG）as ionic electroactive polymer，developed a novel soft actuator based on ILG and conducted a detailed investigation into the electromechanical coupling model of the ILG soft actuator. According to the material properties and current response law of electroactive polymers，established electromechanical coupling equations and driving equations for ILG soft actuator based on the equivalent transformer model of ionic polymer-metal composite actuators proposed by Claudia Bonomo. The least squares method was used to identify the coupling model of the ILG soft actuator， and the influence of structural parameters on the end displacement and driving force of the soft actuator was analyzed， providing a theoretical basis for the control of soft actuators. The electromechanical coupling model of the ionic liquid gel soft actuator is established， which lays a foundation for the development of ionic liquid gel soft robots.
In order to better solve the problem of robust fault-tolerant control for magnetorheological landing gear buffer systems with damper failures， a model reference adaptive fault-tolerant control strategy was proposed，and a mechanical model was established and key parameters were determined by damping experiments. A fault model was established for the magnetorheological landing gear system and fault-tolerant control was introduced. An adaptive law was designed to adjust the control gain in real time， and a fault-tolerant controller was constructed to deal with damper failures. Results show that compared with the traditional passive and model reference adaptive control methods， the buffer efficiency of the damper fault tolerant control method is improved by 4.9% and 0.95% respectively. This control method significantly improves the damping efficiency and quality of the magnetorheological landing gear damping system.
Tibetan Jiu Chess， a traditional folk chess game， is a complete information game that carries the profound Tibetan civilization and splendid culture. In view of the complexity of the rule system and the diversity of the game changes， the traditional game search algorithm is unable to cope with the vast game board and complex strategies. In order to improve the intelligence level of Tibetan Jiu Chess， a Monte Carlo tree search （MCTS） algorithm optimization strategy incorporating prior knowledge was proposed. The strategy was based on deep reinforcement learning in the key phases of layout planning and move strategy，and the strategy selection optimization function and evaluation function were designed by integrating the prior knowledge of domain experts. The search process of MCTS was efficiently guided by functions，and the best model for high-quality tessellation could be trained. Experimental results show that the improved MCTS algorithm achieves significant performance in the game.
Traditional transmission line wire crimping is done manually， and its crimping accuracy and consistency are difficult to ensure. To this end， an automatic crimping control system for transmission line conductors was designed， which took Siemens S7-1200 as the controller， took fuzzy PID as the core control algorithm， and applied the SCL language of Protherm platform for the programming and realization of fuzzy PID control algorithm. The designed system could set crimping parameters through the monitoring interface of the upper computer， realizing the functions of automatic movement of the slide table， automatic crimping of wires， automatic measurement of the distance between wires and edges， etc.， and the real-time change curves， the current variable values and the crimping status in the operation process of the system could be viewed in the monitoring interface. Experimental results show that the designed system can adaptively and dynamically adjust the control parameters to achieve precise control of wire crimping， improving crimping accuracy and reducing the labor costs.
The state of charge （SOC） of lithium-ion batteries is a critical parameter in the battery management system of new energy electric vehicles. To address the issue of insufficient SOC prediction accuracy for lithium-ion batteries under complex operating conditions，an intelligent SOC prediction method for electric vehicle lithium-ion batteries based on the Transformer neural network was proposed. Taking the Nissan Leaf battery as the research object， a charging and discharging test platform for new energy electric vehicle lithium-ion batteries was built to simulate the real energy demands of users and the dynamic changes in real-time energy needs. This platform dynamically adjusted the battery’s charging and discharging strategies， collected multi-dimensional battery data， and preprocessed the data. Then， a SOC prediction framework based on the Transformer model was constructed， which extracted complex time series features through neural networks， achieved high-precision predictions of lithium-ion battery SOC. The experimental results indicate that the proposed method outperforms other networks in prediction accuracy， with a mean absolute error of less than 1.51% and a RMSE of less than 0.48%， validating the effectiveness and accuracy of this method.
For manufacturing enterprise managers，mastering digital leadership adapts to the development of the digital era is the key to promoting the transformation and upgrading of manufacturing enterprises. Based on leadership theory，a path was explored for manufacturing enterprise managers to improve digital leadership，which summarized six antecedents affecting digital leadership，and empirically investigated them using the fuzzy set qualitative comparative analysis （fsQCA） method. The research shows that among all antecedent condition variables，no single element could individually contribute to the realisation of high digital leadership in manufacturing enterprises. There are two paths to achieve high digital leadership capabilities for managers in manufacturing companies. There are four paths to achieve non-high digital leadership capabilities for managers in manufacturing enterprises，which are causally asymmetric with respect to the group paths that produced high digital leadership in manufacturing enterprise.
Based on the theory of planned behavior，the qualitative comparative analysis was used to explore the complex antecedent mechanism affecting the innovation willingness of scientific and technological talents in universities.The results show that internal ecological degree，external ecological degree，directive norm，exemplary norm，self-efficacy and control are not the necessary conditions for the innovation willingness of scientific and technological talents in universities； There are three paths to affect the innovation willingness of scientific and technological talents in universities，namely，innovation attitude-driven，directive-normative attitude-driven，and mixed-driven.The conclusions are helpful to systematically explain the complex antecedents of the innovation willingness of scientific and technological talents in universities，improve the innovation efficiency of scientific and technological talents，and empower the high-quality development of scientific and technological innovation.
