Digital technology has been widely applied in the development of aerospace products, promoting the continuous development of aerospace system engineering methods. In order to further clarify the development direction of aerospace system engineering in the digital age and promote digital space construction, this article provides an overview of the development and application of aerospace system engineering driven by digital technology. Firstly, the new characteristics of the development of aerospace system engineering in the digital age were analyzed from three aspects: model-based system engineering development, digital intelligence technology empowerment, and commercial aerospace promotion. Then, typical full lifecycle system engineering theoretical models in the digital age were analyzed, and the development of digital technology integration applications was analyzed from the entire development process scenarios, including planning and demonstration, development and design, production and manufacturing, experimental testing, service guarantee, and production management. The characteristics of establishing a full lifecycle development and management digital ecosystem through the integration of technologies such as MBSE, digital twin, digital thread, and artificial intelligence were elucidated. On this basis, combined with the core scenario transformation goals of aerospace product development and management, the future technological development trend of digital era aerospace system engineering is proposed, in order to further promote the improvement of the theoretical and methodological system of aerospace system engineering and provide support for the construction of digital development and management mode.

With the continuous development of launch vehicle technologies and the growing demand for high-density, diversified mission requirements, higher requirements have been placed on rapid iteration of launch vehicle development and closed-loop design parameter optimization. Based on the principles of Model-Based Systems Engineering (MBSE), this paper adopts a data-driven approach to enable collaborative design of multidisciplinary models during the overall closed-loop design process of launch vehicles, demonstrating the engineering feasibility of model-based processes over document ones. Aiming at addressing issues such as prolonged aerodynamic characteristic prediction time and multiple trajectory design constraints in traditional general loop design, the application of artificial intelligence prediction and optimization algorithms significantly enhances the design efficiency of aerodynamic characteristic models and trajectory calculation models, thereby substantially reducing the design cycle of general loop systems. Through actuator invocation, the platform enables the calling of specialized tools and data interaction between models. This ensures both free flow of design data across disciplines during the process and real-time tracking of design data iterations. These achievements reach the goals of "data homogenization" and "change synchronization" throughout the entire loop of the overall design process.

As a representative of complex systems, launch vehicles face the challenges of high-quality, high-efficiency and high-benefit development. Addressing the limitations of traditional document-driven approaches such as complex cross-disciplinary coordinaiton, difficulties in multi-system coupled verification, and low iterative efficiency, the current application status of model based systems engineering (MBSE) methods in complex system development is investigated, and the mainstream MBSE methodology is analyzed. The MBSE application technology research is conducted focusing on the requirements analysis, scheme disign, process verification and other aspects in the development process of launch vehicles. Through scenario-based simulations, the effectiveness of MBSE in improving development quality and efficiency, as well as identifying potential risks is demonstrated. A model-driven framework is proposed for launch vehicle system development, extendable to digital twins and intelligent decision support, showcasing significant engineering value in advancing precision-oriented and agile transformation for aerospace complex systems. Suggestions and prospects are put forward for the development direction of MBSE technology under the new situation, as well as the integration application prospects for launch vehicles.

This study summarizes the MBSE-based digital engineering development practices of manned lunar exploration spacecraft, covering the requirements model developed with SysML, the system design model, and the system verification model developed with Modelica, across three product levels: overall spacecraft, subsystems, and individual components. It distills these practices into a comprehensive digital model system for the entire lifecycle, all levels, and across all product dimensions of spacecraft development. Focusing on system requirements analysis, system design, and verification, the study takes the digital model of manned lunar exploration spacecraft as an example to analyze the fundamental composition of master data in the digital backbone, as well as the transfer processes of master data in the digital backbone across temporal, organizational, and product dimensions. It also examines the mapping correspondence between technical state items of spacecraft products and their representations in digital models, research and test documents, physical products, and the digital backbone. By organically integrating the technical state management elements of products in both the digital and physical domains, the study proposes an integrated MBSE-based digital development process for spacecraft products, providing a technical foundation for effectively controlling the technical state in digital development modes.

To address the low visualization in deep cavity structure assembly, which affects assembly quality, a multi-sensor fusion approach for real-time sensing and precise control is proposed. First, the assembly characteristics of deep cavity structures are analyzed, with geometric features and assembly loads identified as key factors affecting assembly quality. The functional modules and logical relationships of the assembly system are introduced, combining digital twin theory. Next, a sensing study of the assembly process is conducted, utilizing laser and force sensors to effectively capture the geometric and load features of the deep cavity structure. Finally, using assembly feature information as input, virtual assembly and error compensation research is carried out. Through assembly path planning and robot end-effector compliance control, precise regulation of the assembly process is achieved. A sensing and control system is developed based on a digital twin framework. Key technology validation on a specific aircraft’s deep cavity structure demonstrates that this method can effectively sense and control multi-stage feature information, providing an effective theoretical framework and technical solution for high-performance assembly.

