A comprehensive review of the research progress of solar-powered drones，energy systems，and aerodynamic configuration was provided，aiming to guide the perpetual flight of solar-powered drones.In terms of research history，Sunglider has become the largest known solar-powered drones with a wingspan of 80 m，while the 29 500 m flight altitude record set by Helios remains unbroken to this day.PHASA-35 has become the fastest solar-powered drone with its top speed of 40 m/s.The payload ratio of solar-powered drones is steadily increasing，with China's Rainbow T4 having a payload ratio of approximately 0. 286，second only to Helios at 0. 457.In terms of energy systems gallium arsenide thin-film multi-junction batteries，with an efficiency of up to 33. 6% are the focus of future applications.Lithium-sulfur batteries，with an energy density of 650 Wh/kg are the highest energy-density storage batteries，but their stability issues require further research and improvement.In terms of aerodynamic configuration，the flying wing configuration has a high aerodynamic efficiency，but it has lower stability and poor controllability.The future research direction is to optimize the stability and operability while maintaining its aerodynamic efficiency.

In order to improve the surface quality and corrosion resistance of DD6 nickel-based single crystal superalloy，the electrochemical polishing experiment of DD6 nickel-based single crystal superalloy was carried out by formamidesulfamic acid solution，and the effects of polishing voltage，electrolyte concentration and polishing time on the surface quality after polishing were studied. The results show that under the conditions of 20 V，electrolyte concentration 1.2 mol/L and of 2 min，the surface roughness is the lowest value of 0.358 \mathrm{\mu }m，and the surface effect reaches the best at this time. Under the conditions of high voltage （30 V） and high acid concentration （1.6 mol/L），irregular pits and impurity particles appeare on the surface of DD6 samples，and the surface quality is poor. After electrochemical polishing，the brightness of DD6 samples is improved，and the polishing voltage is the key parameter affecting the surface brightness.It is analyzed that the surface O element content is low after polishing，indicating that no passivation film containing metal oxides is formed during the polishing process.The Tafel curves before and after polishing of DD6 samples show that the corrosion potential of DD6 samples is larger and the corrosion current is smaller after polishing，so the corrosion resistance of DD6 samples is improved by electrochemical polishing.

In order to address the challenges in structural strength analysis caused by limited training samples and extreme environmental conditions while improving analytical efficiency，deep transfer learning methods was applied to investigate the mechanical properties of composite laminates for the RX4E electric aircraft.Based on the analysis of experimental results obtained from composite laminates， multiple deep learning models were compared in terms of their ability to predict the experimental results. Finally， the convolutional long short-term memory （CLSTM） was selected as the optimal deep learning model. Furthermore， a transfer learning （TL） model was introduced to accurately predict the stress-strain relationships of composite laminates under varying temperatures， humidities and layup configurations. The results indicate that the proposed TL-CLSTM network model has exceptional capability in predicting the mechanical properties of composites， particularly in predicting the stress-strain relationship， with a mean squared error and a root-mean-square error of 10^-5and 10^-3 respectively.The proposed model can effectively predict the mechanical properties of composite laminates for electric aircraft， overcoming the complexities and inefficiencies of traditional mechanical properties measurement methods，which providing a novel pathway for the future study of electric aircraft manufacturing.

To reduce the development costs of electric aircraft， a multidisciplinary optimization design approach was investigated based on the entire life cycle. By analyzing the composition of the entire life cycle costs for electric aircraft，an entire life cycle cost estimation model was developed. The research established multidisciplinary analysis models encompassing aerodynamics， flight performance，mass， and economic factors. With the optimization objective of minimizing life entire cycle costs， a comprehensive multidisciplinary optimization design method for electric aircraft was proposed. Taking a four-seat electric aircraft as a case， the parallel subspace optimization algorithm was employed to identify the optimal solution， resulting in an optimized overall design scheme that validates the method's effectiveness. This method can be applied to electric aircraft conceptual design， providing technical support for electric aircraft development.

