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In range gate pull off (RGPO) jamming scenarios, conventional multiple target tracking algorithm can not effectively distinguish the RGPO deception from real target measurements, resulting in track mis-initialization, increased tracking error, and tracking discontinuity. This paper proposes an information-assisted multiple hypothesis tracking (IA-MHT) algorithm to solve the above problems. The IA-MHT algorithm utilizes amplitude and phase information of radar measurements to distinguish between true and false measurements of targets. Furthermore, the algorithm adjusts the calculation method of global association hypothesis probabilities and track scores, which improves the tracking performance under clutter and RGPO interferences. Simulation results show that the IA-MHT algorithm can effectively distinguish the RGPO deception measurements and obtain superior data association performance compared to the conventional MHT algorithm.

Facing the increasing complexity of aerial combat environments and challenges to the survivability of air platforms from new combat methods, it is necessary to adopt new hard-kill methods to counter advanced air-to-air missiles. In order to improve the success rate and efficiency of launching air-to-air missiles to intercept incoming missiles as a hard kill method, this study proposes intelligent maneuvering strategies for aircraft platforms and missile interception strategies based on reinforcement learning. Firstly, this paper designs the missile threat assessment technology, constructs the simulation environments, and determines the strategy model state and reward function. By setting various attack angles and positions of incoming air-to-air missiles and training maneuvering and intelligent interception strategies under different aircraft platform postures, this paper achieves active interception of incoming targets and effective maneuvering of the aircraft platform. Experiments show that compared to the average escape probability of 5.8% in operations research game strategies, after using maneuver and interception strategies based on reinforcement learning, the average escape probability can increase to 56.8%; Meanwhile, the utilization rate of interceptors has increased by approximately 13.3%, and the response time has remained within 24 ms. The designed strategy can adapt to different numbers of incoming missiles, can significantly improve the survival ability of the carrier platform and the success rate of intercepting incoming missiles. This study can support continuous optimization in a high-dimensional state space of air combat.

The safety of the pyrotechnic and power components of air-to-air missiles under braking and inertial running out conditions is one of the key factors that restrict the launch of air-to-air missiles on aircraft carriers. How-ever, there is no quantitative method for evaluating the safety of ammunition under braking and inertial running out conditions in practical applications. Based on the FLL ignition engineering criterion, relying on standard part test of large sample and whole missile braking and inertial running out test of small sample, a safety evaluation method of braking and inertial running out for ammunition is established, and the technical issue of braking and inertial running out for ammunition safety that can not be quantitative evaluated is resolved. An example of evaluating computation is showed together with the data from braking and inertial running out test, and the evaluation results are in good agreement with the actual test findings.

The maritime kill chain constitutes the core of the current joint maritime combat system, representing the practical application of the OODA loop in the context of informationized warfare. It embodies the operational mechanism of the joint combat system, where information flow dominates energy flow in a closed-loop operation. Determining the critical nodes of the maritime kill chain is the prerequisite for achieving comprehensive maritime dominance. Currently, the assessment of key nodes within maritime kill chains employs theoretical analysis and complex network methods. Complex network analysis techniques, which often utilize a node-by-node deletion approach to evaluate node importance, suffer from issues such as low search efficiency and limited applicability to small-scale systems. This paper takes the NIFC-CA system as an example to construct a typical maritime kill chain model. The importance of kill chain nodes is ranked using a complex network assessment method of integration centrality, and key nodes are identified. Additionally, graph theory and network analysis tools from Python’s Network library are utilized during the assessment to significantly enhance the computational efficiency.

Space reconnaissance has become an important part of modernized combat system, and is the key to obtaining the information dominance in advanced technology warfare and then mastering the initiative on the battlefield. Taking the US military space reconnaissance system as an instance, this paper combs the development status from four aspects: space optical imaging reconnaissance system, space radar imaging reconnaissance system, stationary orbit space signal reconnaissance system and variable orbit space signal reconnaissance system. Combining with the application examples of the US military, it analyzes the technology utilization from the central network, peacetime-to-wartime transformation, joint spying and preliminary reconnaissance, and it summarizes the US military space reconnaissance technologies from four aspects: the collaborative technology of heterogeneous reconnaissance network, high-speed transmission technology of intelligence data, high-resolution penetrating imaging technology, high-precision target positioning technology. Finally, this paper analyzes the development trend of space reconnaissance from five aspects: the mi-niaturization of space reconnaissance satellites, integration of reconnaissance networks, anti-jamming and anti-destruction of reconnaissance systems, integration sharing of reconnaissance information and intelligentization of information analysis and decision making, so as to provide references for the construction, application and development of future space reconnaissance systems.