Decisions made during the architecture design phase are critical to the development of complex equipment systems, as they often define the performance boundaries and guide subsequent research directions. To address challenges in early architecture design decision-making for complex equipment, such as difficulties in mathematical representation, low efficiency in solution generation, design space combinatorial explosion, and the challenge of balancing the diverse needs of multiple stakeholders, this paper proposes intelligent decision support techniques for complex equipment system architecture design. The proposed framework involves six key stages of architecture decision-making: (1) architecture decision representation based on morphological matrices; (2) system architecture generation driven by the integration of domain knowledge and reinforcement learning; (3) architecture design space reduction using constraint management; (4) multi-stage optimization of large-scale system architecture decisions; (5) multi-objective trade-offs in system architecture considering stakeholder preferences; and (6) digital evaluation and verification of architecture decisions driven by the fusion of mechanism models and data. Finally, a typical case study on the stage separation design of a launch vehicle demonstrates the feasibility and effectiveness of the proposed framework and key techniques, providing theoretical and technical references for the practical application of architecture decision-making in complex equipment systems.

Wind tunnel is the vital facility for aerodynamic evaluation and research, which plays a pivotal role in advancing the development of aerospace vehicles and the construction of an independent flight equipment development system. It is a tangible representation of a nation's scientific and technological capabilities. In light of the ongoing digitisation and intelligence development of equipment, we have outlined the historical trajectory of complex equipment digitisation. With the emergency of the next generation aircraft evaluation requirement, a digital framework for wind tunnel full life cycle research is proposed. Throughout the requirement, design, construction, operation, maintenance, the framework is to solve the current limitation, which include the unstable quality and inefficient design, simple but inefficient maintenance. In the case of low-speed wind tunnels, the typical applications of wind tunnel digital prototypes 1.0 to 3.0 are presented, and the main application scenarios of digital twins, such as wind tunnel state monitoring, wind tunnel virtual test and wind tunnel prognostics and health management, are outlined. Finally, potential research directions of wind tunnel digitisation are discussed, including interdisciplinary-multiscale modeling and silulation, flight performance evaluation and design integration, model and data standard system. Through this research, we hope to provides a suggestion to conduct further development for the construction of a digital control system for the entire life cycle of wind tunnel equipment.

Aiming to address the issues of flexible optical fiber laying path design in fiber optic gyroscopes, which currently relies heavily on manual operation experience, difficulty in controlling optical path stress, and low assembly efficiency, an automatic planning method for low-stress laying path of flexible optical fiber has been proposed, including single-compartment fibers and through-compartment fibers. Based on the set reference information for the laying path, including the starting connection surface, terminating connection surface, laying surface outer circle, and through-compartment hole (applicable only to through-compartment fibers), the automatic planning of low-stress flexible optical fiber laying paths is achieved. Firstly, the low-stress laying path design of the fiber optic cable is carried out based on the bending radius standard of the fiber optic cable, thereby determining the two-dimensional distribution of the fiber optic cable laying path control points. Then, according to the spatial positional relationship between the optical devices and the fiber optic cable laying plane, as well as the through-compartment hole (applicable only to through-compartment fibers), the coordinates of the path control points are discretized in the vertical axis direction. At the same time, adjustments are made to the laying path based on the length of the fiber optic cable; if the fiber optic cable length meets the coiling conditions, coiling operations are performed, ultimately achieving the planning of low-stress fiber optic cable laying paths in three-dimensional space. Based on the above design ideas, an automatic planning system for low-stress laying path of flexible optical fiber has been developed, and relevant practical application tests have been conducted, verifying the effectiveness of the method.

The digital-twin system for the internal mechanical state of Carbon Fiber Reinforced Polymer (CFRP) wing structure, which serves as an effective means for achieving structural health monitoring of CFRP components. By using the real-time mapping between the physical space and the digital space, the dynamic human-machine interaction during the service life of critical structures can be achieved. Addressing the difficult issues in clear the internal mechanical state of CFRP structure during actual service based on four key parts: CFRP wing preparation, mechanical simulation, construction of radial basis function (RBF) surrogate model, and unidirectional data reduction processing. Then, a novel method for constructing digital-twin framework of the internal mechanical state of CFRP wings based on high fidelity proxy model is proposed. Taking the CFRP wing structure as a case study, high-fidelity data obtained from sensors and low-fidelity data derived from simulation are employed in reduced-order processing with one-way reduced-order model, and the RBF surrogate model is utilized to interpolate the stress values at each node. Ultimately, these data are used to train the surrogate model, which then repairs and reconstructs sample points for the wing's digital twin. It is helpful to facilitate the construction of a digital-twin system for the internal mechanical state of CFRP wing, enabling real-time mapping between the physical CFRP wing and its twin model.

During the operation of wind turbines, blade vibration data exhibit significant differences in feature distributions under varying operating conditions and are often affected by noise, making fault feature extraction challenging and accurate health state identification difficult. To effectively address this challenge, this study proposes a blade health state monitoring method based on gramian angular field and multi-head attention convolutional neural network. First, a modal transformation approach based on Gramian Angular Field is employed to encode the one-dimensional vibration signal into two types of two-dimensional image representations: Gramian angular difference field (GADF) and gramian angular summation field (GASF). By using polar coordinate mapping, this method effectively preserves the amplitude and phase characteristics of the time-series signals. Second, a parallel dual-channel Convolutional Neural Network (CNN) is constructed to extract spatial features from GADF and GASF images separately, incorporating depthwise separable convolutions to reduce model complexity. Finally, a multi-head attention mechanism is introduced to perform cross-channel feature fusion, enhancing the expression of critical fault features through adaptive weight allocation.To verify the effectiveness of the proposed method, experimental validation is conducted using real-world data on blade fatigue damage from wind farms, ensuring its applicability and reliability in practical scenarios. The experimental results demonstrate that the proposed method achieves a diagnostic accuracy of 93.7%, significantly outperforming other comparative methods, thereby confirming its effectiveness and superiority in real-world applications.

