In response to the need for rapid iteration in the conceptual design stage of propeller aircraft， low-fidelity aerodynamic evaluation methods， such as the vortex lattice method was a more suitable choice. In order to obtain suitable computation parameters and quantitative errors， the NASA OpenVSP unsteady vortex lattice method （UVLM） was studied using the propeller standard model， and the computation characteristics of the multiple reference frame quasi-steady vortex lattice method （MRF-VLM） were presented for the first time. The computational convergence and error characteristics were analyzed using the APC electric-propeller standard model， and the grid/iterative parameter settings that take into account both computational stability and efficiency were obtained. The comparison with experimental data shows that with appropriate grid and iterative parameters， the computation errors for the propulsion efficiency of the above two methods are within 6.1% and 3.6% respectively， under conditions of low pitch angle and medium advance ratio. The accuracy meets the requirements of the conceptual design stage， and the MRF-VLM computation with 4-thread parallel processing takes only 4 minutes， which is more efficient. The case of NACA 5868-9 propeller standard model further verify the computational reliability of the MRF-VLM method. The above research results can provide a reference for the reliable engineering application of OpenVSP VLM. However， due to the limitations of the linearized potential flow theory of the VLM， the above two methods can not accurately simulate the strong flow nonlinearity under high pitch angle and high/low advance ratio， and the computation accuracy needs to be improved.

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.

To address the collaborative search task planning issue for unmanned aerial vehicles （UAV） and unmanned ground vehicles （UGV） in search and rescue scenarios， a method that combines centralized task allocation with independent path planning was proposed. Firstly， tasks were clarified based on requirements and assigned to UAV and UGV. Firstly， the UAV and UGV conducted trajectory planning and path planning independently according to their assigned tasks. For the task allocation problem，a multi-objective area segmentation and allocation model based on task types was proposed，and an adaptive hybrid algorithnm incorporating genetic algorithm and tabu search was developed in solution.For trajectory planning， a “traveling salesman path-area coverage path planning” model was constructed based on the task requirements of the UAV， employing an improved genetic algorithm that introduced an “S”-shaped path as the initial population and designed a fitness function to optimize the selection process. Regarding the path planning for UGV， a method that combines A* algorithm with artificial potential field algorithm was proposed to find the optimal traveling path. Simulation results indicate that the proposed algorithm effectively completes search tasks and shows significant improvements in both task execution efficiency and path planning accuracy compared to commonly used genetic algorithms and A* algorithms.

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.

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 investigate the influence of assembly deviations on pipeline sealing performance， a finite element model was established based on the torque-tension relationship. The influence of three assembly deviations （axial，radial， and angular） acting individually on the sealing performance of pipeline connectors was analyzed， and the coupling influence of these three assembly deviations on the sealing performance of pipeline connectors was studied through orthogonal experiment. The results indicate that under single deviation conditions， negative axial deviation，radial deviation，and angular deviationall reduce pipeline sealing performance. When the three assembly deviations are coupled， the sealing performance decreases. Negative axial deviation and angular deviation have significant influences on pipeline sealing performance， while the influence of radial deviation is relatively small. Therefore， in practical engineering， negative axial deviation and angular deviation should be strictly controlled， and positive axial deviation and radial deviation should be minimized as much as possible.

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.

Aiming to address the limitations of traditional health monitoring methods of hydraulic oil pump truck testbed， such as reliance on periodic physical inspections and maintenance， low levels of informatization， and insufficient production efficiency， an application development architecture for a hydraulic oil pump truck monitoring system was proposed based on digital twin technology. This architecture integrates data， models， and communication to improved the predictive maintenance level and operational efficiency of the equipment. The research enabled real-time data interaction and fusion between the physical equipment and the virtual model by constructing a digital twin virtual model of the equipment and utilizing the TCP/IP protocol and a unified JSON packet format. On this basis， the system could perform simulation， numerical prediction， fault diagnosis， and early warning for the hydraulic oil pump truck testbed， thereby optimizing the equipment’s operation status.Test results show that the system is able to perform health monitoring and fault diagnosis for the hydraulic oil pump truck， showing broad prospects in the application of aviation testbed.

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.

