In this work, the research progress on diffusion bonding of titanium alloys and fatigue crack growth (FCG) behavior of their laminates are briefly reviewed. Furthermore, the microstructural evolution and FCG characteristics at the interfaces of titanium alloys subjected to diffusion bonding are summarized. Firstly, the application background and advantages of superplastic forming/diffusion bonding technology are outlined, as well as some auxiliary technologies to improve the diffusion bonding interface quality of titanium alloys, such as the interlayer addition, thermohydrogen treatment, pulse current heating, and surface modification. The microstructures and mechanical properties of the bonded interfaces are shown based on the diffusion bonding of titanium alloys and titanium alloys with other alloys. The strong dependence of microstructural evolution on the alloy elements and interdiffusion ability of elements at the bonded interfaces is clarified. Diffusion bonding process can be used to fabricate the laminates of the same and different alloys, and the shape and distribution of the bonded and unbonded zones at the interfaces can be flexibly controlled. Finally, the diffusion bonding laminates with the same or different titanium alloys can be used to reduce the FCG rate. Therefore, the fatigue damage tolerance of titanium alloy components is optimized.

This paper aims at the chatter problem in thin-walled parts, which is dominated by the flexibility of the workpiece. A chatter suppression method for the piezoelectric intelligent thin plate was presented based on the PD–sliding mode control (SMC) coupled algorithm. Firstly, an active control algorithm with only displacement measurement required was designed. The uncertainty of system parameters and the external disturbance were treated by the SMC theory. In addition, a dynamic compensator was established to approximate and compensate the unknown cutting state online. To overcome the sensing error and system delay, a time-space-varying PD control method was further coupled in the SMC.
The time-varying functions of control parameters were fitted with the help of ABAQUS simulation. Finally, a set of active control devices was designed for thin-walled workpiece. The experimental results show that the milling chatter of thinwalled parts can be suppressed effectively under active control, which verifies the feasibility of the proposed method.

Polymer-derived route is an important method for the preparation of high-performance ceramic materials, especially in the fabrication of continuous fibers and fiber reinforced ceramic matrix composites (FRCMC), which has significant advantages in terms of composition and microstructure modulation. Based on adjustable multi-element contents and controllable chemical bonding structure of precursors, polymer-derived SiBCN ceramics are discovered with various structural features and special properties. In recent years, the development of structure-function integrated SiBCN ceramics has received extensive attention. In this paper, we mainly focused on the research progress of precursor-derived SiBCN ceramics from 2016 to the present, firstly briefly introduced the common features of precursor-converted SiBCN ceramics, and then summarized the important advances in four areas: SiBCN ceramic precursors and pyrolyzed products, continuous SiBCN ceramic fibers, SiBCN matrix composites, and functional SiBCN ceramics, raised research prospectives and priority proposals in the final section. This tourism review is expected to provide a reference for the research and development of SiBCN ceramics, and to promote the application of SiBCN-based ceramic materials.

The continuous development of high-performance aero-engines has put forward higher requirements for the comprehensive performance of titanium alloys. The composition design of titanium alloys based on the mechanism of different alloying elements is an important means to achieve titanium alloy modification. For the increasingly complex titanium alloy system for aero-engines, the interaction mechanism and precise design of different elements are extremely difficult. Traditional alloy design methods based on Mo equivalent or density functional theory cannot meet future needs, while machine learning has become a feasible and efficient theoretical method. The basic principles and methods of titanium alloy machine learning is introduced in this review, and the latest research achievements on the element design and processing optimization of titanium alloy for aero-engines through machine learning are summarized. This review focuses on the comparison of the characteristics and advantages between different machine learning models in predicting mechanical properties and high-temperature oxidation performance. Finally, a prospect is proposed for the future research methods for designing titanium alloy components in aero-engines based on active learning frameworks. It is supposed that the combination of Mo/Al equivalent design with machine learning, and the simplification design of complex multi-element alloy materials, are important development directions in the future.

For the problem of fast solution of the anti-tetrachiral negative Poisson’s ratio honeycomb out-offace deformation, a fast solution method using numerical fitting is proposed. First, the out-of-plane deformation of the honeycomb was solved by finite element analysis software, and the result data were divided into training data and validation data. Then, the least squares method was used to fit the solution results. According to the characteristics and dimensional analysis of the out-of-plane deformation of the honeycomb, a three-parameter fitting equation was constructed. And the fitting curve on the symmetry axis of the honeycomb was obtained. Next, the fitting parameter results and the size parameters of the honeycomb were fitted again. The relationship between the size and the deformation curve of the honeycomb was obtained. Then, the deformation of the honeycomb under other sizes predicted by using this relationship was compared with the validation data. In addition, the out-of-plane deformation of the two-stage non-uniform honeycomb was also studied. The fitting function was constructed by using the fitting results of the previous uniform honeycomb and the Logistic function. And the fitting results were compared with validation data. The results show that the prediction results of the fitting equation are in good agreement with the simulation results. This numerical method can be applied to the deformation prediction and design of anti-chiral honeycomb.