As the “functional cornerstone” of high-end equipment, the technological level of mechanical transmission directly determines the performance and reliability of critical equipment in strategic domains such as aerospace and humanoid robotics. Enhancing its independent innovation capacity is an urgent requirement for national modernization and industrial upgrading. This paper systematically reviews the current status and trends of cutting-edge technologies in the mechanical transmission field, focusing on five core dimensions: materials, design, manufacturing, testing, and intelligent operation & maintenance (O&M). It identifies key bottleneck problems and core developmental challenges currently constraining deeper technological advancement and industrial upgrading. To break through long-standing technical bottlenecks and dilemmas, this study proposes a breakthrough pathway centered on constructing a synergistic innovation system encompassing the entire chain of materials, design, manufacturing, testing, and O&M. This pathway fosters an innovation-driven ecosystem by integrating Material Genome Initiative-enabled design, independent configuration innovation, digital twin-based process optimization, and closed-loop feedback from intelligent O&M data. Characterized by the synergistic evolution towards " high-end, intelligent, and greening," this new technological paradigm aims to propel the high-end transmission industry towards a strategic pivot from passive substitution to active leadership. It not only focuses on overcoming critical performance bottlenecks such as power density, dynamic accuracy, and service reliability but also deeply integrates artificial intelligence and advanced materials technology to systematically reconstruct the technological system for the innovative development of mechanical transmission. Provide a core technological foundation for the transformation and upgrading of the manufacturing industry.

Flapping-wing aircraft exhibit unique high-lift characteristics, high propulsion efficiency, and exceptional agility, with their overall flight performance critically dependent on the design and functionality of their flapping-wing drive mechanisms. As these aircraft, renowned for their numerous advantages, gain prominence, there is a growing demand for enhanced performance. Researchers worldwide have intensified theoretical investigations and innovative designs of flapping-wing drive mechanisms. A comprehensive analysis is carried out from the perspectives of rotary-driven linkage mechanisms and smart material-driven mechanisms, addressing the current developmental and applicational status of multi-mode hybrid motion in flapping-wing drive mechanisms. Their respective applications in flapping-wing aircraft are systematically examined, their operational characteristics are comparatively summarized, and future directions are projected, including the realization of multi-degree-of-freedom mechanisms, advancements in miniaturization and lightweight architectures, and the progressive diversification of structural configurations facilitated by the exploration and integration of high-performance materials. Through a comprehensive summary and analysis of current flapping-wing drive mechanisms, valuable references are provided for the future design of such mechanisms and the advancement of flapping-wing aircraft.

To address the need for efficient and energy-saving trajectory planning in autonomous loader excavation operations, a multi-objective shoveling trajectory optimization method is proposed based on non-uniform rational B-splines (NURBS). First, a soil-bucket coupling model is established using soil mechanics failure theory, which accurately characterizes the resistance encountered during the excavation process. Subsequently, the soil-bucket interaction is incorporated into the dynamic modeling of the loader’s working device, thereby improving the model’s representation of actual working conditions. Finally, a nonlinear multi-objective and multi-constraint trajectory optimization model is constructed, with both operation time and energy consumption considered as synergistic performance indices. This optimization problem is efficiently solved using a genetic algorithm. To validate the effectiveness and superiority of the proposed method, a high-fidelity mathematical-physical co-simulation platform is developed, and simulation experiments are conducted. The results demonstrate that the proposed approach can generate smooth and feasible excavation trajectories, with hydraulic cylinder velocities and output forces maintained within reasonable ranges during critical stages. The loading process is both efficient and stable, exhibiting good operational continuity.

A double closed-loop control strategy for the wheel-legged mobile platform is proposed to enhance resistance to external disturbances, and it is mainly used to address the difficulty in maintaining platform stability when the body is subjected to strong external perturbations. Firstly, the wheel-end contact force estimator is established by combining the single-leg dynamics model and the recursive least squares method with forgetting factor, dealing with the problem of challenge in obtaining the contact force without ground reaction force sensors. Furthermore, the changes in the additional kinetic energy of the platform's movement in different directions are solved through the motion orbit reference energy method, and based on it, an external disturbance trigger is designed. The linear and angular flexible mass-spring-damping model ideas are used to analyze the mapping relationship between motion parameters such as displacement, velocity, acceleration and equivalent forces and torques in the linear and angular motion of the center of mass of the platform. Considering the influence of the relative position between the wheel end and the center of mass on the virtual force distribution of the legs, the dynamic relationship of the contact force tracking error and the wheel position tracking error is established. Then the double closed-loop control framework of body position closed loop and wheel end force closed loop is built. Finally, simulation and prototype experiment verify the real-time performance and effectiveness of the proposed method.

Non-contact measurement of rotating blades using blade tip timing technology is recognized as an effective method for blade vibration monitoring. However, due to the limitation on the number of sensors that can be arranged in the casing, the vibration signal acquired by the blade tip timing system has a serious under-sampling problem. The current convex relaxation and non-convex relaxation methods do not take into account the important scale invariance of $\ell_0$ norm, which limits the reconstruction accuracy and makes it impossible to obtain the sparsest solution. To solve this problem, a scale-invariant norm ratio function is first introduced to approximate $\ell_0$ norm. For its non-convex and non-smooth properties, a smooth approximation proxy function(Smooth $\ell_p$ over $\ell_q$,SPOQ) is constructed to avoid falling into the local minimum. Then, a sparse representation model of blade tip timing signals is constructed based on the SPOQ function, and the model is solved using a variable metric forward–backward algorithm. The results of blade tip timing simulation and test show that, by comparing with $\ell_1$ regularization and GMC regularization, this method can not only accurately reconstruct the signal amplitude, but also effectively filter out the interference frequency components, making the solution sparser.