To improve the calculation accuracy of the overall performance model， a overall performance modeling method for aero-engines with primary and secondary flow integration was investigated. Through research on principles for aero-engine performance calculation， the influencing factors of secondary flow on the primary flow thermodynamic cycle were comprehensively identified. Their mechanisms of action were clarified. A characteristic model of the impact of secondary flow on the primary flow thermodynamic cycle was constructed. Based on the traditional modeling framework， this method innovatively introduced a coupling calculation mechanism for secondary flow rate， energy， and mixing terms with the primary flow thermodynamic cycle. Using this method， an overall performance calculation model was developed for a specific aero-engine. The results show that， compared to traditional models， the proposed method achieves a 1.4% improvement in thrust calculation accuracy， a 1.33% enhancement in fuel consumption rate prediction， and a 2.7% increase in turbine inlet temperature estimation accuracy， significantly optimizing the precision of the overall performance calculation model for aero-engines.

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 of obstacle distribution on the flow characteristics of ultrafine dry powder fire extinguishing agent in confined space，a fluent software was used to establish a two-dimensional transient simulation model of gas-solid two-phase flow in the confined space after the release of ultrafine dry powder extinguishing agent， and the spatial flow characteristics of ultrafine dry powder were simulated under the conditions of different layers of obstacles and spatial locations. The results show that both the layer number and distribution of obstacles have a more significant influence on the spatial flow and distribution of ultrafine dry powder. In the early stage of spraying， the concentration of the area under the middle obstacle is significantly lower than that of the other obstacles， while the side obstacles have a more significant influence on the time required to reach the fully submerged fire extinguishing agent in the space. The number of layers of obstacles has a significant influence on the total flooding state of ultrafine dry powder fire extinguishing agent， single-layer obstacles to a certain extent is conducive to speeding up the confined space to achieve the state of total flooding of fire extinguishing agent， while multi-layer obstacles is just the opposite， and with the increase in the number of layers of obstacles， the longer the time required to reach the state of total flooding.

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 solve the problem of high false detection rates in tunnel fire detection caused by the complexity of tunnel environments based on the YOLOv8n network model， an improved tunnel fire detection algorithm was proposed.First， in the backbone network， the FasterNet network was used for replacement while retaining the original SPPF module to achieve more comprehensive feature extraction； Secondly， in order to improve the detection accuracy of the model for irregular targets in the complex background， the D-LKA attention mechanism was introduced in the C2f module； Finally， Focaler-IoU to optimize the model loss function was introduced， which further reducing the problem of false positives or false negatives caused by distractors. The experimental results show that compared with YOLOv5， YOLOv7 and the original models of YOLOv8n， the accuracy of the improved model is increased by 7.6%， 5.6%， and 3.5% respectively， and the average accuracy means are increased by 8.3%， 7.7%， and 5.1% respectively. Compared with other YOLOv8n-based improved algorithms， the mean average precision of our proposed model is increased by 3.3% and 6.4% respectively.

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.

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.

To improve visual tracking precision for friction stir welding under weld seam occlusion and other interference， a weld seam feature tracking algorithm based on the ECO-HC was proposed. A traditional image processing technology was employed to detect the initial weld seam feature point， while enhancing the sensitivity of the algorithm to abnormal disturbances by introducing a dual confidence assessment mechanism comprising similarity calculation and peak to sidelobe ratio on the basis of the ECO-HC algorithm. Additionally， a trajectory prediction method based on curve fitting was proposed to achieve the relocalization of lost target. Experiments were conducted on aluminum alloy weldments of varying thicknesses. The experimental results show that the mean absolute error of the weld seam tracking system proposed can be maintained within 0.051 mm， which fully meets the precision requirement for weld seam tracking and demonstrates the effectiveness of the algorithm proposed.

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.

To systematically investigate the mechanisms of thermal degradation and damping effects on panel flutter boundaries and responses， an aeroelastic model incorporating thermal degradation and damping terms was developed， followed by a sensitivity analysis of key parameters based on stability criteria. Firstly， based on the von Kármán plate large deformation theory， the Kelvin damping model， and the first-order piston theory， a two-dimensional supersonic panel dynamic equation was established. This equation considered thermal degradation and damping effects. Spatial discretization was achieved using the Galerkin method. Next， the Lyapunov indirect method and the Routh-Hurwitz criterion were used to obtain stability region diagrams for various degrees of thermal degradation. This identified the number and stability of equilibrium points in each region. Finally， the nonlinear ordinary differential equations were solved using the fourth-order Runge-Kutta method to determine the panel’s nonlinear aeroelastic response. This response was analyzed using nonlinear dynamic tools， such as time history plots， phase trajectory diagrams， and bifurcation diagrams. The results indicate that both thermal degradation and material damping significantly reduce the stability region of the panel. Panel thickness also influences the stability region. An increase in the thermal degradation coefficient not only amplifies the panel’s vibration amplitude but also causes the bifurcation points to appear earlier， accelerating the bifurcation evolution process. Furthermore， thermal degradation significantly increases the diversity of panel response types and their sensitivity to system parameters. In addition， material damping effectively suppresses the panel’s quasi-periodic and chaotic vibrations responses.

