Carbon fiber reinforced polymer (CFRP) composites are widely used in aerospace applications owing to their high strength-to-weight ratio. Despite their advantages, mechanical fastening remains essential due to manufacturing limitations and structural load transfer requirements. Interference fit technology shows significant potential for enhancing the strength and fatigue life of mechanicaly fastened CFRP joints. However, the inherent brittleness and low interlaminar strength of CFRP materials pose significant challenges to its application. To address these issues, this paper reviews the research progress on interference fit connection technology for CFRP composite materials, both domestically and internationally. It analyzes the fatigue life enhancement mechanisms associated with interference fit connections, introduces the primary process methods used for achieving interference fits in CFRP composites, and discusses the key factors influencing interference fit connection quality. Based on this review, future development trends and application prospects of CFRP interference fit connection technologies are discussed.
Extreme operating environments pose significant challenges for the next generation of aerospace materials. Traditional materials design methods, characterized by low efficiency, high costs, and long development cycles, have severely hindered the advancement of aerospace materials development. The development of new aerospace materials calls for innovative, highly efficient, and precise research and development paradigms. Artificial intelligence (AI) technologies, particularly the rapid advances in machine learning and deep learning, have emerged as powerful tools for aerospace materials research, markedly enhancing the efficiency of new material designs and the accuracy of performance predictions. This paper provides a systematic review of the research progress of AI in the aerospace materials field. It begins with an introduction to AI-assisted multiscale computational simulation and intelligent experimentation, then comprehensively presents surrogate model-accelerated materials optimization methods and a new materials design process centered on large-scale models. Detailed case studies are also presented on AI applications in the research and development of alloy materials, composite materials, and metamaterials. Finally, the paper summarizes the advantages and challenges of AI-assisted aerospace materials design and offers insights into future research directions.
Aerospace equipment such as aircraft, satellites, and space stations are exposed to multi-field coupling environments including extreme temperature fluctuations, atomic oxygen erosion, ultraviolet radiation, and the penetration of local corrosive media (such as Cl–), which can cause mechanical damage and chemical failure of surface protective coatings. Traditional repair methods, due to insufficient precision and poor adaptability to working conditions, are difficult to meet the protection requirements of complex equipment. Self-healing coatings, designed based on biomimetic repair mechanisms, trigger targeted repair responses in damaged areas, providing an innovative solution for extending the lifespan of equipment. This paper systematically introduces the technical characteristics of exogenous and intrinsic self-healing coatings, and focuses on discussing the engineering application breakthroughs of self-healing coatings in typical aerospace environments (such as thermal shock-resistant coatings for engine hot-end components and atomic oxygen-resistant coatings for space station modules) and special working conditions (such as aircraft body protection in high-humidity and high-salt environments at coastal airports). It reveals the cross-scale action mechanism of “damage perception-repair triggering-performance regeneration”, and points out that environment-adaptive repair, in-situ monitoring integration, and multi-mechanism synergy will be the core directions for future development in this field.
During the coating preparation process, differences in the morphology, size, molten state, flight path, and spreading behavior on the substrate of the feedstock result in a certain degree of undulation within and among the adjacent coating layers. Changes in the geometry of the interface of the coatings make the morphology at the interface more complex, showing irregular and inhomogeneous structural characteristics. It also further makes the stress distribution at the interface uneven, leading to unpredictable failure of the self-healing TBCs at the interface in the subsequent service process, which in turn leads to the warpage or delamination failure of the entire coating. Finite element software was used to simulate the effect of the variation of the surface morphology on the residual stress which is inside the coating and at the interface. By establishing the cosine ideal interface model, it is found that when the wavelength L of interface Ⅰ and interface Ⅱ increases, both the maximum S22 tensile stress and compressive stress of interface Ⅰ and interface Ⅱ decrease. When the amplitude A of interfaces Ⅰ and Ⅱ increases, the stress is affected by both interface roughness and interface buffer stress. Varying the phase offset d between the peaks at the upper and lower interfaces, it is found that the microstructural characteristics of interface Ⅰ have a greater influence on the tensile stress at the peaks of interface Ⅱ . When the valley of interface I faces the peak of interface Ⅱ, this morphology pattern can reduce the maximum tensile stress of interface Ⅱ by 25.7% and avoid excessive stresses at interface Ⅱ. Further, the failure mechanism of the coating is systematically investigated, which provides a more comprehensive theoretical guidance for the optimal control of the interface of the self-healing thermal barrier coatings and the optimal design of the processing technology.