Aiming at the problem that the vibration response of some key positions of the rotor system under different working conditions is difficult to obtain in real time through the sensor, a real-time prediction method for the response of the rotor system under variable working conditions driven by digital twin is proposed. Firstly, based on the dynamic model, the vibration characteristics of the rotor system are analyzed, and a high-precision simplified model based on genetic algorithm-BP neural network is established as the data-driven image of the dynamic model, which can improve the response calculation speed of the model and ensure the real-time performance of the digital twin model. Secondly, a model dynamic updating method based on RBF surrogate model is proposed. The genetic algorithm-BP neural network is used to realize the real-time and efficient iterative optimization of the model, which solves the fusion problem of the measured vibration signal and the mechanism model. Finally, the digital twin experimental platform is built to carry out the real-time prediction experiment of the vibration response of the difficult point of the rotor system under different working conditions, and the validity of the digital twin response prediction method is verified. The experimental results show that the digital twin model can realize the real-time mapping of the operating state of the rotor system, and can better solve the problem of difficult point response prediction of the rotor system.

Inclination sensors are widely used in equipment attitude monitoring and other fields. Diamagnetic levitation technology has the characteristics of passive stable levitation, which can break through the limitations of contact mechanical friction and realize the fast and free response of the sensitive element, and has a natural advantage in the design of high-precision inclination sensor. Existing studies mainly focus on the input-output mapping relationship of the sensitive element in the self-stabilized region, resulting in a small sensor operating range (±1.1°). Based on this, an adjustable sensitivity and large range single-axis electromagnetic-Diamagnetic hybrid levitated inclination sensor design method is proposed in combination with optical measurement means. The inclination sensor adopts a new type of sensitive element structure composed of diamagnetic graphite plate and induction coil as the detection unit, realizes the passive and stable levitation of the sensitive element in the non-measuring axis through the layout of the “Opposite1D” type permanent magnet arrangement, and introduces the axial AC induction electromagnetic drive technology so that the sensor working range is no longer limited to the self-stabilized region. The experimental verification, experiments show that the inclination sensor can realize the measurement of ±10.8° angular range, and the sensitivity can reach 1.168 mm/(°); and the sensor sensitivity can be adjusted in the range of 1.168 mm/(°) to 2.623 mm/(°). With the characteristics of frictionless, large range and adjustable sensitivity, it is of great value in the field of precision measurement of small inclination angle.

In order to solve the problem that the dissipated energy of the damping elements of the traditional suspension system for heavy duty vehicles is difficult to recover efficiently, especially under the vertical and large loads and complex driving conditions, a structural design method of Inflatable hydraulic-electric energy regenerative suspension (IHERS) system is proposed to meet the requirements of energy saving and comfort under long-distance transportation of vehicles. The damping characteristics and energy recovery characteristics are analyzed. Considering the body structure of HDV and the comfort of the cab, a five-degree- of-freedom half-car model with IHERS system is established. The working principle of the system under tension and compression conditions is expounded. The energy recovery power of the IHERS system is obtained based on Kirchhoff's law, and the damping force expression of IHERS under different working conditions is derived. The effects of piston diameter, piston rod diameter and hydraulic motor displacement on the amplitude and frequency characteristics of IHERS system in different frequency ranges are analyzed. Based on the vertical acceleration of the body, the dynamic stroke of the suspension and the dynamic load of the wheel, the fitness function is constructed, and the parameters of the IHERS system were optimized by genetic algorithm. The simulation results show that when the vehicle is driving on a C-level road 20 m/s, the energy recovery efficiency of the optimized IHERS system can be increased by up to 34.35%, and the vertical acceleration of the cab can be reduced by 47.96%, which significantly improves the vehicle ride comfort. The research provides a theoretical reference for the development needs of electrification and energy saving of heavy-duty vehicles.

In traditional blade tip timing (BTT) measurement technology, a once-per-revolution (OPR) sensor is typically used as a reference to obtain the ideal time of arrival (ToA). The measured actual ToA is then compared with the ideal ToA to calculate the blade tip vibration displacement. However, in practical applications, due to the limited space inside the engine, it is often difficult to obtain a true or virtual rotational reference for vibration calculation. Moreover, the computation of the ideal ToA introduces additional errors. Under variable rotational speed conditions, speed fluctuations can cause the calculated blade tip vibration displacement to exhibit trends or steady-state offsets, which severely affect subsequent vibration analyses. To overcome these challenges, this study proposes an OPR-free method that does not require a rotational reference or the computation of ideal ToA to obtain vibration velocity. The method relies on a pair of BTT sensors and the measured actual ToAs, enabling the estimation of blade tip vibration velocity. By replacing traditional vibration displacement with vibration velocity, the proposed method minimizes computational errors and uncertainties in BTT measurements while maintaining accurate identification of blade vibration parameters. More importantly, vibration velocity provides a better characterization of high-frequency components, laying a foundation for high-frequency vibration identification. Finally, based on the intrinsic relationship between vibration displacement and velocity, the blade’s natural frequency can be directly determined without any prior knowledge of engine orders.