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.

Aims to elucidate the mechanisms through which digital transformation at the micro level influences enterprises’ new quality productivity，the micro-mechanisms of digital transformation affecting new quality productivity from the perspectives of internal control and external supervision were empirically discussed， using data from A-share listed manufacturing firms from 2012 to 2022. It was found that： corporate digital transformation is conducive to promoting the development of new-quality productivity； Internal control and external supervision positively regulate the process of digital transformation to promote the development of new-quality productivity； The higher the technological level of the enterprise， the stronger the moderating effect of internal control and external supervision； the moderating effect of external supervision is stronger than that of internal control in large-scale enterprises， while the moderating effect of both is not significant in small and medium enterprises； the more competitive the industry is， the stronger the moderating effect of internal control is， and the external supervision plays a role only in the industry with high degree of competitiveness. It is of great significance in deeply understanding the internal logic of digital transformation promoting new quality productivity at the micro enterprise level and provides a basis for enterprises to formulate rational development strategies.

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.

In order to improve the control law of airborne windmilling start for turbofan engines and enhance windmilling start performance and reliability， a specific aviation turbofan engine that utilized a fuel-air ratio control mode for windmilling start was selected as the research object. Based on the results of windmilling start tests conducted on an altitude test facility， the effects of ambient temperature， cold and hot starts， flight altitude， and flight speed on windmilling start performance were analyzed. The results show that a decrease in flight speed has the most significant impact on the increase in starting time， extending it by 89%. An increase in flight altitude has a secondary effect， extending the starting time by 21%. The effects of cold weather and cold starts are relatively small. According to the test results， the correction coefficients of starting fuel-air ratio related to atmospheric pressure， Mach number， and temperature were designed. Therefore， when altitude increases， flight speed decreases， ambient temperature drops， or during cold starts， the fuel-air ratio for windmilling start is increased to shorten the starting time.

To systematically review the research methods for the mesoscale mechanical properties of carbon nanotube-reinforced composites， this paper reviewed mesoscale analysis methods （Mori-Tanaka method， cell model method， homogenization method） and finite element simulation methods （asymptotic expansion homogenization method， Voronoi cell element method，micromechanics finite element method）. The review focused on the random sequential adsorption （RSA） and random sequential expansion （RSE） algorithms for representative volume element （RVE） and their improvements. The results showed that the mesoscale finite element method could effectively obtain the stress-strain field of materials， revealing the correlation between their macro and meso performance. It was demonstrated that the introduction of carbon nanotubes could significantly enhance the interfacial strength and interlaminar properties of epoxy resins and carbon fiber composite，and provides an important theoretical basis for the performance optimization and engineering application of composites.

To solve the problems of cracking， wrinkling， and low precision in aluminum alloy sheet metal parts formed at room temperature， and to achieve low-cost， high-precision forming of fairing components， a study was conducted on deep stretching and pressing forming processes of thin-walled， complex structural components made of low-plasticity， low-strength 2A11 aluminum alloy at room temperature. By combining field experiments and sheet metal forming principles， an analysis of the rubber pad forming process and steel die pressing forming for an aluminum alloy fairing with a wall thickness of 1.0—2.0 mm and a stretching ratio of 0.62 was performed. Through segmented forming and iterative parameter optimization， the influence of parameters such as stretching speed， pressurization rate， and lubrication conditions on the quality of the stretching process was investigated. The impact of the quenching process on the aluminum alloy pressing forming process was studied through heat treatment experiments. This research successfully achieved deep stretching forming of the aluminum alloy fairing with a wall thickness of 1.0—2.0 mm at room temperature， effectively suppressing wrinkling and cracking. Furthermore， the problem of cracking in the stiffeners during pressing was resolved by optimizing the solution heat treatment parameters （temperature： 495—500 °C， time： 35—40 min）. The results indicate that rubber pad forming combined with segmented parameter optimization significantly improves the forming quality of thin-walled aluminum alloy components， and precise control of the quenching process is key to achieving defect-free pressing of the fairing’s stiffener surfaces.