To address the process route planning problem characterized by dynamic process requirements and intricate process data，a flexible process route planning method was proposed based on deep recurrent q-network （DRQN）.Firstly， leveraging the structural advantages of the long short-term memory （LSTM） network， sequential data features were thoroughly mined to enhance the accuracy and stability of process route planning.Secondly， by integrating the robust dynamic decision-making capability of the deep q-network （DQN） with an adaptive adjustment strategy， the challenges posed by fluctuations in requirements and processing environments were effectively mitigated.Lastly， in response to frequent process changes， a "selective forgetting" mechanism was implemented to improve the response speed of process route planning during step process changes.Simulation results demonstrate that the proposed method can efficiently resolve the process route planning issue associated with part occurrence feature reconstruction.

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.

To explore the impact of enterprise standardization capabilities grounded in the theory of resource conservation，a meta-analysis structural equation model was constructed based on data from 20 empirical research samples to reveal the potential relationship between them. Research results indicate that Standardization capability positively promotes innovation performance.For technology-based enterprise，the positive impact of standardization capability on innovation performance is more significant；when considering mediating variables，the positive impact of standardization capability on innovation performance is more significant；knowledge conversion partially mediates the impact of standardization capability on innovation performance. It is recommended that enterprises should formulate reasonable standardization strategies based on their own situations，actively engage in standardization formulation，and strengthen the utilization of knowledge resources.

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.

Video person re-identification is a technology for identifying specific person in a multi-camera surveillance network. Compared to the methods based on single-frame images， this type of algorithms can provide more person information， but it also has issues such as model complexity and misalignment in constructing features. To address those issues， a feature fusion-based video person re-identification algorithm was proposed. The proposed algorithm included a global branch and a local branch with spatial transformation. The global branch extracted the global features of person， capturing coarse-grained information and overall contextual information of the person. The local branch with spatial transformation integrated a spatial transformation matrix into the local branch to learn discriminative local regional features and alleviating the issue of feature misalignment. By utilizing a multi-branch structure， the algorithm fused local and global features and aggregated features through temporal average pooling to enhance the diversity of features and improve the robustness of the model. Finally， the model was trained using cross-entropy and a soft boundary triplet loss. The test results on the Mars and DukeMTMC-Video datasets have verified the feasibility of the proposed algorithm. Specifically， the Mars dataset achieves mAP and Rank-1 accuracies of 82.25% and 89.76% respectively， demonstrating excellent practicality.

With the rapid development of the aerospace industry，high quality repair technology of aerospace aluminum alloy castings has significant economic benefits and scientific research mirits.Accordingly，a study on the laser deposition repair technology of ZL105 aluminum alloy was carried out.Optimal laser deposition repair process parameters were explored.The microstructure morphology of the laser repair area，the microhardness and room temperature tensile properties of the specimens were measured.The results show that good metallurgical bonding between the repair area and the substrate are obtained.Restoration areas are finely organized and composed of columnar dendrites and isometric crystals.The microhardness of the repaired area increased 16% compared to the substrate，and the strength of the repair parts can reach more than 96% of the strength of the substrate.What’s more，as the repair ratio increases，the strength of the repair parts decreases gradually but the plasticity improves.The fracture mechanism of the repaired specimen is a mixed fracture of tough and brittle.

To address the issues of low efficiency， blind spots in vision， and high costs of traditional manual security patrols， a security patrol system based on the DiMP （discriminative model prediction） algorithm was designed. The system adopted a modular design and implements autonomous flight control and tracking functions for UAV （unmanned aerial vehicle） on an embedded onboard computer. To enhance the tracking precision and accuracy of small targets during the patrol process， a multi-scale feature fusion strategy was employed to improve the DiMP target tracking algorithm. This strategy involved fusing image pyramid features of different scales with the backbone network features， providing the backbone network with information-rich fused features. The optimized DiMP algorithm achieved a 2.6% increase in target tracking success rate and a 3.4% increase in precision on the UAV123 dataset， while also reaching a tracking speed of 38 fps on the VOT2018 dataset. Finally， the effectiveness of the UAV security patrol was verified in an outdoor environment. The results show that the improved tracking algorithm is capable of operating in real time on the UAV and stably tracking the target for a long time.