A hollow-type traveling wave ultrasonic motor that can be applied to the extreme environment of space is proposed for the low rotational speed, large speed ratio and high stability operation requirements of the low-speed frame servo drive of the control moment gyro (CMG). Firstly, the dynamic simulation analysis is conducted on the proposed hollow-type ultrasonic motor, the modal and harmonic response analysis of the stator of the hollow-type ultrasonic motor is carried out, and the influence of the key dimensions of the rotor on the contact stress distribution of the hollow-type ultrasonic motor is explored. Secondly, the prototype of the proposed hollow-type ultrasonic motor is fabricated. The vibration characteristics of the stator and the mechanical output characteristics and speed stability of the prototype are tested in a conventional environment. The experimental results show that the stator can be excited the rotating traveling wave, and the mechanical output performance of the prototype can meet the requirements of low-speed frame servo drive of the CMG. Finally, in order to evaluate the adaptability of the prototype to the application environment of the CMG, a relatively comprehensive space extreme environment test is carried out for the first time. The electrical characteristics, mechanical characteristics, temperature rise characteristics, and speed stability of the prototype are tested in a composite environment of vacuum and variable temperature. The experimental results show that the prototype can operate at low speed with load for a long time with a vacuum degree less than 1×10^-3 Pa and a temperature range of -10～50 ℃, meeting the technical indicators required for the low-speed frame servo drive of the CMG, verifying the application potential of the space hollow-type ultrasonic motor in the low-speed frame of the CMG.

To solve the problem of pipeline vibration, a kind of built-in grid particle damper is proposed to improve the traditional particle damper's poor damping effect under large excitation. The vibration characteristics of the pipeline are analyzed based on the finite element method. The second and third order natural modal frequencies exist in the adjustable speed range of the fan, and the control process of the pipeline vibration is simulated by multi-body dynamics and discrete element joint simulation. The reliability of the simulation results is verified by the experimental platform of pipeline vibration control. The results show that when the particle diameter is 6 mm, the built-in grid particle damper has better damping effect. When filled with 6 mm stainless steel, zirconia, and aluminum alloy particles respectively, stainless steel particles are found to exhibit the optimal damping effect. When the particle filling rate is 90%, the built-in grid particle damper can reduce the vibration of the pipeline at the second and third mode frequencies by 53% and 54%, respectively. The energy dissipation mechanism of the internal grid damper and the non-grid particle damper is compared. It is found that the particle velocity vector in the internal grid damper is more regular, and the kinetic energy, energy consumption and collision times of the particles are more frequent. It is verified that the internal grid particle damper has better damping effect at high excitation level. In order to exclude the influence of the mass of the damper itself on the vibration reduction effect, the equal mass control is adopted to verify the effectiveness of the particle vibration reduction effect.

Superconducting magnetic levitation bearings, which have the advantages of non-contact, low energy consumption and long life, have been applied in mechanical systems such as flywheel energy storage and transport vehicles. Superconducting magnetic levitation bearings can generate magnetic field much higher than traditional magnets, resulting in more significant dynamic stability problems. It is necessary to conduct research on the influencing factors and action rules of the dynamic stability of superconducting magnetic levitation bearings. An electromagnetic, thermal and mechanical coupling numerical model of HTS magnetic suspension bearings is established, and the optimized structure to improve the background magnetic field and suspension capacity is introduced. The vibration response characteristics of fully superconducting magnetic bearings, hybrid stator magnetic bearings and magnetic bearings with optimized parameters for rotor bulks are studied. The dynamic parameters such as levitation forces-displacement relationship, temperature rise and natural frequency of the system under free vibration, harmonic and pulse excitation are analysed. The influence of external excitation on the overall stability of the system is discussed. It lays a theoretical foundation for the application of full superconducting hybrid stator maglev bearings.

A theoretical model for predicting the nonlinear damping characteristics of foam-filled all-composite honeycomb-core sandwich panels (FF-ACHCSP) is presented. Firstly, the theoretical framwork of the structure is established by combining Reddy’s high-order shear theory with Hamilton's principle. Subsequently, the energy equations of the FF-ACHCSP structure are solved by the finite element method, and the nonlinear damping is expressed using the complex modulus method. Finally, a comprehensive theoretical model is developed, enabling the determination of natural frequencies, mode shapes, modal damping ratios, and frequency response curves of the FF-ACHCSP structure. To validate the accuracy of the theoretical model, a vibration testing system is set up, and experimental specimens are prepared for vibration testing. The results from both approaches agree well, confirming the accuracy of the theoretical method. Finally, to further optimize the structure, this study investigates the influence of filler density, honeycomb cell wall thickness, and wall width on the damping characteristics of the FF-ACHCSP structure. The theoretical model proposed accurately predicts the damping characteristics of the FF-ACHCSP structure, providing guiding suggestions for the practical application of this type of structure.