To address the issue of high-pressure rotor seizure after engine shutdown， a fault tree analysis method based on Isograph was employed to identify the causes of the high-pressure rotor seizure. By analyzing physical re-inspection results and performing deformation compatibility calculations for typical seal clearance locations， the root cause of the seizure was determined. Corresponding corrective measures were formulated and verified through engine testing， thereby further enhancing the efficiency of the overall engine test process. This approach can provide ideas and methods for addressing other rotor seizure issues， enabling targeted preventive measures to be taken in the early design stage and refining deformation compatibility theory from an engineering application perspective.

To investigate the surface state of GH4151 alloy after ultrasonic shot peening strengthening and analyze its strengthening mechanism， characterization tests and numerical simulation analysis were conducted. The effects of shot diameter on surface morphology， microstructure， and microhardness distribution of GH4151 alloy under peening intensities of 0.15 A and 0.25 A were explored. The difference between the simulated roughness value and the final test evaluation data is less than 10%， confirming the reliability of the simulation prediction. At a peening intensity of 0.15 A， compared with 1.5 mm shots， the use of 2.5 mm shots results in a reduction of approximately 10.9% in roughness Ra and about 10.4% in roughness Rz. The results show that a higher shot peening intensity enhances the weakening effect on the peaks and valleys. Increasing the shot diameter improves the uniformity of the surface macro-morphology. After ultrasonic shot peening treatment， the plastic deformation layer is obvious， and the dispersion of hardness values along the depth direction is reduced. Both surface microhardness and the depth of the affected layer increase significantly， and the uniformity of the hardened layer is improved.

To address the problems of low resource utilization，high costs and high carbon emissions of traditional single delivery tools，a joint delivery routing problem for electric vehicles and drones with a two-tier system was proposed. It considered factors such as energy consumption and carbon emissions of vehicles and drones during different delivery stages. A mixed-integer linear programming model was established， aiming to minimize the sum of fixed costs， energy consumption costs， and carbon emission costs， subject to constraints including customer time windows， vehicle and drone capacities， and battery capacities. Based on this model， a hybrid genetic algorithm was designed. Initially， an initial population was generated according to a greedy rule， and the destruction and repair concept from large-scale neighborhood search was integrated with the genetic algorithm for solving. The experimental results verify that this hybrid algorithm can effectively solve the 2E-VRPD problem， optimize delivery routes， improve vehicle-drone collaborative delivery efficiency， and reduce delivery costs.

Aiming at the problem of traditional position control ignoring human-robot interaction， a novel omnidirectional mobile lower limb rehabilitation robot was taken as the object， and an adaptive interaction control strategy based on fuzzy admittance control was proposed. Firstly， the robot structure was introduced， which mainly consists of a lower limb exoskeleton and an omnidirectional mobile platform. Then， the kinematic model of the lower limb exoskeleton， dynamic model of the omnidirectional mobile platform， and motion coordination model between them were established for the subsequent control. Then， a sliding mode controller was designed to combine with the exoskeleton kinematic and motion coordination model to achieve trajectory tracking， and a fuzzy admittance controller was designed to adjust gait speed based on human-robot interaction. Finally， a trajectory tracking experiment and an interaction experiment were conducted on a healthy subject， and the results show that the control strategy has good trajectory tracking performance and can adaptively adjust gait speed according to the subject’s motion intention.

To address salt spray deposition in aero engine compressors in marine atmospheric environments， the motion and deposition characteristics of salt spray particles， as well as the effectiveness of thermal cleaning， were systematically investigated using numerical simulation. The deposition characteristics of salt spray with different particle sizes were analyzed using the DPM（discrete phase model）， while the atomization， impingement， and film formation processes of the cleaning liquid were simulated using a coupled VOF-to-DPM model and the Eulerian wall film model. The results show that salt spray deposition is mainly concentrated in the blade pressure surface and root regions， with a maximum total coverage of 31.38%. After thermal cleaning， the total cleaning coverage on the blade surface reaches 32.32%， with the highest coverage observed in the pressure surface of large blades （63.18%）， whereas the suction surface and blade root regions exhibit poorer cleaning performance. Experimental verification demonstrates that the positions where cleaning droplets are predicted to cover in the simulation are all cleaned in the experiments， confirming the effectiveness of the thermal cleaning method established. These findings provide a theoretical basis for optimizing online cleaning strategies.