In order to measure and analyze the forces on skis during skiing，It is necessary to develop the snowboard measuring system.On the basis of summarizing and analyzing the use of similar products，the integrated circuit design of signal conditioning and wireless transmission，and two dimensional force sensor combination were adopted，a five-dimensional force measurement system for snowboard was developed successfully.The system has higher stiffness，natural frequency and better dynamic measurement performance.The static accuracy of the three-dimensional force sensor is better than 0.2%FS，and the static accuracy is better than 0.4%FS.The dynamic performance of landing impact is tested by the system，and the test results are in good agreement with the theoretical analysis.In the testing process，all the sensors return to zero well，the dynamic performance is stable，and the law of measuring load is reasonable.The successful development of the system provides reference for the research and development of multimensional force measuring system for skiing and skating，and lays a good foundation for the localization and self-control of sports testing device.

Regular inspection of transmission lines is an important guarantee for the long-term stable operation.To solve the problems existing in traditional manual inspection methods such as high labor intensity，low work efficiency and high cost，a PLC-based transmission line automatic inspection robot system was designed， focusing on the robot inspection operations of anti-vibration hammer resetting and broken lines repairing control problems. The manual and automatic control mode were used， the classic PID control algorithm was applied to reset the anti-vibration hammer， and repair the broken lines. The experimental results show that the transmission line inspection robot repair control system can accurately achieve the resetting of the anti-vibration hammer and the repairing of broken lines， and get a better control effect. The system designed is of great significance for the inspection robot to replace the traditional manual inspection method， reduces the labor intensity of inspectors and improves the automation level of transmission line management and maintenance.

Aiming at the problem that the forming quality of wingtip fairing and glass fiber rib parts in aircraft body couldn’t be guaranteed in the manufacturing process， the influence of uniformity of temperature field distribution on mechanical properties and solidification deformation of parts was studied by optimizing the curing program， changing the number of parts entering the tank， and monitoring the surface temperature field distribution of parts by thermocouple.The results show that in the curing process， appropriately increasing the curing temperature can effectively increase the heating rate in the lower temperature area， improve the mechanical properties of parts and reduce the deformation during curing. When six glass fiber rib specimens are put into the autoclave， the heating rate in the whole tank will decrease， which will affect the curing effect of the structure. In actual production， the number of specimens in the autoclave should be reasonably arranged to ensure the forming quality.

Hydroxylated boron nitride nanosheets （BN—OH） were prepared by using 30% hydrogen peroxide solvent to strip and modify hexagonal boron nitride （h—BN） by the method of combined hydrothermal/ultrasound preparation. BN—OH/APTES—HPCTP intumescent refractory coatings were prepared by melt blending method using BN—OH， silane coupling agent （APTES） and hexaphenoxycyclictriphosphonitrile （HPCTP） as filler materials. The impact of BN—OH and HPCTP on flame retardant and smoke suppression property of intumescent refractory coatings was explored. According to the cone calorimeter （CCT） test， the BN—OH/APTES—HPCTP intumescent refractory coatings had the lowest fire growth index （FGI）， and the thermal release rate peak （pHRR） and smoke release rate peak （pSPR） were reduced by 17.37% and 22.39%， respectively， compared with conventional intumescent refractory coatings. It is found that HPCTP-assisted intumescence system （IFR） catalyses the expansion of epoxy resin （EP） to form a carbon layer. The modified boron nitride （BN—OH/APTES） is beneficial to improving the compactness of the carbon layer and preventing the flammable gas from approaching the substrate， thereby reducing the damage of the substrate caused by fire.

To address the control requirements for extending the residual stability margin of adaptive variable-cycle engines， a specific configuration of an adaptive variable-cycle engine was selected as the research object. The basic effect sensitivity analysis method was used to analyze the impact of geometric adjustment on the stability margin under three typical engine operating conditions： ground take-off state， subsonic cruise state and supersonic cruise state. The adjustable mechanisms that should be prioritized when the stability margin of the compression system of the adaptive variable-cycle engine was insufficient were identified. The geometric adjustment stability margin extension law was established for this specific adaptive variable-cycle engine and verified under typical operating conditions. The results show that adjusting the throat area of the outer nozzle is effective for extending the front fan stability margin； adjusting the throat area of the nozzle and the ejector area of the rear bypass is effective for extending the rear fan stability margin； adjusting the compressor inlet guide vane angle is effective for extending the compressor stability margin. When applying the established geometric adjustment strategy under typical conditions， the absolute error in stability margins for all compression components is less than ​​0.5%​​， demonstrating the good applicability of the proposed method.