As the service environments of aerospace equipment become increasingly complex and extreme, traditional epoxy resin coatings face technical bottlenecks such as microcrack propagation and deterioration of protective performance. Self-healing technology endows the epoxy resin coatings with damage-healing capability, thus can significantly reduce the risk of failure. This review summarizes the design principles and recent advancements in intrinsic and extrinsic self-healing epoxy resin coatings, analyzes the reversible repair bonding mechanisms of dynamic covalent and non-covalent bonds, and discusses the repair-enhancing principles of carrier-based extrinsic healing technologies such as microcapsules and organic framework structures. Furthermore, challenges including insufficient tolerance to strong radiation and high friction, inadequate repair energy supply, and limited damage-sensing capabilities in aerospace applications are addressed, along with prospects for future development.
With the growing demand for lightweight, intelligent, and long-life aerospace equipment, self-healing functional composite coatings (SHFCs) have become a critical technology to address extreme environmental challenges, owing to their dynamic damage-repair mechanisms and multifunctional synergy. This article systematically reviews the classification, repair mechanisms, and functional applications of self-healing coatings in aviation. SHFCs are categorized into extrinsic and intrinsic types: Extrinsic coatings employ microcapsules or hollow fibers to store healing agents, enabling physical filling or chemical repair of damage; Intrinsic coatings rely on dynamic covalent bonds (e.g., Diels–Alder bonds, disulfide bonds) or non-covalent bonds (e.g., hydrogen bonds, metal coordination) to achieve repeated self-healing through molecular chain reorganization. Furthermore, synergistic design strategies for functionalized SHFCs are highlighted, including corrosionresistant self-healing coatings, superhydrophobic self-healing coatings and conductive/electromagnetic shielding self-healing coatings. Future research should focus on optimizing the responsiveness of dynamic chemical bonds, resolving large-scale manufacturing bottlenecks, and expanding applications in extreme environments such as high temperatures and radiation, thereby providing innovative solutions to enhance the reliability and intelligent development of aerospace equipment.
The assembly accuracy of thin-walled cylindrical parts in flight section of the aircraft is affected by multidimensional factors. As the initial source of assembly deviations, geometric errors directly influence the error transmission and accumulation characteristics of the assembly chain, serving as the foundation for systematic error modeling and regulation. This paper proposes an assembly error analysis method for thin-walled cylindrical parts based on small-displacement torsor theory. By mathematically modeling the geometric tolerances of key features of thin-walled cylindrical parts using smalldisplacement torsor theory and characterizing assembly deviations with homogeneous transformation theory, an assembly error propagation model for thin-walled cylindrical parts is established. The Monte Carlo method is employed to calculate and verify the qualification rate of assembly gradients through a combination of numerical computation and simulation analysis. The results show that the qualification rate obtained from simulation analysis differs by merely 1.25% from the theoretical calculation, validating effectiveness of the proposed model. By adjusting the tolerances of key assembly features, the qualification rate of thin-walled cylindrical parts assembly is improved from 90.90% to 99.90%. The theoretical method proposed in this study provides a reliable theoretical basis and practical reference for engineers in tolerance design.
Aiming at the poor stability caused by temperature variation of aircraft assembly equipment, the spatial position of assembling equipment at different temperatures was measured considering the factors such as tooling structure design and assembly site environment. Based on statistical analysis of data, the position data of tooling at different temperatures was compared with those at periodic check and thermal expansion deformation of the equipment was obtained. The key factors causing poor measurement stability of the tooling were explored, and the corresponding solutions and control methods were put forward. According to the improved control method proposed in this study, when the temperature change is within 5 ℃ , overall deformation of the assembly tooling can be controlled within the tolerance range required by assembly, verifying effectiveness of the proposed optimization measures for stabilizing measurement of tooling and providing reference basis for measurement accuracy and precision of aircraft assembly tooling.
Assembly accuracy is crucial to the working performance of precision machinery, which is affected by the surface profile errors of parts in the manufacturing process and deformation under the action of assembly force. Hence, this study proposes an assembly accuracy analysis method that integrates the surface profile error of parts and deformation under force. Firstly, a small-displacement torsor model is used to model the pose error and a shape error model is constructed by combining the basis function superposition method, and a comprehensive surface error model is established by introducing a Gaussian function to generate random noise. Subsequently, a finite element method is used to analyze deformation of parts under force conditions and its influence on assembly pose, and non-uniform rational B-splines (NURBS) are used to fuse and reconstruct the surface shape and part deformation, generating a surface model of the part that simultaneously considers the surface profile error and force deformation. Finally, based on this model, the fit state between surfaces is evaluated by combining the nearest projected point method, and the assembly accuracy is then calculated by an optimization algorithm. The results of 1000 simulation experiments on planar bolted joints and interference fits of column surface show that different assembly forces or overloads affect the final assembly accuracy; the proposed method is able to carry out effective evaluation and provide guidance for actual assembly.
