This study investigates the coupled aerothermal and structural response of a hypersonic morphing vehicle undergoing configuration changes across a wide speed regime. Numerical simulations were conducted at Ma 5 and an altitude of 24 km to evaluate surface heat flux and pressure loads under varying wing folding angles (0°–90°) and angles of attack, using computational fluid dynamics (CFD). Based on the transient heat conduction equation— governed by the principle of energy conservation and Fourier’s law of heat conduction— the aerodynamic loads obtained from CFD were applied as boundary conditions in a finite element analysis to perform thermo-structural coupling simulations of the wing structure under representative morphing states. Results show that wing folding significantly intensifies localized aerodynamic heating and stress concentration: At a 90° folding angle, the peak heat flux at the wingtip reaches 1309.9 kW/m2, and the equivalent structural stress increases to 506 MPa. Nevertheless, with appropriate thermal protection design, both thermal and mechanical safety requirements can still be satisfied. This work provides preliminary engineering analysis for evaluating the multi-state coupled characteristics of hypersonic morphing vehicles.
The extensive application of industrial robots has become one of the key characteristics of smart manufacturing. With the accelerated advancement of intelligent manufacturing, robotic smart manufacturing is emerging as a crucial driver for industrial transformation and upgrading. In this context, this paper focuses on the challenges faced by the aviation industry, including high precision, multi-variety, variable-batch, and large-scale customized production, and systematically reviews the development status of robotic smart manufacturing in this field. The study highlights key technological advances such as high-precision perception and environmental modeling, precision manufacturing and control of individual robots, multi-robot collaborative and optimization, human–robot collaboration and hybrid operations, and digital twin-enabled manufacturing control. Furthermore, typical engineering practices and application results of robotic smart manufacturing in representative aircraft assembly scenarios are analyzed. This work aims to explore new-quality productive forces for the aviation industry under the paradigm of robotic smart manufacturing and to provide new pathways and momentum for its intelligent transformation and sustainable upgrading.
Flexible skin is one of the key technologies for morphing structures in aircraft, requiring not only the ability to undergo large deformations but also the capability to carry significant normal aerodynamic loads. A metal skeleton-enhanced rubber composite flexible skin structure is an effective solution, where the skeleton reinforcement support structure must possess both large deformation and normal load-bearing characteristics. This paper focuses on U-shaped honeycomb skeleton structures, establishing theoretical models for the relationship between the tensile deformation of the skeleton structure and the maximum strain, as well as the deflection of the structure under normal force. By combining the SLSQP optimization algorithm, the geometric dimensions of the skeleton are optimized based on the performance requirements of the skin under specific operating conditions, using out-of-plane deflection as the boundary condition and minimum strain as the optimization objective. The optimization process yielded the optimal geometric dimensions that meet the requirements for deformation and load-bearing capacity. Results show that, regardless of the initial values of the optimization model, the optimization process consistently converges to the same optimal solution, validating the feasibility and effectiveness of the size parameter optimization of U-shaped honeycomb skeleton structures.
In morphing aircraft, achieving smoothness, continuity, and seamless connection of wing surfaces during deformation remains a major challenge in structural design. To address the issue of wrinkling that frequently occurs in conventional flexible skins under compression, this paper proposes a corrugated flexible morphing framework with displacement constraints. Firstly, considering the bending-compression coupling inherent in traditional corrugated structures, a novel corrugated configuration is designed by introducing displacement constraints at critical locations, which effectively suppresses compression-induced deformation during bending. Taking into account the anisotropic characteristics of the structure, it is simplified into a beam-element model, and a chain-based algorithm is developed to establish a largedeformation computational method under displacement constraints. The mechanical responses of the structure under flexible skin constraints and uniformly distributed loads are further analyzed. Finally, a prototype of a morphing trailing edge based on the proposed corrugated structure is fabricated and experimentally validated. The results demonstrate that the trailing-edge structure achieves large deformation of up to ±20°, while maintaining good surface smoothness and continuity throughout the morphing process, with no local buckling observed in the flexible skin. This design provides a new theoretical basis and engineering pathway for the design and optimization of flexible trailing-edge structures.