With the continuous development of generative AI technology, vertical-oriented AI generative design has become a new paradigm，whose trust relationship in human-AI team work has a significant impact on the innovation, efficiency and quality of design results. However, the current related research lacks a complete and systematic discussion. Therefore, in order to clarify the trends, hotspots and methods of the research related to the trust relationship in design for human-AI collaboration, the influencing factors of trust are defined by clustering and analyzing the literature from the development of research on trust. Based on the design field, a trust level model for human-AI collaboration in design is constructed, the research content and architecture of the three aspects of technology, interaction and experience are systematically explored. The key technologies of trust measurement, calibration, repair, decision-making, and evaluation are summarized. Research trends and perspectives of human-AI collaboration trust in design are presented in terms of theory, methods, technology, systems, and practice, which can provide references for future related research.

In the current vast and complex data environment of electromechanical products, it is challenging for R&D personnel to obtain effective support for green design throughout the entire product lifecycle due to personalized features such as professional background and design experience. To address this issue, proposes an active knowledge pushing method based on the dynamic characteristics of personnel in green design. Firstly, constructs a green design knowledge context model based on green performance indicators of electromechanical products throughout their lifecycle and the characteristics of R&D personnel, providing a data foundation for subsequent knowledge pushing. Secondly, based on this model, the dynamic characteristics of R&D personnel in the design process are further analyzed. By matching the dynamic characteristics of personnel with variables such as utilization rate, timing, and similarity of green design knowledge, a method for knowledge association and active pushing based on dynamic characteristics is proposed. This ensures that designers receive optimal green design knowledge support according to their specific needs. Finally, taking a specific XGA model aerial work platform as an example, the paper effectively analyzes and pushes knowledge sets for two designers by integrating dynamic characteristics—such as designer profiles, design knowledge, and timing information—along with green design knowledge pushing enabling tools. This supports the product's lightweighting and greening processes in green R&D, validating the effectiveness of the proposed method.

Considering the complex coupling relationship between mechanical, electrical, and control parameters of electric drive system, and aiming at its variable operating conditions and multi-directional performance requirements, a collaborative optimization design method of "machine-electric-control" parameters of electric drive system is proposed. Firstly, based on the reduction model of permanent magnet synchronous motor, the motor power loss calculation model is also established, and the power loss calculation model of the total electric drive system is constructed combined the power loss model of motor and gear transmission. Moreover, considering the actual driving conditions of vehicles, the comprehensive loss evaluation method of electric drive system under driving cycle is established. Then, the dynamic model of the electric drive system is established by the lumped parameter method to obtain the dynamic response of the electric drive system, and the radial force on the stator teeth of the motor is considered comprehensively to realize the comprehensive evaluation of the dynamic performance of the electric drive system. Finally, taking the total mass of the electric drive system, total energy loss under cyclic driving conditions, torque fluctuation and radial electromagnetic force fluctuation as comprehensive optimization objectives, the dynamic synchronous optimization of mechanical-electrical-control parameters is realized. The optimization method proposed in this paper, in which, the internal nested optimization is included, realizes the cooperative optimization of mechanical, electrical and control parameters, provides the design theory and method for high performance electric drive system.

A novel topology optimization method for the design of coated structures infilled with multiple materials is proposed, where a new material interpolation model for the topology description is developed based on the ordered SIMP scheme. With the introduction of two special Heaviside projections into the two-step filtering and projection procedure, the external coating and the substrate region can be well identified by using several modified density fields. Then, the material distribution of the multi-material infilling is obtained by multiplying the infill identification field with the piece-wisely projected design variables and optimized via the mathematical programming algorithm under the ordered SIMP framework. Using an eroded density field and its original field, the uniform thickness of the external coating can be well controlled. The proposed approach for optimizing coated structures with multi-phase infill materials is easy to implement due to its implementation relying on those frequently-used filtering and projection operations. Besides, without introducing any additional design variables, the method developed in this paper inherits the advantages of the ordered SIMP method and has great calculation efficiency and stable iteration performance. With the consideration of several issues such as different coating thicknesses and different design parameters, several 2D numerical examples are studied to demonstrate the effectiveness of the proposed approach, as well as a 3D example. The optimization results illustrate that the method developed in this paper is effective for the design of coated structures infilled with multiple materials and the advantages of considering multiple infill materials are also validated.

The calibration accuracy of the electron gun directly affects the forming accuracy of the electron beam selective melting process. Aiming at the shortcomings of the traditional manual calibration method in terms of accuracy and reliability, an automatic calibration method based on the mean value estimation model of circular hole is proposed, and the estimation error of the model under different radius of circular holes is analyses. The calibration error of the deflection voltage of the electron beam gun is calculated under the conditions of different beam spot diameters, differences between the long and short axes of the beam spot, the angle of deflection of the beam spot's long axis, and the distance of the line, and the experiments on automatic calibration of the deflection voltage of the electron beam gun are designed to validate the reliability and calibration accuracy of the method. The reliability and calibration accuracy of the method are verified. The experimental results show that compared with the manual calibration, the automatic calibration method proposed reduces the mean straightness error of the X-direction scanning track from 0.3983 mm to 0.1154 mm, and the mean straightness error of the Y-direction scanning track from 0.5818 mm to 0.0951 mm, with an overall reduction of more than 60% in the automatic calibration error, which verifies that the method has a higher reliability and calibration accuracy than the manual calibration method. higher reliability and calibration accuracy than the manual calibration method.