After multiple batches of production, the product process and quality control have been gradually improved and matured. As an important means of inspecting the quality stability of batch production, the sampling proportion of environmental routine test should be appropriately reduced, in order to reduce product consumption, shorten inspection cycle and reduce the occupancy of test resources under the promise of ensuring inspection quality. At present, most of the sampling schemes for the routine test are based on the former products and would not be adjusted once determined. After analyzing that GJB 179A can’t be directly applied to missile’s routine test, drawing on the concepts of GJB 179A and GB/T 2828.1 for continuous batch sampling inspection adjustment, according to GB/T 26823 and the missile routine test conditions, referring to the practices of the United States and others, a routine test sampling scheme based on credit principle is proposed. That is, after the success of multiple routine tests, the sampling size of subsequent batches can be reduced.

A strong tracking cubature Kalman filter(STCKF) method is proposed to overcome the challenges of insufficient nonlinear approximation capability and decreased tracking accuracy of traditional filtering algorithms in dealing with complex maneuvering targets. Firstly, models for snake maneuver and barrel roll maneuver are developed based on the maneuvering characteristics of fighter aircraft evading air-to-air missiles. Secondly, strong tracking filter(STF) is introduced to enhance the ability of cubature Kalman filter(CKF) to handle sudden changes in system states and other uncertainties. Then, STCKF is applied to estimate the motion parameters of missile terminal guidance target, and its effectiveness is validated through comparative simulation analysis with CKF, unscented Kalman filter(UKF), and particle filter(PF). Simulation results indicate that STCKF has enhanced robustness and adaptive capabilities, especially when the target maneuver suddenly changes, its tracking error is reduced by about 10% compared to CKF, which can meet the high precision and rapid response requirements of air-to-air missile terminal guidance.

Angle estimation of coherent source has always been an important challenge in radar angle measurement. Based on the assumption of uniform array, some mode space-based decoherence algorithms is proposed to solve the problem of target angle estimation under coherent interference conditions. However, the above algorithms have poor adaptability to composite arrays. In the present work, a decorrelation algorithm based on matrix cyclic reconstruction is proposed for coherent multi-source angle measurement in composite arrays. By utilizing the spatial filtering characteristics of antenna outside the circular array, it effectively solves the problem of coherent source angle estimation when the number of sources exceeds the number of elements. The simulation results show that the proposed algorithm can effectively solve the angle measurement problem of coherent sources under composite array antennas, and its angular resolution performance is better than traditional algorithms.

Addressing the challenges of unclear mission scenario definition and insufficient intent prior information utilization in the trajectory prediction process for high-speed and high-maneuverability glide vehicle, a trajectory prediction method for high-speed and high-maneuverability glide vehicle based on mid-terminal guidance handover point identification is proposed. Firstly, a mission scenario involving the gliding of high-speed and high-maneuverability vehicle towards multiple typical guidance handover points is constructed. A quasi-equilibrium glide guidance method is employed to generate trajectory datasets. Secondly, a guidance handover point recognition method based on long short-term memory network is proposed, utilizing tracking data to construct feature sequences for preliminary classification of glide trajectory. Finally, the self-attention mechanism is introduced to improve the feature extraction performance of sequence-to-sequence prediction networks, and encoder-decoder method is employd to predict the classified glide trajectory in the long term. Simulation results show that the trajectory prediction method based on mid-terminal guidance handover point identification exhibits high accuracy. For prediction times of 120 s, 180 s, and 240 s, the trajectory errors remain within 18.77 km, 36.91 km, and 57.75 km, respectively. Compared to directly utilizing a deep learning mo-del for prediction, the proposed prediction method demonstrates a reduction of 37.61% in average prediction error and 37.34% in maximum prediction error within a prediction time of 240 s.