The performance differences between continuous and discrete variable design methods for topology optimization of infill structures were investigated. Based on local volume constraints， two optimization models were established： a continuous variable model using the SIMP method with the optimality criterion and a discrete variable model using the SAIP method with the canonical relaxation algorithm. Firstly， the fundamental formulations of these methods for topology optimization of infill structures were derived theoretically. Subsequently， numerical examples were utilized to conduct comparative studies from three aspects： optimization performance， clarity of structural topology design， and computational efficiency. Finally，by implementing identical initialization strategies， move limit strategies， and convergence criteria， the external interference in the algorithm was eliminated. The results demonstrate that the optimization time using the SIMP method is approximately 50% of that using the SAIP method； however， the topological designs generated by SIMP exhibit grayscale regions at structural boundaries. In contrast， the SAIP method yields topological designs with clearer boundaries and superior structural configurations， achieving about a 4% reduction in the objective function value. A theoretical reference and basis for the topology optimization design of infill structures is provided.

To address the delamination failure issue in composite laminates caused by interlaminar stress concentration during supersonic flight，a novel sandwich functionally graded material （FGM） panel structure was proposed. First，the nonlinear geometric relationship of the sandwich FGM panel was formulated based on the Kirchhoff thin panel theory and the von Kármán large deformation theory. The nonlinear aerodynamic forces acting on the sandwich FGM panel were simulated using the third-order piston theory. The Hamilton principle was employed to derive the differential equations of motion for the sandwich FGM panel during supersonic flight. Subsequently，the Galerkin method was introduced to discretize these differential equations of motion spatially in both the streamwise and spanwise directions，yielding the corresponding system of ordinary differential equations. Finally，the dynamic response of the sandwich FGM panel was obtained by solving the derived ordinary differential equations using the Runge-Kutta method. The results indicate that，for a constant thickness of the sandwich core，a smaller gradient index n of the core material leads to a higher flutter critical dynamic pressure； When the gradient index n of the sandwich core is less than 1.0，the flutter critical dynamic pressure exhibits a monotonic increase as the thickness ratio of the sandwich core rises； Furthermore，as dimensionless dynamic pressure increases，the motion of the sandwich FGM panel transitions progressively from static stability to limit cycle oscillation.

To enable the cockpit defogging system of a certain type of four-seater electric aircraft to meet the airworthiness requirements.According to CCAR23.773（b）， the initial design scheme of the cockpit defogging system was given.According to the idea of compliance verification of the provisions， method and steps of the ground test for defogging were designed. By carrying out the compliance verification of the defogging system， the initial scheme of the defogging system was improved based on the test results， and the test scheme of the defogging system was optimized. Finally， the verification results of meeting the airworthiness requirements were obtained， and the airworthiness verification work was completed. The cockpit defogging system and verification process studied can not only provide references for the subsequent design and airworthiness of other models， but also play a certain reference role for designers and airworthiness inspectors engaged in related work.

To address the issue of SLAM-based visual relocalization failure in unmanned vehicles under visual degradation conditions，an adaptive collaborative relocalization algorithm was proposed，which combined wheel odometry （WO） with visual odometry （VO）.This algorithm constructed a WO/VO fusion model based on error-state Kalman filter （ES-KF），enhancing the positioning accuracy of the unmanned vehicle’s path planning.To tackle the challenge of insufficient visual feature points that hinder relocalization during unmaned vehicle operation，an adaptive collaborative relocalization algorithm for WO/VO was proposed.The system included a switching mechanism between WO/VO and WO，improving the continuity of the unmanned vehicle’s localization and the reliability of path planning.Experiments were conducted and compared on the developed unmanned vehicle platform under various conditions.The results demonstrate that the ES-KF-based WO/VO fusion method significantly improves localization performance.The absolute trajectory error （ATE） is reduced by 39.1% and 59.2%，respectively，compared to VO-only and WO-only methods，and path overlap is increased by 9.2% and 11.5%，respectively.The algorithm also successfully achieves WO-assisted adaptive collaborative relocalization in visual degradation scenarios.Compared to the extended Kalman filter （EKF） and the unscented Kalman filter （UKF），the ES-KF demonstrates superior performance in both trajectory accuracy and pose estimation stability，significantly enhancing path fusion effectiveness and system robustness.

To address the problem of disconnection between equipment functions and user needs in the context of snow accumulation in urban alleys and streets in northern winters， a functionally optimized small-scale snow removal device was designed by integrating the AHP-QFD-FBS model. The method involved investigating user needs， establishing a user needs analysis model using analytic hierarchy process （AHP）， and calculating demand weights. The weights of user demands were introduced into the quality function deployment （QFD） quality house model to convert them into design demand weights. The function behavior structure （FBS） model was used for structured mapping of design requirements to form the final design solution. The results of the design verification of small-scale snow removal equipment show that the AHP-QFD-FBS model effectively guided the innovative design of the equipment， especially in enhancing the responsiveness of the design to user needs. It also successfully improves the equipment's snow treatment efficiency. This method not only improves snow removal efficiency， but also reduces mechanical losses and user operational complexity， enhancing overall user satisfaction.

