To efficiently predict the dynamic stability of integrated thermal protection systems under aerodynamic heating environment， a thermal flutter calculation method for corrugated sandwich panels based on a thermo-mechanical equivalent model was proposed， aiming to enhance the computational efficiency of finite element analysis. First， the homogenization theory was applied to approximate the core layer as a single layer of orthotropic material， thereby simplifying the model. Second， the proportion of the areas occupied by the web and the insulating material was redefined to increase the characteristic size of the equivalent area， thereby reducing the number of finite element grids while ensuring the accuracy of the temperature gradient. Finally， based on the developed thermo-mechanical equivalent model， the modal characteristics of the corrugated sandwich panel were extracted， and the p-k method was employed for thermal flutter analysis to evaluate the aerodynamic response. The results show that this method improves computational efficiency by 80%， and the error is controlled within 3%.

In order to study the influence law of main process parameters on forming limit of conical parts in dieless spinning based on spherical roller， the influence of four main process parameters， such as spinning part half-cone angle， feed rate of the spinning roller， initial diameter of the sheet metal and roller radius， on the forming limit of the spinning part was studied through the spinning forming experiment of the conical part with spherical roller. The results show that the decrease of the half-cone angle of the spinning part leads to the increase of the feed of the spinning roller in the axial direction of the sheet material and the increase of the contact area between the sheet material and the spinning part roller. The spinning part is prone to wrinkles or cracking. In addition， the decrease of the half-cone angle of the spinning part will increase the bending degree of the sheet material at the round corner of the mandrel， and the spinning part is prone to crack. The contact area between the sheet and the roller increases with increasing the feed rate of the roller. The spinning part is prone to appear wrinkle. When the feed rate of the roller decreases， the forming time of the roller to the sheet is prolonged， and the spinning part is prone to appear crack. The increase of the initial diameter of the sheet metal increases the time of the tensile stress on the radial direction of the sheet metal， which leads to the cracking of the spinning part at the top fillet. While the decrease of the half-cone angle of the spinning part leads to the increase of the deformation of the sheet metal and the risk of wrinkling of the part flange. The flange of the part is more likely to wrinkle. The radial tensile stress of the sheet metal with a smaller radius is longer in duration during forming， which leads to cracking of spinning parts more easily. The circumferential compressive stress of the sheet metal with a larger radius increases and lasts longer in duration at the end of spinning forming， resulting in the outer edges of the spinning parts being prone to wrinkles.

To verify whether the mechanical properties of the composite skin of a certain type of electric aircraft meet the design requirements under hot and humid environments， an environmental chamber was used to simulate the actual operating conditions， and the conditioning of test specimens under elevated-temperature and wet conditions was completed. for composite foam sandwich structure wing skin instability test specimens from a certain type of aircraft， the environmental chamber simulation technology was adopted. The elevated temperature wet （ETW） conditioning was completed during the preliminary assessment of test conditions. Comparative analysis of failure modes and structural strength was conducted under both room temperature dry （RTD） and ETW environments. The strain variation with compressive load was monitored， and the influence of the hygrothermal environment on the mechanical properties of composite materials was analyzed. The results indicate that the recommended maximum service temperature for the structure of this test specimen is 71 ℃， with a minimum temperature of -54 °C and a relative humidity of 85% RH. Post-test analysis reveals that although both the strength and stiffness of the structure are significantly reduced under ETW environments， they still meet the airworthiness verification requirements. Due to the influence of the ETW environment， the collaborative working ability between the fibers and the matrix is weakened， and they can’t efficiently cooperate to jointly bear the load and resist deformation. Therefore， the failure modes of the test specimen under the ETW environment exhibit greater complexity and diversity compared to those observed under the RTD environment. The results provide data support for optimizing the environmental conditioning scheme， establishing environmental design criteria， and completing the airworthiness verification plan， while offering critical technical references for designing composite structure in aircraft operating under complex environmental conditions.