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.

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 solve the problem that rolling bearing fault features were difficult to be extracted under strong noise background， parameter optimized variational mode decomposition （VMD） and maximum correlation kurtosis deconvolution （MCKD） were proposed to extract rolling bearing fault features. Firstly， the original signal was decomposed by the optimal combination of parameters obtained by offline optimization of the VMD parameters using the improved sparrow algorithm. Secondly， in order to screen and reconstruct each IMF after decomposition， a new screening metric was constructed based on the envelope spectrum peak factor and sample entropy. Then， the reconstructed signal was augmented with MCKD optimized by the online method of the improved sparrow algorithm. Finally， the bearing failure frequency information was extracted from the enhanced signal by envelope demodulation analysis. Simulation and experimental results show that the proposed method is able to enhance the shock components submerged in the strong noise and effectively extract rolling bearing fault features.

In order to improve the hot corrosion resistance of TiAl-based alloys in molten salt， rare earth Ce modified NiCrAlY coating was prepared on the surface of TiAl-based alloy by atmospheric plasma spraying technology. The hot corrosion tests in molten salt of NiCrAlY（Ce） coatings were carried out at 900 ℃ for 60 h. The effect of rare earth element Ce on the hot corrosion behavior and mechanism was further discussed. The results show that the addition of rare earth element Ce can improve the hot corrosion resistance of NiCrAlY coating. After hot corrosion at 900 ℃ for 60 h， the corrosion layer on the surface of the NiCrAlY/TiAl coating system peels off severely， causing the failure of the coating. Therefore， the TiAl alloy has suffered from severe corrosion. For the NiCrAlYCe/TiAl coating system， its surface still covers with a complete corrosion layer and only small cracks generat at the interface between the coating and substrate. The NiCrAlYCe coating still possesses hot corrosion resistance property to a certain degree after corrosion.The addition of rare earth element Ce is beneficial to the selective oxidation of Al element， which hindered the formation of spinel oxides. The dense Al₂O₃ film blocks the internal diffusion of S element， thereby improving the corrosion resistance of NiCrAlY coating and extending service life of TiAl based alloy.

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.

In response to the current problems of relying on manual experience and slow processing speed for ligh electric helicopter faults，a fault diagnosis expert system based on fault tree was proposed to ensure the flight safety and reliability.Fault tree model was constructed based on common faults of a light electric helicopter. Through qualitative and quantitative analysis of the fault tree，the probability importance FVI values of each event in the fault tree were calculated. The FVI values were used to rank each fault event and convert the fault tree into a binary fault tree. An expert knowledge base was established through binary fault tree analysis，and the inference machine was designed based on the production rules and forward reasoning strategies in the knowledge base. Finally，the expert system was developed using QT，and the simulation testing proved that the designed expert system can effectively diagnose faults in light electric helicopters.

With the development of the aerospace field and advancement of science and technology，the application field of die-less spinning is becoming more and more extensive.Pre-formed workpieces can be obtained by spinning without a mandrel support，which can really achieve the purpose of high efficiency and low consumables.However，the lack of mandrel support makes it difficult to determine the direction and speed of metal flow of the original blank during forming process.The study of the formed workpiece microstructure can reflect the metal flow and plastic deformation on the macroscopic level，and it can also deeply reveal the related mechanism of the spin forming method.So far，there are few studies on the evolution of the microstructure of die-less spinning forming，which is summarized in this paper.According to the microanalysis of the influence of the spinning parameters on the forming accuracy； through the microstructure of the grain orientation and grain size of the spinning process to carry out a detailed analysis of the metal flow； according to the microstructural characteristics of the spinning workpiece can be the study of the mechanical properties，which helps to reveal the spinning process.The study of the mechanical properties of the spinning workpiece can help to reveal the forming mechanism of the spinning process.

In view of the problem of traditional continuous carbon fiber toughened ultra-high temperature ceramic matrix composites （C_f /UHTCs）， such as long preparation period and high cost， an internal grouting process of carbon fiber based on ultrasonic regulation technology was proposed to realize the uniform distribution of ceramic powder in carbon fiber braided body， and the mechanical properties of the prepared composites were analyzed. The research results show that the mechanical properties of the composites can be effectively improved by using ultrasonic regulation technology to assist the internal grouting of carbon fiber， and it has a remarkable effect in the preparation of ultra-high temperature ceramic matrix composites toughened by continuous carbon fiber， which can improve the material preparation efficiency and improve the material properties at the same time， and plays a very important role in promoting the innovation of composite preparation technology.