The prediction of creep life for turbine blade relies on simulated blade temperature and stress data. However，simulations often simplify the entire turbine disk to a single blade，leading to inaccurate results. In order to investigate the validity of simplified single-blade models and enhance the accuracy of blade creep life prediction，a study on the creep life of turbine blades based on full-scale simulation method was conducted. First，full-scale simulation method for the turbine disk and a simplified single-blade model were established. Then，the blade temperature and maximum principal stress were calculated using the hybrid thermal-fluid-solid coupling method. Finally，the comprehensive equation of thermal strength parameters was employed to predict the creep life of the blade. The results indicate that the relative error in temperature between the single-blade model and the full-scale model does not exceed 2%； the relative error in maximum principal stress between the two is within 8%； however，the relative error in prediction of creep life between them reaches as high as 712.93%. The single-blade model predicts lower temperatures and maximum principal stresses，resulting in a significantly overestimated creep life. These findings demonstrate the necessity of employing a full-scale model to analyze the creep life of turbine blades and lay a foundation for the accurate prediction of their creep life.

To reveal the root cause of the sudden vibration-exceedance fault during the 150h endurance test of a certain type of turboshaft engine， the physicochemical inspection was combined with thermal-mechanical coupling simulation to carry out a full-chain mechanism analysis. The results show that severe transient thermal shocks induced by the anti-icing system’s intervention cause typical γ′-phase rafting degradation and accelerated creep elongation in DZ22 alloy blades. This excessive radial growth then triggered intense rotor-stator rubbing， generating an unbalance exceeding 60 g·cm and ultimately causing a sudden rotor vibration exceedance. Larson-Miller model calculations confirm that the extreme thermal load drastically reduces the local creep life from 150 h to approximately 80.5 h， precisely matching the actual removal timing and location. Based on these findings， a sequential control strategy of “reduce operating condition first， then activate anti-icing” was developed. Bench test results demonstrate that this strategy completely suppresses thermal overshoot at the source， eliminates the risk of rotor rubbing， and successfully ensures the safety of subsequent endurance tests for the same engine type.

In order to improve the accuracy and efficiency of fire monitoring in complex enviroments， an improved YOLOv8n model named YOLOv8n-MAAI for fire detection was proposed. Firstly，by incorporating a multi-head self-attention （MHSA） mechanism into the backbone network， the model’s ability to handle complex scenarios was enhanced， improving detection accuracy. Furthermore， the ADown module from YOLOv9 was integrated into the YOLOv8 architecture， reducing computational complexity through a lightweight design. The adaptive spatial feature fusion （ASFF） mechanism was introduced to form a new Detect_ASFF detection header， filtering conflicting information and improving feature scale invariance. Finally， the Inner-MPDIoU loss function was employed to optimize the training process， enhancing regression accuracy and accelerating model convergence. Experimental results demonstrate that YOLOv8n-MAAI achieves a detection precision of 92.4%， a recall rate of 93.6%， and a mean average precision （mAP） of 94.3%， outperforming both the original YOLOv8n and other popular detection models such as YOLOv5s and YOLOv3-tiny. These improvements provide a more accurate and reliable solution for fire detection， supporting advancements in fire prevention and control technology.

To ensure grasping stability， prevent object slippage， and avoid structural damage， three common grasping models were established for a three-fingered robotic hand， and the critical force during the robotic finger grasping process was accurately solved. In the case of the design of the robot hand and the ideal physical assumption of the object to be grasped， through the force analysis in mechanics， the constraints of the critical force of the robot finger grasping problem were obtained according to the static equilibrium equation， and the optimization model of the critical force of the robot finger grasping was further given. Firstly， the KKT condition was written according to the optimization model， and then the NR function was used to transform it into a smooth equation system， and the value function was further introduced to transform the KKT condition into an unconstrained optimization problem. The dynamic equation system was constructed， and the stability of the dynamic equation system was analyzed， and the relationship between the solution of the dynamic equation system and the solution of the optimization problem was used to solve the critical force problem of robot finger grasping. Finally， a numerical experiment was conducted to verify the effectiveness of the dynamical equation system method.