Bolted joints are extensively utilized in aviation, aerospace, railway, and automotive engineering, where accurate control of preload is essential to ensure the structural integrity and operational safety of assemblies. To accurately measure the bolt preload, a bolt preload accurate measurement system was designed and developed based on the ultrasonic acoustoelastic effect, combined with the ultrasonic time-of-flight (TOF) accurate measurement technology. A refined theoretical model was first established to quantify the relationship between bolt preload and the variation in ultrasonic TOF. Subsequently, a high-voltage spike pulse excitation circuit was designed to effectively drive the ultrasonic transducer. A transmit/receive switching module and a cascaded amplification circuit were developed to obtain distinct echo signals. To achieve high-resolution temporal measurement, a method combining coarse and fine time conversion based on a time-todigital converter (TDC) chip was proposed. A dedicated hardware/software platform was implemented for ultrasonic TOF acquisition inside bolts. Finally, calibration experiments on M12 and M14 bolts were conducted using a universal testing machine, and a linear correlation between bolt preload and ultrasonic TOF variation was established. Experimental results validate that the proposed system achieves a preload measurement error of less than 5% when preload is greater than 15 kN. Moreover, the measurement error decreases as preload increases.
To solve the problems associated with titanium alloy joining, this study examines the fatigue behavior of TA1 titanium alloy single-lap clinched joints. Dynamic response data and strength degradation tests were conducted to track the variations in natural frequency and residual strength with increasing fatigue cycles. The cyclic ratio was utilized to quantify the correlation between natural frequency changes and strength degradation, establishing a model to predict the joint’s fatigue life and damage progression. Based on the natural frequency change and strength degradation index model, the service state calculation model of TA1 titanium alloy clinched joints is established to realize the prediction of residual strength and residual life of the joints. The results show that the natural frequency change and the strength degradation show similarity in the damage stage, which corresponds to the different degradation stages of the joint under fatigue service. The joint service state calculation model realizes the prediction of the current remaining strength and remaining life of the joint by collecting the instantaneous natural frequency, and the model is found to have good accuracy through experimental verification.
High-frequency pulsed arc welding is an effective technique for optimizing the microstructure andproperties of weld joints. Currently most researches focus on arc-induced ultrasonic effect under ultrasonic pulses. To determine the effect of high-frequency pulsed arc at non-ultrasonic frequency on the nickel-based alloy weld microstructure, high-frequency pulsed tungsten inert gas (TIG) welding which is of low-ultrasonic frequency was employed to investigate welding characteristics of Inconel 690 (Ni–Cr–Fe) alloy. The characteristics and microstructure features of regular TIG welding and high-frequency pulsed TIG arc welding were systematically compared and analyzed. The results demonstrate that a pronounced arc compression effect occurs under high-frequency pulsed arc conditions, accompanied by a significant increase in arc pressure. The primary dendrite growth is inhibited, resulting in homogeneous growth orientation of dendrite, while the secondary dendrite spacing exhibits minor variation (approximately 3.6 μm). Moreover, the element distribution among dendrites of weld region is notably homogenized, with a significant reduction in Cr-depleted area. This study provides theoretical insights into optimizing welding quality of nickel-based alloys using non-ultrasonic frequency highfrequency pulsed welding.
Superalloy castings such as aero-engine blades, turbine rear casings, and guides are core components of aero-engines. It is still difficult to manufacture castings with fully qualified size even though the material composition is completely known, which has become a challenge for independently developing aero-engine superalloy castings. Among all, investment casting is the main forming method of complex superalloy castings. Hence, this review comprehensively examined the development of investment casting technology for superalloys and analyzed casting defects such as shrinkage and compromised dimensional accuracy in the investment casting process. Additionally, the progress of domestic and foreign development in rapid prototyping of investment casting for aero-engine superalloy castings was introduced. Finally the research status of intelligent casting of aero-engine superalloy castings at home and abroad was summarized, and the development trend of precision forming technology for aero-engine superalloy castings was prospected.