Simulation and experimental comparison methods were used to study the thermal expansion coefficient and anisotropic thermal expansion behavior of 2.5D SiC_f /SiC ceramic matrix composites in different directions to provide certain ideas for the thermodynamic research. Thermal expansion coefficient of 12 temperature gradients in the range of 100~1 200 ℃ in the 0°，45° and 90° directions of 2.5D SiC_f /SiC ceramic matrix composite were measured respectively to analyze the influence of direction and temperature. Then simulation models in different directions were established to simulate the experimental heating process and to get thermal expansion coefficient of the material. The results show that the coefficient of thermal expansion increases with temperature rises and then gradually stabilizes. In terms of direction， the thermal expansion coefficient of the material in the direction of 45° is greater than that of the other two directions， and in the direction of 90° is the smallest. The thermal expansion coefficient is calculated through the thermal deformation data results of the simulation model. The calculated Pearson correlation coefficients are 0.968 06， 0.974 19 and 0.917 37， which proves the validity of the model and lays the foundation for future research.

In order to solve the problems of large volume， limited travel and aseptic isolation requirements of vascular interventional surgery robot， a slave mechanism of vascular interventional surgery robot imitating doctor’s action was designed. The bionic finger-based mechanism enabled unrestricted continuous delivery and rotation of guidewires / microcatheters， simultaneous rotation and delivery of guidewires， and adjustable clamping distance and force and the modular design was utilized to achieve the isolation of sterile/non-sterile operation areas.A three-dimensional model of the mechanism was developed， and the design structure was analyzed kinematically to establish its kinematic equations.The rationality of the design was validated through simulation analysis. Experimental studies were conducted to investigate the positioning accuracy of guidewire delivery. Results indicate that the mechanism achieves a positioning error within from -0.5 mm to 0.5 mm under static conditions， enabling precise delivery of guidewires. This performance meets the clinical requirements for vascular interventional surgery robot.

To further explore the thermal insulation potential of C/SiC corrugated lattice structure composite materials in extreme environments such as aerospace，took C/SiC corrugated lattice structure composite materials， and investigated their thermal insulation performance using CAE simulation methods based on Fourier’s heat transfer law. Firstly， under isotropic conditions， the effect of temperature gradient on heat transfer coefficient was deeply explored for steady-state and transient situations； Secondly， by comprehensively optimizing the variable constraint range， considering factors such as fiber size， fiber content， and weaving method， a simulation analysis of the heat transfer performance of the corrugated lattice structure was conducted based on anisotropy. The simulation results show that under isotropic heat transfer conditions， the insulation efficiency of the corrugated lattice structure under five high-temperature gradients reaches 13.89% to 14.12%； Under anisotropic heat transfer conditions， the temperature of carbon fiber is significantly higher than that of SiC matrix， and when the fiber content is above 600 K， the effect of temperature on the heat transfer coefficient can be ignored. The twill weaving method exhibits better insulation performance than the plain weaving method， especially under low-temperature insulation conditions. This simulation study provides certain engineering application value for the research of thermal insulation performance of aerospace composite materials.

Aiming at the problems of high computational cost， large parameter volume， and difficult deployment in current deep learning models for glass bottle defect detection， an efficient lightweight solution was explored.To solve this problem， the feature extraction network GCNet was designed by combining the network structure of YOLOv8. First， GhostConv was used to replace standard convolution. In order to reduce the number of parameters and calculation amount of YOLOv8 bottleneck layer， the convolution module of bottleneck layer was designed， and the bottleneck layer was rebuilt. A new CM module was built based on the structure design of C2f module. The new feature extraction network had a lower parameter count than the original YOLOv8 network. In the feature fusion part， a reconstructed double-weighted bidirectional feature fusion pyramid structure was used to solve the problem of feature information loss with the deepening of network layers. At the same time， for the boundary box regression problem， the combination of WIoU and Inner-ShapeIoU improved the regression convergence speed of the model. The results show that compared with the YOLOv8 algorithm， the YOLOv8-DB composed of the above， the number of parameters is reduced by 45.8%， the calculation amount is reduced by 11.9%， and the accuracy is increased by 0.4%. The improved model can effectively reduce the consumption of computing resources， and is better suitable for specific industrial detection environments.