In 2023, world military powers have invested heavily and actively promoted the development and actual combat application of air-to-ground missiles. This paper summarizes the latest development trends of typical foreign air-to-ground missiles, such as American AGM-158 Joint Air-to-Surface Stand-off Missile (JASSM), Stand-in Attack Weapon (SiAW), AGM-183A hypersonic missile, AGM-182A Hypersonic Attack Cruise Missile(HACM), the UK’s “Spear” missile, Russian Kh-38 multi-purpose missile, “Kinzhal” hypersonic missile, Israeli “Ice Breaker” missile, etc. At the same time, the development characteristics of foreign air-to-ground missiles, such as systematic cooperative operations, low-cost series development, electromagnetic combat capability, competitive situation in hypersonic field, and building digital engineering ecosystem, are summarized and analyzed.

The reform of test and evaluation is a critical component of the US defense acquisition system reform and the digital transformation of the US military. Facing the challenges of test and evaluation brought by the development of emerging technologies such as artificial intelligence and autonomy, as well as the systematic operational requirements like multi-domain warfare and all-domain warfare, to the delivery of weapon equipment capabilities, the US Department of Defense is actively promoting digital transformation in the field of test and evaluation. One of the crucial measures is to put forward the concept of test and evaluation as a continuum, aiming to continuously optimize test strategies and evaluation processes with the help of digital engineering concepts, and further enhance the efficiency and qua-lity of acquiring weapon equipment. This article briefly outlines the development of test and evaluation as a continuum, analyzes its framework content and conceptual implications, discusses the specific capability elements required for implementation, and provides insights into the digital transformation of test and evaluation for weapon equipment.

High-precision cooperative navigation is the key to realizing multi-aircraft formation flying, and formation configuration is an important factor affecting the positioning accuracy of cooperative navigation. In order to achieve high-precision cooperative navigation, a multi-aircraft cooperative navigation system model is established, the effect of formation configuration and its dynamic change on cooperative navigation positioning accuracy is analyzed, and the formation configuration that makes the system fully observable is determined. Then, the cooperative navigation positioning accuracy evaluation model is established based on the system observable degree analysis method, and the optimal formation configuration of multi-aircraft cooperative navigation is obtained. The simulation results show that compared with the non-optimal formation configuration, the positioning accuracy of the optimal formation configuration can be increased by more than 75%, which effectively improves the cooperative navigation positioning accuracy of the aircraft formation.

Helicopters are vulnerable to a variety of ground-to-air/air-to-air weapons during low-altitude operations. Short-range launched RPGs and missiles with increasingly strong anti-jamming capabilities have posed a great challenge to the traditional “soft kill” protection system composed of infrared decoy bombs and laser directional jamming. Therefore, there is an urgent need for active protection system with “hard kill” capabilities. In order to study the key technologies for implementing helicopter active protection systems, the deve-lopment status and trends of foreign helicopter active interception systems are analyzed. On this basis, key technologies such as the real-time detection and warning technology for incoming threats, high-precision interception fire control technology, precise control and rapid response interception munition design technology are analyzed.

With the deepening of equipment price management reform, the equipment acquisition price has increasingly become the core of comprehensive price control. In response to fundamental issues such as unclear understanding of the formation mechanism of equipment acquisition price and unreasonable selection of argumentation me-thods in military and enterprise at the current stage, based on deep analysis in concepts of the equipment acquisition price, this paper concludes its basic characteristics and evaluation criteria. Based on the principles of system engineering and the equipment life cycle cost, it studies the formation mechanism of the equipment acquisition price, and analyzes the influencing factors of the equipment acquisition price, standardizes the demonstrating process and work items for the equipment acquisition price. On the basis of the cost attribute oriented argumentation methods, such as traditional engineering methods, parameter methods, analogy methods, this paper puts forward the economic affordability analysis method, war cost analysis method, and cost-effectiveness evaluation method for the demand attributes and benefit attributes. It sets up the method system of the equipment acquisition price to provide effective instructions in practice of the equipment acquisition price demonstration, and to increase the scientificity and rationality of equipment acquisition price demonstration results.