An active yarn feeding system tailored for the weaving process of three-dimensional woven composites is proposed. The structural design and device assembly are completed, and the tension generation mechanism during active yarn feeding is analyzed. By employing an error-proportional compensation method, the theoretical and actual yarn feeding lengths are effectively stabilized. The coupling effects of weaving speed, extrusion pressure, and speed ratio on yarn tension are explored through response surface methodology, and a second-order polynomial model is used for fitting to achieve stable tension control during weaving. The optimization model, aiming to minimize the tension variation rate, is used to determine the optimal process parameters. Results indicate that the error-proportional compensation significantly reduces yarn feeding errors, with all deviations controlled within 0.3 mm and an average error reduction to 0.49%. The extrusion pressure and speed ratio of the active yarn feeding system exhibit coupled effects on the yarn tension variation rate. Utilizing the response surface experiment and regression model, the tension fluctuation of the flexible-oriented three-dimensional weaving system is controlled within 10%.

To address the challenges in glioma radiotherapy, including difficulties in controlling drug dosage, uneven radiation dose distribution, poor outcomes from single treatment, and high risks of repeated surgeries, a novel glioma radiochemotherapy microcavity capsule is designed to achieve full coverage irradiation of the tumor. First, Monte Carlo simulation software GEANT4 is used to calculate the radiation dose distribution of the microcavity capsule in a water phantom, analyzing radial dose and anisotropy at different angles and exploring the three-dimensional dose distribution to investigate the dosimetric characteristics of the structure. Then, finite element simulation is employed to analyze the dynamic response of the microcavity capsule structure, assessing its feasibility and safety for clinical application. Finally, LiF thermoluminescent dosimeters are used to experimentally measure and validate the radiation dose distribution in the water phantom. The Monte Carlo dose distribution simulation results showed that the surface absorbed dose rate of the microcavity capsule is high. As the radial distance increased, the absorbed dose rate rapidly decreased in all directions. Additionally, due to the influence of its shape, the absorbed dose rate exhibited a spiral distribution. The finite element simulation results indicated that the maximum stress and displacement of the implanted microcavity capsule fluctuated cyclically under total physiological load, with a maximum stress of 0.422 MPa and a maximum displacement of 0.272 mm per cycle. When the maximum stress is less than 6 MPa, the deformation remained below 15% of the capsule's length, meeting safety requirements for intracranial irradiation. Experimental validation results showed good agreement between the simulation and measured data, demonstrating that the microcavity capsule can provide long-term, stable low-dose irradiation, enabling localized high-dose radiotherapy.

Microlens array elements are widely used in advanced imaging systems such as infrared detection and photoelectric sensing due to their unique functions such as beam shaping, equalization, diffusion and microfocusing. The mass manufacturing of its components mostly uses injection molding and molding processes to accurately copy the microstructure on the surface of the mold to the surface of the component. Due to the defects such as knife lines on the surface of the mold obtained by ultra-precision and close cutting, the further improvement of the performance of the component is limited, and subsequent polishing treatment is required. In order to solve the technical problem that the current microlens array polishing technology is difficult to take into account the surface shape accuracy and surface quality, a non-contact conformal polishing method based on shear thickening principle for microlens array molds is proposed, a full-diameter polishing tool for spherical molds is designed, the distribution of surface stress and slip velocity of the mold during polishing is analyzed, and the polishing performances of the Ni-P alloy microlens array is studied. The results show that the proposed shear thickening conformal polishing has excellent polishing performances for the microlens array structure. After polishing, the defects such as knife lines on the surface of the microlens array are significantly removed, the high-frequency error is significantly reduced, and the rainbow pattern phenomenon is significantly suppressed. The surface roughness of the mold decreased from the initial 2.01 nm Sa to 1.07 nm Sa, and the shape accuracy before and after polishing changed by less than 25 nm.

As an important part of flexible micro and nano electronic devices, high-precision flexible transparent circuit has been widely used in 5G/6G flexible transparent antenna, wearable devices, transparent electric heating film, flexible transparent electronics and other fields. However, the high efficiency, low cost and flexible manufacturing of high density circuits with high resolution, high optoelectronic and mechanical performance, especially copper based circuits, is a major problem in current research. To address this challenge, a new method for manufacturing high-precision flexible transparent copper based circuits by combining electric field driven micro 3D printing and wet etching technology to achieve additive/subtractive composite manufacturing is proposed. It not only achieves low-cost and flexible printing of high-resolution and high-precision etching masks, but also further reduces the linewidth of ultra-fine circuits through rapid etching processes.The basic forming principle and key technology realization are described. Through experiments, the influence of main process parameters on circuit morphology and performance is revealed, studied the influence law of etching speed and explored the controllability of two stages in the etching process (fast etching and side etching), and precisely controlled the side etching process. Combined with optimized printing parameters and precise control of side etching speed, the manufacturing of flexible transparent circuits with a minimum line width of 2.4 μm and a minimum line spacing of 4 μm is achieved. The resistivity of the typical sample is 4×10^-6 Ω·cm, when the light transmittance is as high as 87.65% (550 nm wavelength, including substrate), the sheet resistance is only 3.58 Ω/sq, simultaneously possessing excellent mechanical stability and electric heating performance. The prepared high-density flexible transparent interdigital electrode has excellent sensitivity and can detect dilute sulfuric acid solutions with a minimum concentration change of only 1 nmol/L at a frequency of 100-10 000 Hz. This method provides a new solution for high efficiency and low cost manufacturing of high density copper based flexible transparent circuits, and shows a good industrial application prospect.