In view of the problem of path planning caused by unknown environment when unmanned vehicle performs tasks in complex rescue environment， a dynamic path planning method was proposed for unmanned vehicle assisted by UAV. Firstly， UAV aerial images and SURF algorithm were used to assemble the aerial images to build the complete map information.Then the color space conversion and morphological processing were performed to identify the obstacle information.Finally， the improved artificial potential field method was applied to conduct the unmanned vehicle path planning， and the dynamic gain factor and influence function method were proposed to redesign the potential field function to solve the target inaccessible problem； meanwhile， A* algorithm was proposed to solve the local minimum problem of the artificial potential field method. The results show that the UAV-assisted unmanned vehicle path planning method is feasible and efficient， which improves the performance of unmanned vehicle path planning in complex rescue environment.

In order to solve the problem that the current fitness exercise evaluation systems provided poor evaluation information and involved high computational complexity， a fitness exercise evaluation system based on human posture estimation was proposed. The system utilized the built-in camera of mobile phones or tablet computers， combined with human pose estimation algorithms， action recognition algorithms， and action evaluation algorithms to achieve intelligent and effective evaluation of users’ fitness exercises. Firstly， the MediaPipe algorithm was used to estimate the human posture and obtain the human joint bone data.Then， it was fed into the proposed SCBT-GCN network for action recognition. Based on kinematic principles， a series of evaluation methods had been designed which evaluate joint angles， symmetry， trajectory characteristics， and movement fluency. Finally， corresponding targeted movement assessment algorithms were invoked based on the identified action categories to detect and evaluate abnormal fitness movements， thereby forming a fitness action evaluation system with strong intelligence and high real-time performance. Experimental results show that the system has an accuracy of 98.6% in action recognition， which can detect abnormal actions in real time and score fitness actions offline， demonstrating high practical value.

To gain an in-depth understanding of the latest research advances in gait recognition， the existing studies were comprehensively reviewed and summarized， with a focus on discussing the strengths and weaknesses of deep learning-based gait recognition methods， as well as outlining their applications and prospects in civil aviation security. The results show that deep learning methods have significantly improved the accuracy and robustness of gait recognition， demonstrating greater potential in civil aviation security scenarios such as suspectassisted identification and intelligent earlywarning.

Civil-military integration enterprises serve as core carriers for constructing an integrated national strategic system and capabilities，and enhancing their risk-taking capacity is critically significant for advancing the civil-military integration development strategy. Taking this as the point of departure， which aims to explore the relationship between supply chain concentration and risk-taking capacity， thereby providing theoretical and practical support for the further advancement of the civil-military integration development strategy. The empirical analysis of the listed civil-military integration enterprises in Shanghai and Shenzhen A-shares from 2015 to 2023 finds that： supply chain concentration can improve the risk-taking level of civil-military integration enterprises， and digital transformation plays a positive moderating role in the relationship between the two； secondly， supply chain concentration can improve the level of risk-taking by alleviating corporate financing constraints and reducing information asymmetry； furthermore， supply chain concentration has a more obvious effect on the improvement of risk-taking level of military-to-civil enterprises and large-scale civil-military integration enterprises. The conclusion of the study is that it is of reference significance for civil-military integration enterprises to improve the level of risk-taking through supply chain centralization.

In the new development stage， promoting digital transformation is an inevitable choice to promote the high-quality development of enterprises. The panel data of China’s A-share listed companies from 2012 to 2022 as the research sample was taken， which used the entropy value method to innovatively construct enterprise high-quality development index system， examined the empowering effect of digital transformation on high-quality development of enterprises， and tested the threshold effect of R&D investment on high-quality development of enterprises as a result of the role of digital transformation and the possible differences in heterogeneity. The results show that digital transformation significantly promotes high-quality development of enterprises. Furthermore， influenced by the level of R&D investment， digital transformation has a threshold effect on the high-quality development of enterprises. Further research finds that there are three levels of heterogeneity in the threshold effect， the region where the enterprise is located， the nature of the property right， and the size of the enterprise. The findings of the study can provide empirical evidence and important theoretical references for enterprises to formulate digital transformation strategies and determine the reasonable range of R&D investment.