The rapid development of additive manufacturing technology (AM) has brought opportunities for the design, preparation, and application of high-performance aluminum alloys and Al matrix composites (AMCs). In this review, the application status and prospects of AM in Al-based alloys/composites were addressed. The effect of process parameters on the microstructure and mechanical properties were analyzed in detail. On this basis, the formation mechanism and control strategy of defects in Al-based alloys/composites during the AM process were reviewed. It was found that the wide semi-solid range, high thermal conductivity, high laser reflectivity of Al, high heating/cooling rate, and the resultant great temperature gradient during AM jointly lead to the formation of defects, e.g., coarse grains, pores, and micro cracks. By introducing nanoparticles to increase the nucleation rate, stabilize the molten pool, and increase the laser absorption rate, the density of defects can be significantly reduced. In the future, a deeper understanding of defect control mechanisms,  composition regulation, and reinforcement distribution in AM technologies is needed, as well as the development of special Al powders for AM. This review provides a reference for the development and application of high-performance Al-based alloys/composites fabricated via AM.

The shape-position tolerance of the joint surface of each component of aviation products is very high.  The traditional manual and semi-automatic processing methods have low efficiency and poor accuracy, and it is difficult to meet the task requirements. To improve the alignment accuracy of the tail cabin and the middle and outer wings of a large aircraft wing, this paper proposes a solution based on reverse engineering technology to combine automatic measurement technology with CNC machine tools for milling holes on the joint surface. According to the process requirements, the laser scanner is used to realize the method of contour size detection, reference extraction, milling amount calculation of large space parts, which is verified by experiments. The results show that the system significantly improves the assembly accuracy and efficiency of the tail cabin and the middle and outer wing, and has high application value and popularization significance. At the same time, it also has a positive role in promoting the digital design and processing technology research of other complex structural parts.

Aiming at the problems of difficult springback control and poor forming accuracy during the CNC bending of aero-engine pipes, the CNC bending process experiments of 0Cr18Ni9 and 1Cr18Ni9Ti stainless steel pipes were carried out. The springback data of different pipe diameters, wall thicknesses, relative bending radius and bending angles were obtained. A springback prediction model of pipes during CNC bending was established through machine learning and genetic algorithm. After genetic algorithm optimization, the prediction error distribution of the model was reduced from [–0.741°, 0.771°] to [–0.310°, 0.314°]. On this basis, an intelligent prediction and compensation system for springback of pipes during bending was developed. It was used for the compensation on process parameters and springback control of typical full-size aero-engine pipes during CNC bending. After testing, it was found that the maximum angular deviation of the full-size aero-engine pipes compensated by the system was 0.358°, which fully met the actual production accuracy requirements, and significantly improved the CNC bending accuracy and production efficiency of the aero-engine pipes.

Particle reinforced metal matrix composites have been widely used in automotive, aerospace and military and others fields due to their excellent properties such as high modulus, high strength and good wear resistance. However, in the cutting process of it, due to the presence of reinforced phase particles, the tool wear is serious, leading to the formation of debris and machined surface defects. Finite element simulation can realize the analysis of stripping and breakage of particle, and give the other microscopic details. It is an important supplement to the research of cutting experiment. In this paper, the research progress of three-dimensional finite element simulation of machining of particle reinforced composites is reviewed. The latest research of geometric model, interface model, constitutive model, meshing and boundary condition processing is introduced. The existing problems and development direction are discussed. The research results are helpful to promote the research of three-dimensional finite element simulation of cutting of particle reinforced composite, better reveal the cutting mechanism, and provide theoretical basis for the optimization of process parameter.

Verticality of hole is strictly required during the assembly of aerospace components. In order to ensure verticality when using automatic equipment such as robots to make holes, it is necessary to measure the normal direction of each machined hole in place. The existing normal measurement methods of the workpiece surface are difficult to meet the measurement requirements of the workpiece surface with large curvature. Through line laser scanning, point cloud data reflecting the detailed information of the local surface of the workpiece can be obtained. On this basis, a method for calculating the surface normal of the workpiece with large curvature is proposed. First studied the method of plane fitting to local point cloud data to obtain the surface normal through PCA (principal component analysis), then selected some typical curvatures, generated point cloud data through simulation, and analyzed the change of normal fitting error law. The effectiveness of the above method is verified by experiments. The results show that when the selection range of point cloud is less than 12 mm, the normal fitting error of cylindrical test piece with diameter of 50 mm can be guaranteed to be less than 0.219°.

Using a digital light processing (DLP) projector and an industrial camera as main hardware platform, developed an integrated prototype system of 3D measurement and positioned indication, namely i-Guider. The working principle and key techniques of i-Guider system were described. A set of sinusoidal phase shift fringes were loaded in the memory of the DLP projector, which was taken as an inverse imaging device. The camera-projector system was calibrated by using a planar board with the aid of structured-light projection. A method was proposed to automatically generate the 2D projecting images of pre-defined 3D indications, such as specific curve features and operation instructions on the CAD model of the workpiece. The projecting images were sent to the projector via HDMI to achieve accurate positioned indications on the real workpiece. A positioned indication experiment on aircraft skin riveting was performed, in which i-Guider system had exhibited excellent performance. Experiments show that the positioned indication error is within 0.25 mm.