Carbon fiber reinforced polymer (CFRP) with lightweight and high-strength has been widely used in aircraft structures. As their weaker electrical conductivities compared to metals, the impact of lightning strike must be considered. Usually, the damage caused by lightning current component C wave is most serious to CFRP, so a thermo-electric coupling model of C wave and a finite element model (FEM) of composite laminates are proposed to simulate the ablative damage induced by C wave in the CFRP laminates. In the subsequent thermal equilibrium process, a further propagation of the damage in the CFRP laminates by thermal radiation and conduction is estimated. Finally, the residual compressive strength of CFRP laminates with lightning damage is predicted by employing the three-dimensional Hashin criterion based on propagated damage.

This paper reviews the research on InAs/GaSb superlattice mesa etching technology. The physicochemi-cal mechanism and parameter control of wet and dry etching are analyzed to elucidate the influence of process conditions on mesa morphology, so as to suppress the surface leakage current of long wave and very long wave superlattice with narrow band-gap. The results show that the uniform etching of the two components can be achieved with the appropriate proportion of etching solution in wet etching, without causing rough surface and serious undercut. In dry etching, Cl2-base and CH4-base mixed gas is used. By adjusting the type and proportion of etching gas, the balance between physical and chemical etching processes can be achieved to ensure the smoothness of the mesa sidewall and the perpendicularity of the dip angle. In addition, for superlattices of different components, different process parameters need to be selected to meet the synergistic etching of InAs and GaSb. Finally, the InAs/GaSb superlattice mesa etching process is prospected.

Addressing the numerous limitations in solid motor performance experiments for aircraft power systems, such as high costs, specialized equipment requirements, specific experimental environments, and high risks, this paper proposes an artificial intelligence method based on deep meta-learning for engine performance prediction. This method employs model-agnostic meta-learning (MAML) and deep convolutional neural networks (DCNN) models. Firstly, thrust-time data is divided into different training tasks according to varying experimental conditions. The optimal model parameters for each task are obtained through inner-loop training, and the model initialization parameters are updated in the outer-loop. After iterative optimization of the inner-loop and the outer-loop, a model predicted the total impulse of solid engines with high accuracy is obtained, and finally it is tested for new tasks. The test results demonstrate that compared to DCNN without meta-learning, this method reduces the error on the test set significantly, with a maximum percentage error of 2.27%. This verifies the high-precision prediction ability of the meta-learning model for solid motor perfor-mance under small sample conditions.

The development of the US military’s kill web reflects a profound transformation in its combat style and outlines a blueprint for future intelligent warfare. Through an in-depth analysis of the development trajectory and core characteristics of the kill web, its significant advantages in dynamics, multi-dimensionality, synergy, optimization, and resilience are pointed out. This paper discusses the core technologies of the US military’s kill web, as well as the role of projects such as the adapting cross-domain kill-webs (ACK), the system-of-systems technology integration tool chain for heterogeneous electronic systems (STITCHES), and mission-integrated network control (MINC) in promoting the practice of the kill web. The development of the US military’s kill web will focus on the evolution of intelligent and autonomous technologies, the deep integration of global combat capabilities, the innovation in decision-making timeliness and accuracy, the enhancement of system elasticity and resilience, and the rapid network reconstruction and adaptability.

One of the important ways to break the endurance bottleneck of aircraft is to apply the flight strategy of albatrosses obtaining energy from gradient wind fields to glide thousands of miles on aircraft. Based on the body characteristics and flight strategy of albatross, a bionic albatross aircraft with bionic shape, aerodynamic layout and control mode is designed. The lift-drag ratio during cruise is 1.13 times that of conventional aircraft, and the maximum lift-drag ratio is 1.31 times that of conventional aircraft. The maximum drag is reduced by 12% and the wing root load is reduced by 35% through wing tip deformation. According to the behavior of albatross flapping its wings from time to time during gliding, the intermittent dynamic gradient wind gliding method is proposed, and the control performance simulation of bionic albatross aircraft is carried out. The results show that the error between the actual flight path and the gradient wind gliding path is less than 5%, and the energy consumption is 51.5% of uniform flight, which verifies the rationality of the intermittent dynamic gradient wind gliding strategy.