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%.

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.

In order to improve the spoofing interference detection capability of satellite navigation system， a satellite navigation spoofing interference detection algorithm based on RNN was investigated， and the loss function was designed. In order to improve the accuracy of data prediction， a data preprocessing method was studied， which maped the data in a fixed interval and amplifies the characteristics of the data. The experimental results show that the prediction accuracy of the RNN model for the signal-to-noise ratio of ten satellites is higher than that of the Transformer model. The recurrent neural network model has an average accuracy of 64.76% in predicting the signal-to-noise ratio data， while the Transformer model has only 3%. In the RNN prediction model， the accuracy of the prediction for 7 out of 10 satellites signal-to-noise ratios is above 60%. It can be seen that the RNN model has a better prediction effect when facing the signal-to-noise ratio data of BeiDou satellite navigation signals with the time series data type. Therefore， the RNN model can realize the prediction of 0.08dB error for BeiDou signal-to-noise ratio， and when the difference between the future signal-to-noise ratio value and the predicted value is greater than 0.08 dB， it is considered that the signal is a spoofing signal at this time， so as to realize spoofing interference detection. The research results provide certain reference value for the research of satellite navigation spoofing algorithm.

In order to gain a theoretical understanding of the heat transfer mechanism of C/SiC materials，Monte Carlo method was applied to analyze heat transfer of C/SiC corrugated lattice structure composite material.The heat transfer mechanism of the corrugated lattice structure was studied from three aspects： the beam emission position，the beam emission direction and the judgment of the beam occlusion.At the same time，the influencing factors of the heat transfer coefficient of the lattice structure were studied by changing the structural geometric parameters，the emissivity of the solid surface and the temperature applied by the upper panel.The number of samples can be accurate to 4.0×10⁶ and the heat transfer coefficient converges to 0.554 9 \mathrm{W}/(\mathrm{m}\cdot \mathrm{K}) by using the heat transfer coefficient derived from the formula of Monte Carlo method.The results show that，the linear relationship between the heat transfer coefficient，the geometric parameters of the corrugated lattice and the reasons for its change are given，the optimal thermal insulation model parameters of the corrugated lattice structure are obtained.The theoretical research provides certain engineering application value for thermal insulation of aerospace material and composite material research.

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.

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 distribution​​of 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，the​​rotational speed​​ has negligible effects on droplet impingement characteristics due to the streamlined aerodynamic profile of the rotating fairing.

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.

Based on the measurement of EEG，the behavioral intention of online shoppers after interacting with shopping website was evaluated and predicted.The research method combining objective electroencephalogram （EEG） experiments and subjective evaluation scales was employed to measure the EEG of online shoppers during the interaction tasks on the homepage of shopping websites， and to predict the behavioral intentions of online shoppers towards shopping websites after completing the tasks. The method of variance analysis was adopted to extract the significant EEG-based indicators which influence users’ behavior intentions. Based on the partial least squares （PLS）method，a relationship model between the users’ electrical indicators and the behavior intentions was established， and the model was verified. The results show that the proposed model can predict the approach trend of online shoppers towards shopping websites well.

In wireless multi-hop networks，using the broadcast backbone to forward messages can effectively improve network efficiency.Based on the existing ECHO protocol，an optimized ECHO-OPT scheme was proposed，which considered the energy factor of nodes in the decision-making process of critical nodes，and optimized the redundant nodes in the critical node set in the process of message forwarding.In the experiments，the influence of communication range on redundant nodes was studied and the network performance of the protocol was tested under fixed network density and dynamic network density.The simulation results show that compared with ECHO，ECHO-OPT can optimize the size of critical node set by an average of 4.67 in high-density networks，and reduce the network load by 65% and 32% respectively compared with MPR and ECHO.At the same time，ECHO-OPT also has a higher network lifetime.

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.