To enable real-time perception of the shape of morphing trailing edge and support closed-loop control of wing profiles, this study focuses on a finger-joint-style variable camber trailing edge. A shape reconstruction method based on fiber Bragg grating (FBG) sensors is proposed. First, an FBG deformation sensor was designed to connect with the trailing edge ribs via supporting components. Using laser tracking and other measurement techniques, the geometry data and key-point coordinates of the trailing edge were recorded at different deflection angles, establishing a mapping relationship between the strain data measured by the FBG sensor and these parameters. The deformation of the trailing edge structure is modeled as a three-joint serial robotic system. By leveraging known dimensional information of the trailing edge, the joint rotation angles are calculated via inverse kinematics using key-point coordinate data. Forward kinematics is then employed to determine the current configuration of the trailing edge, achieving shape reconstruction. The relative error between the reconstruction and the actual trailing edge deflection rotation angle is 1.57%, which confirms the feasibility and accuracy of this approach for real-time shape perception of flexible large deformation wings.
Aerospace technology demands ever-higher standards for aircraft performance, safety, and intelligence. Traditional rigid sensors struggle to achieve real-time, in-situ measurement of multifunctional and large-scale sensory signals, and the extensive deployment of discrete rigid sensors has a non-negligible impact on the aircraft’s structure and its surface flow field. The advent of flexible electronics offers a new opportunity to overcome the bottlenecks of conventional sensing technology. Its inherent characteristics— such as being flexible and conformable— have fostered the development of new concepts like the “SensorCraft”. The core principle involves deploying large-scale, distributed sensor networks across the aircraft’s surface and within its structure for real-time, multi-modal perception of both the aircraft’s state and the external environment. This review systematically covers the key principles and representative device/system designs of flexible electronics for sensing surface flow characteristics (e.g., pressure, shear stress, airflow) and for perceiving aerodynamic forces and thermal conditions (e.g., strain, temperature). It also discusses the applications of flexible electronic skin in active actuation domains, including drag reduction, anti-/de-icing, and electromagnetic control. Combined with the burgeoning field of artificial intelligence, the functionality and intelligence of flexible electronic skins can be further expanded. Finally, the paper provides an outlook on the main challenges and future directions in this field, aiming to promote the development of embodied intelligence for SensorCraft.
With the advancement of smart materials and advanced manufacturing processes, bio-inspired morphing aircraft have progressively overcome the limitations of morphing mechanisms in terms of weight and energy efficiency, sparking growing research interest among domestic and international aviation industries and academic institutions. Morphing aircrafts face multiple design challenges during development, including requirements for maintaining smooth and continuous aerodynamic surfaces, control efficiency, anisotropic load-bearing and deformation stiffness characteristics, as well as flight controllability. This paper comprehensively reviewed the structural design and key technologies for morphing mechanisms in large-scaled aviation platforms and small-scaled UAVs. The synergistic integration of compliant architectures, intelligent material systems, and advanced fabrication techniques was emphasized to advance the development and implementation of morphing mechanisms. Key technologies such as mechanical metamaterials, smart actuators and sensors, flexible skins, and compliant mechanisms were analyzed, along with their main challenges and unresolved issues, to prospect future development trends in morphing aircraft technology.
We prepared YSZ-based composite coatings with CaF2/Al2O3 as additives using atmospheric plasma spraying (APS). We prepared two groups: Group A (YSZ + 6% CaF2 + 6% Al2O3) and Group B (YSZ + 12% CaF2 + 12% Al2O3), and investigated their tribological performance and lubrication mechanisms across a wide temperature range (room temperature –1100 ℃ ). Results show that Group B, with higher additive content, exhibited lower room-temperature Vickers hardness (337HV0.5) than Group A (423HV0.5), but achieved a significantly reduced friction coefficient of 0.22 at 800 ℃. At low temperatures (≤400 ℃), mechanical strength dominated friction behavior, while at high temperatures (≥600 ℃), CaF2 actively reduced shear strength through ductile-to-brittle transition, synergizing with Al2O3 to dynamically form oxide glaze layers that enhanced lubrication. At 1100 ℃ , Group A developed a stable glaze layer via Ca diffusion and CaZrO3 formation, lowering the friction coefficient to 0.16, whereas Group B failed due to excessive additive content.