Open-cell foam material is an advanced functional and structural integration material，which can meet the practical needs of aerospace and other high-tech fields，and has a good prospect in practical engineering production applications. The research on the mechanical model of 3D open-cell foam has been developed，but there is little research on the acoustic model. A method of constructing a 3D open-cell foam model using Voronoi diagram is proposed to simulate the geometrical characteristics of the open-cell foam micro structure，and the disturbance factor K is defined to measure the degree of irregularity of the micro structure. The photosensitive resin printing technology is used to generate the corresponding physical model，and its accuracy is verified with mechanical and acoustic experiments and simulations. The results show that the generated porous foam solid model with cross-section properties can be imported into a variety of finite element software to complete the finite element calculation such as mechanics and acoustics，which can provide an idea and method for the construction of three-dimensional Voronoi open-cell foam model，and has certain reference significance for the further study of properties and production of porous materials.

Flexible materials to achieve deformable wing technology requires high mechanical properties of flexible materials，the existing research on chiral structures as flexible materials to drive deformable wings is based on the case of linear small deformations. In order to investigate the mechanical properties of chiral structures under large deformation conditions，five common chiral system negative Poisson's ratio structures，such as tri-chiral，anti-trichiral，tetra-chiral，anti-tetra-chiral，and hex-chiral structures are taken as the object of study. Based on the theory of cellular structural mechanics，the effect of topological structure and cellular element geometrical parameter on the in-plane compression and energy absorption characteristics of chiral system negative Poisson's ratio structures of the intrinsic model of ideal plastic materials are compared and analysed. The results show that the elastic modulus，plateau stress and energy absorption capacity of the chiral structure are inversely proportional to the cell element parameter α and positively proportional to the cell element parameter β. The topology affects the energy-absorbing properties of chiral structures significantly，i.e.，the energy-absorbing capacity of chiral structures with the same single-cell geometrical parameter is significantly enhanced with the increase in the number of ligaments.

The aerodynamic noise test of counter-rotating propellers in wind tunnels has the problems of difficult time coordination and high cost. The aerodynamic noise test system of counter-rotating propellers，which is capable of simulating the driving state of counter-rotating propellers on the ground，is developed by relying on the acoustic environment of the ground. The aerodynamic noise test is carried out on a perforated counter-rotating propeller and a reference propeller to validate the test system and evaluate the noise reduction effect of the perforated counter-rotating propeller. The results show that the perforated counter-rotating propeller can effectively reduce the noise under the prerequisite of guaranteeing the aerodynamic performance in the range of the tested working conditions. In the 90° pointing angle，which has the most significant effect on the aircraft cabin，the noise reduction at the secondorder passing frequency reaches 5 dB. The designed aerodynamic noise test system can provide assistance for the evaluation of aerodynamic noise of the counter-rotating propeller and the design of noise reduction.

Addressing the challenge of low identification accuracy in traditional load identification methods based on the truncated singular value decomposition（TSVD）method，especially when the external load frequency approaches or reaches the natural frequency of the structure，the LSTM-CNN load identification model is proposed in this paper. This model combines the feature extraction capabilities of the convolutional neural network（CNN）with the long-term memory function of the long short-term memory network（LSTM）. The load identification method based on the LSTM-CNN model is then applied to research load time domain waveform identification on the GAR TEUR aircraft model. For model training and load identification，the response data and excitation data from the structure are corrected. The identification results are compared with the TSVD method，LSTM method，and DCNN method. Results show that the load identification method based on the LSTM-CNN model proves effective for sinusoidal load identification problems，especially under the natural frequency excitation of the structure. The method exhibits high identification accuracy and robust noise resistance capabilities.

The structures of hypersonic vehicle surfaces，engine blades，internal ducts and exhaust ducts may generate thermal-acoustic fatigue damage because of high temperature and high-intensity noise environments. Thus，it is of significance to study the thermal-acoustic fatigue problems for improving the durability and reliability of such structures. Thermal-acoustic fatigue problems of aircraft structure have received widespread attention. In this paper，the research status of thermal-acoustic fatigue problems and the research progress during the theoretical research，simulation analysis and experimental technology of thermal-acoustic fatigue are summerized both at home and abroad. The research status of structural thermal-acoustic fatigue in foreign countries is reviewed from the 1970s to the present from a time perspective. The work carried out by domestic research institutes and higher education institutions in this field is introduced according to the classification of research units. On this basis，the technical difficulties are analyzed and the further development is proposed during the research on thermal-acoustic fatigue of aircraft structures.