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 solve the thermo-mechanical fatgue damage problem of trubine blade under the complex multifield coupling service conditions，combining the improved Morrow low-cycle fatigue damage and creep damage models based on the load spectrum of the engine’s service conditions，the prediction of the thermo-mechanical fatgue life of engine turbine blade was achived.Firstly， considering the rotor-stator interference effect between cascades， the three-dimensional flow field modeling and multi-field coupling simulation of the turbine blade were completed. Further， based on the engine load spectrum and multi-field coupling response characteristics under service operating condition， the key assessment positions of fatigue damage of the turbine blade were determined. then， an improved Morrow low-cycle fatigue damage model was developed and compared with traditional models and experimental results for verification. Finally， using the linear cumulative damage criterion， as well as the Morrow low-cycle fatigue damage and L-M creep damage， thermo-mechanical fatigue life of the turbine blade was predicted under service conditions. The results show that the numerical simulation results are in good agreement with the experimental data， verifying the accuracy of the three-dimensional unsteady flow field simulation of the turbine blade and the improved Morrow low-cycle fatigue damage model. Under the engine load spectrum and multi-field coupling effect of service conditions， considering the Morrow low-cycle fatigue damage and L-M creep damage， the thermo-mechanical fatigue life of the turbine blade is 6.028×10³ h. The area with the minimum life is located at the leading edge of the blade root at the air inlet， the assessment position A， which is the key maintenance part of the turbine blade. This study can provide a theoretical reference and basis for the thermo-mechanical fatigue life assessment of turbine blade under complex service operating condition.

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.

Nomex honeycomb materials are widely used in marine，high-speed rail，aerospace and other fields because of the material’s low density，high specific strength and high specific stiffness. However，the non-homogeneous，thin-walled and brittle characteristics of honeycomb structures make them prone to tearing，crushing and other defects during processing. Therefore，scholars both in China and abroad have used ultrasonic machining technology to solve the problem of Nomex honeycomb material processing with the advantages of small cutting force and high surface quality，which have carried out extensive and in-depth research. However，compared with ordinary machining，high-frequency vibration and periodic impact generated in high-quality and efficient ultrasonic machining process put forward higher requirements for tool performance and life. Therefore， focused on tool material selection， tool design， kinematic analysis， cutting force and cutting heat modeling， and surface topography analysis during machining of Nomex honeycomb materials. The research status of machining mechanism，cutting characteristics and ultrasonic tool design for ultrasonic cutting of Nomex honeycomb materials were summarized. The future research and development trend of ultrasonic cutting Nomex honeycomb materials were put forward， which provided a reference for further research on the service performance and processing quality of ultrasonic cutting tools in cutting.

To meet the requirements for open-loop trajectory motion of a solar-powered car， a design and fabrication method was proposed for a solar-powered car. Firstly， by using B-spline curves， the characteristic points were fitted to generate an ideal open-loop trajectory curve. MATLAB software was then utilized to analyze and optimize the planned trajectory to produce the cam profile. Next， based on the overall functional requirements， the overall structure， transmission mechanism， and steering fine-tuning mechanism of the solar-powered car were designed. Subsequently， simulation software was employed to perform simulation analysis and optimization of the cam trajectory， and the car’s circuit modules were assembled. Finally， actual driving tests of the car were conducted. To improve the trajectory accuracy of the car， the front wheel offset angle was modified by adjusting the fine-tuning mechanism. Experimental results demonstrate that the car fabricated using this method operates stably and successfully passes through all predetermined characteristic points.

To ensure the normal operation of turbine blades Facing continuously increasing turbine inlet temperatures， the development of more efficient cooling technologies has become particularly urgent. Ceramic matrix composite （CMC） transpiration cooling technology combines the excellent high-temperature resistance of CMC with the efficient heat dissipation potential of transpiration cooling， showing broad application prospects in future thermal protection of turbine blades. However， the strong anisotropy of CMC materials and their complex internal porous structure pose significant challenges for the thermal analysis of the transpiration cooling process， and the underlying flow and heat transfer mechanisms remain unclear. This review summarized recent research progress on the anisotropic thermal conductivity and microporous seepage characteristics of CMC， analyzed key existing problems and challenges in current studies， and offerd suggestions for establishing a comprehensive design framework for CMC turbine blade transpiration cooling structures.