The gluing quality of thermal protection tile on hypersonic vehicles directly affects thermal insulation performance and flight safety. Current gluing process predominantly relies on manual operations strictly following established procedures. However, their dynamic complexity and strictly time-sequenced characteristics lead to frequent occurrences of operational sequence errors and component mis-assemblies, necessitating intelligent temporal behavior recognition and monitoring methods. To address these challenges, this study first defines the temporal behavioral characteristics of tile gluing process. Subsequently, we construct the SimA3D model for temporal behavior recognition by integrating the SimAM parameter-free attention mechanism into the C3D network architecture. A cosine annealing dynamic learning rate strategy is introduced in conjunction with an adaptive AdamW optimizer to enhance model convergence stability. Furthermore, a triple collaborative data augmentation strategy is proposed to expand sample diversity and input data complexity, effectively alleviating overfitting issues in small-sample temporal behavior recognition scenarios. Experimental results demonstrate that the SimA3D model achieves 98.32% recognition accuracy for gluing process behaviors, and the accuracy is improved by 19.9 percentage points over the baseline C3D network.
High-silicon aluminum alloys, due to their excellent thermal conductivity and high specific strength, are crucial in aerospace thermal protection structures. However, the silicon particles within these alloys complicate machining processes. Longitudinal-torsional ultrasonic vibration-assisted minimum quantity lubrication (LTUVAM & MQL) cutting has proven effective in enhancing the machinability of homogeneous materials, but its application in high-silicon aluminum alloys requires further study. In this research, single-factor experiments were conducted to investigate how different cutting parameters affect cutting force, temperature, and workpiece surface quality during LTUVAM & MQL milling of Al–50% Si (mass fraction) alloys. Comparisons were also made between the machining performances of LTUVAM & MQL, minimum quantity lubrication (MQL) milling, longitudinal-torsional ultrasonic vibration-assisted milling (LTUVAM), and conventional milling (CM) for Al–50% Si alloys. The results indicated that LTUVAM & MQL offered the best cutting performance, followed by LTUVAM and MQL, with CM being the least effective. This study provides valuable insights and important references for improving the machining efficiency and quality of high-silicon aluminum alloys.
Under the background of “dual-carbon” goals and high-quality development, green manufacturing technology is an important direction in recent years. For aircraft products, structural assembly operations account for about half of the workload during the entire aircraft, and it has a direct impact on the final performance, quality and reliability of the products. Improving the greenness degree is crucial for the transformation and upgrading of the production process and the guarantee of product quality. Firstly, green assembly technology was defined as an assembly method system that ensures the geometric accuracy and service performance of the airframe structure. Two core supporting technologies, i.e. assembly processes and quality control, and tooling equipment were proposed, with typical green characteristics such as low consumption, low emissions, high efficiency and high benefits. Secondly, evaluation indicators for structural green assembly technology were constructed. Specifically, it could analyzed from the correlation of assembly efficiency, assembly quality, assembly cost, assembly safety and the greening of tooling equipment. Then combing with specific assembly links, with the perspective of assembly process data driving on virtual pre-verification
Addressing the issues of slow dynamic response and poor measurement accuracy of airflow temperature sensors used in aero-engines, an analysis and real-time compensation of steady-state and dynamic errors were conducted for a certain type of turbo-exhaust temperature sensor selected for aero-engines. Based on the physical model of the airflow temperature sensor, a numerical simulation of thermal-flow coupling was performed. A dynamic real-time compensation model based on a second-order compensation system was proposed and validated through experiments in a calibrated hot-wind tunnel. The results showed that the simulation results were basically consistent with the sensor time constants obtained from the calibrated hot-wind tunnel tests, verifying the accuracy of the simulation model. Meanwhile, after realtime compensation, the steady-state and dynamic errors were significantly reduced, suppressing the overshoot phenomenon of dynamic response. At an incoming total temperature of 772.95 K and an incoming Mach number of 0.400, the minimum reduction in steady-state error was 0.1 ℃ , with a decrease of 98.6%. At an incoming step temperature of 403–594 ℃ and an incoming Mach number of 0.402, the maximum reduction in dynamic error was 63.9%.