The traditional finite element model has the problems of high computational cost，more black-box operation，and lack of independent intellectual right. The analytical method is used to study the prediction of the vibration response of aircraft wall panels with macro fiber composite（MFC）patches under basic harmonic excitation. Based on classical laminate plate theory，electro mechanical coupling constitutive equations，and the energy method，the analytical model of the MFC-panel system under basic harmonic excitation is established. By employing velocity feedback control method and modal superposition principle，the vibration response of the structure system before and after active control under such an excitation load is successfully solved. The analytical model and its predictive results are extensively validated through the integration of literature data and experimental data obtained from a vibration testing system that is assembled. The results show that，compared to the literature results，the maximum deviation in the calculation of natural frequencies by the proposed model is less than 2%. Additionally，the maximum error in predicting the first two order resonance responses by the model is less than 8.6 %，and both of them are within an acceptable range.

Aviation aircraft will be subjected to a large number of complex random vibration loads during service， and its structure is prone to vibration fatigue，which leads to damage or even failure，which can cause serious losses. The stress intensity factor（SIF）solution method for cracked beams under random vibration loading is investigated，and a time-domain method based on Hudson's theory is proposed to estimate the vibration fatigue crack growth life by combining with the Paris formula. The theoretical analysis and vibration fatigue test are conducted on a typical cantilever beam as an object. The results show that the life prediction results of the proposed time-domain method based on the Hudson's theory is better than that of the experimental estimation results，which can verify that the method can effectively describe the random vibration crack growth behavior.

The suppression of vibration and noise has always been an important issue in engineering，and metamaterials have shown significant application value in vibration and noise reduction. In this paper，a novel hollow starshaped chiral metamaterial is designed by incorporating chiral structural characteristics into traditional hollow starshaped metamaterials and further evolves it into a solid star-shaped chiral metamaterial. The bandgap formation mechanism is analyzed through vibration mode analysis，and the effects of different structural parameters on the bandgap are studied. The propagation characteristics of elastic waves in the structure are investigated through dispersion surfaces，wave propagation direction，group velocity，and phase velocity. Finally，the transmission characteristics of finite periodic structures are studied. The results show that the solid star-shaped chiral metamaterial can generate an ultra-wide bandgap with a width of 5 116 Hz. The bandgap formation is mainly due to the rotational vibrations of the concave stars and ligaments dissipating the energy of elastic waves. Additionally，a decrease in the inner concave angle α and an increase in the angle θ between the ligaments and the horizontal direction result in a wider largest bandgap. The finite periodic structure can generate significant displacement amplitude attenuation within the bandgap range. This novel metamaterial has excellent vibration isolation performance.

As an advanced composite sandwich structure，the configuration of folded core is diverse，and previous research has mostly focused on the V-shaped folded core，while there is still relatively little research on the sound insulation performance of other configurations. A numerical model of a four sided simply supported M-shaped folded core sandwich panel under vertical incident sound pressure excitation is established，and the numerical simulation of its sound insulation performance based on finite element software is conducted. The theoretical predicted sound transmission loss curve of the honeycomb sandwich panel is compared with the simulation results. Based on simulation models，the sound insulation performance of M-type folded core sandwich panel structure is systematically studied，and the qualitative influence of geometric parameters of folded core cell on sound insulation performance is discussed. The influence of relative misalignment and laying angle of the upper and lower layers of M-type folded core sandwich panel with double-layer core on sound insulation performance is proposed and studied. The results show that the sound insulation performance is improved when the upper and lower layers of core are staggered and stacked in the Z-shaped line step direction of the cell，and it is better than single-layer folded core sandwich panel with the same surface density. When the relative laying angle of the upper and lower layers of core changes，the maximum weighted sound insulation reached the most value while the axis of the upper and lower layers of core is vertically laid.