To study the intrinsic mechanism by which elliptical ultrasonic vibration milling (EUVM) enhances the subsurface mechanical properties of GH4169, comparative experiments are conducted under both EUVM and conventional milling (CM). The cutting characteristics are investigated under varying cutting parameters. Subsurface microstructural changes are analyzed using material characterization techniques, and the effect of machining conditions on subsurface mechanical behavior is revealed. Experimental results indicate that the cutting force of EUVM, under wet cutting, is overall higher than that of CM, up to 16.76%. Similar force peak positions suggest that the determining factors affecting the cutting force are the cutting parameters rather than the vibration parameters. EUVM produces uniformly arranged wavy micro-textures on the machined surface, resulting in increased surface roughness, up to 0.781 μm. An increased number of low-angle grain boundaries and higher dislocation densities in the subsurface grains are observed, attributed to the enhanced dislocation motion and interaction induced by the vibrational and velocity effects of EUVM. Compared with CM, EUVM-induced microstructural evolution contributes to a maximum increase of 48.4% in work hardening and 76.98% in compressive residual stress. However, the gap in dislocation density between EUVM and CM is reduced at higher process levels, primarily due to the weakening of ultrasonic vibration effects at elevated cutting speeds. The results provide valuable guidance and reference for the fatigue-resistant manufacturing of GH4169.

High-precision physics experiments, aerospace engineering and other high-tech and industrial fields have a significant demand for complex surface parts. A particular type of them is commonly designed with unrotational-symmetric features such as sudden changes in local curvature, non-uniform low-frequency undulations, and sharp contour variations. Slow tool servo turning is an effective method for creating these surfaces. However, due to the high sensitivity of unrotational-symmetric complex surfaces to factors within the tolerance limits of conventional accuracy, even minor process differences can have a significant impact on machining accuracy, making it challenging to maintain consistent accuracy for the whole region. To address the challenges of quality control in the slow tool servo turning of unrotational-symmetric complex surfaces, a contour deviation consistency controlling method for turning toolpaths is proposed. This approach constructs a normal equidistant offset surface of the unrotational-symmetric complex surface as the target for toolpath planning, and generates discretized toolpaths for PVT interpolation based on this surface. A local sparsification and densification strategy is developed for cutter location points constrained by PVT interpolation deviations, and an iterative optimization method is proposed to adjust cutter location points while maintaining consistency of contour deviations between adjacent points. A machining verification experiment is conducted using a rotating wave surface abstracted from the sealing ring of a nuclear main pump as a typical sample. The results show that the produced sample using the proposed method can reduce profile error by 32.61%, root mean square profile error by 36.36% and surface roughness by 28.03% compared to conventional equal parameter method, significantly improving the machining accuracy and surface quality for slow tool servo turning of complex surfaces.

In fields such as aerospace and automotive manufacturing, adhesive bonding technology is widely used for connecting lightweight metals like aluminum alloys due to its technical advantages, including light structure and simple manufacturing. This paper uses an electrochemical method to texture the surface of aluminum alloy to achieve better adhesive bonding performance. The corrosion characteristics of aluminum alloys in different solutions are systematically studied, and the effects of different current parameters on the microstructure of the aluminum alloy surface and its adhesive bonding performance are further analyzed. The results show that in NaNO₃ solution, a loose corrosion layer easily forms on the aluminum alloy surface, which significantly reduces its adhesive bonding strength. In NaCl solution, chloride ions accelerate the removal of the initial oxide film on the aluminum alloy surface, forming a more compact new oxide layer. Particularly under a current of 5 A, the surface roughness reaches its highest value, and the maximum tensile load of the adhesive joint increases by more than twice compared to the untreated surface. Additionally, the discrete element method was used to simulate the crack initiation and propagation during the tensile process of the adhesive joint under the 5 A condition, revealing the fracture mechanism of the adhesive joint transitioning from interface failure to mixed-mode failure. Finally, based on the experimental and simulation results, a fracture mechanism model for the adhesive joint of aluminum alloy surface electrochemical texturing treatment is established. This research provides an effective new method for achieving efficient pre-treatment of aluminum alloy surfaces and high-performance adhesive bonding.

This study employed milling and drilling processes to conduct hole-making experiments on Al/AFRP(Aramid fiber reinforced polymer，AFRP) and Al/Carbon fiber reinforced polymer(CFRP) co-cured materials, investigating the impacts of process parameters on hole quality and surface defects, while performing a mechanism analysis in conjunction with cutting forces. By comparing the cutting performances of the two co-cured materials, the study aimed to elucidate the different modes of fiber material fracture and surface formation mechanisms under various processing methods. The results indicated that the axial force during the milling process is more dispersed, which helps to reduce delamination damage and matrix peeling defects in the hole-making process of carbon fiber composites, thereby enhancing chip fragmentation and minimizing wall scratches. This makes milling more suitable for processing Al/CFRP co-cured materials. In contrast, under drilling conditions, the cutting process begins at the drill tip, which concentrates the material removal area and effectively reduces burr accumulation defects in aramid composites, resulting in a 30% improvement in hole quality. Consequently, drilling proves to be more effective for processing Al/AFRP co-cured materials. The research findings demonstrate that at a feed rate of 20 mm/min, the average cutting force for Al/FRP co-cured materials is reduced by 67.25%. Notably, the maximum reduction occurs during the milling of Al/AFRP co-cured materials, reaching 76%. This study reveals the differences in cutting mechanisms for various materials, providing a theoretical foundation for the machining of novel co-cured materials and expanding the application range of composite materials.