The pipeline space configuration of fuel pump accessory is complex，and it is difficult to simulate directly in vibration environment test. In this paper，the system equivalent reduction expansion process（SEREP）is used for the dynamic equivalent design of the pipelines to meet the test requirements. By selecting the specific nodes on the pipeline as the main DOFs，and reducing the original pipeline model to the main DOFs model，the reduced mass and stiffness matrix are obtained. The sub-mode matrix is decomposed by SVD to further simplify the reduced mass and stiffness matrix，then the new reduced mass and stiffness matrixes of low-order pipeline model are obtained. The "mass ball-beam spring" structure model is proposed，which maps the reduced mass and stiffness matrices using "mass ball" and "beam spring" respectively，thereby determining equivalent design and processing parameters. Finally，the implementation of the equivalent design method is verified through examples，and the first frequency error between the equivalent pipeline and the original pipeline is mostly within 10%，meeting the requirements of engineering applications.

The mechanism of contra-rotating propeller's aerodynamic noise is very complicated，and propeller-driven aircraft is not equipped passive noise reduction components such as nacelle liner to absorb noise during sound transmission，the noise generated by propeller will straightforward radiated to the fuselage and surrounding. Therefore，reducing the intensity of propeller noise is the key to the development of low-noise propeller aircraft. In this paper，a "soft blade" module is formed by placing a "small hole and through channel" structure on the suction front edge of spiral blade tip to balance the peak pressure at the leading edge of blade and reduce the load noise. According to the optimal parameters，the conventional propeller and the soft-blade propeller are manufactured，and the radiation noise measurement is carried out on the basis of the counter-rotating propeller aerodynamic noise test system. The results show that the counter-rotating propeller with perforated structure can effectively reduce the noise as well as ensuring the aerodynamic performance. At the 90° pointing angle，which has the most significant effect on the aircraft cabin，the noise reduction at the second-order passing frequency reaches 5 dB.

The rubbing of the labyrinth sealing structure is a common problem during the operation of aeroengine air system. Due to the difficulty in observing the process of crack initiation and propagation on the sealing ring during actual rubbing，using finite element method for numerical simulation can provide a deeper understanding of the process and mechanism of crack initiation and propagation. The sealing ring model with wear grooves after rubbing is proposed. The surface convective heat transfer coefficient，rubbing force and rubbing temperature of the sealing ring are considered. The extended finite element method（XFEM）is used to numerically study the temperature field， stress field，and crack initiation and propagation of the sealing ring. The crack numerical simulation result is com pared with the result of rubbing experiment. The results show that the crack initiation and propagation direction obtained from numerical simulation are basically consistent with those obtained from rubbing experiment. The mechanism of crack initiation is revealed，and it is proven that this method can effectively simulate the process of crack initiation and propagation caused by rubbing.

The study on the absorber of flexural waves based on time-domine model coupling theory is not applicable to all models，and has complex design process，which is difficult for widespread application in industrial engineering. Therefore，a research method for elastic absorbers based on the acoustic impedance matching theory is proposed. The absorption curve of absorbers is verified with theoretical calculations，numerical simulations and experiment. The results show that the proposed method can quickly and easily realize the structural design of elastic absorbers，bringing new possibilities for the research on flexural waves absorption and vibration reduction design. The theoretical method and absorption structure proposed in this paper do not need additional damping materials，which is more conducive to meet the requirements of lightweight structures in aeronautical engineering. At the same time， it brings new possibilities for the field of vibration wave absorption，especially the design of efficient absorption and vibration reduction of curved waves.

Ground vibration test is an important part of aircraft model development and strength verification. In aircraft ground vibration test，an appropriate excitation scheme can significantly shorten the test's period and improve the accuracy of mode identification. In this paper，QR decomposition based on the finite element model is used for global planning of exciter placement，and mode participation is introduced to evaluate the plan's exciting efficiency. The multivariate mode indicator function is used to optimize the exciting force vector for closely spaced modes. Finally，these methods are verified in a small general aircraft's ground vibration test，which significantly improves the test's efficiency and reduces the difficulty of closely spaced modes identification. The excitation scheme optimization method adopted in this article has high engineering application value.

Aviation fuel pump has the problem of flow-induced noise in engineering application，which can affect the unit operation stability and staff's working security. To solve these problems，the noise reduction technique for fuel pump is introduced. Firstly，the noise data of fuel pump acquired during the on-land system test of air plane is tested，and the noise amplitude and frequency are analyzed. Then，numerical simulation is conducted to understand the flow regime in the fuel pump. Finally，the optimization design is conducted for impeller and guide vane of fuel pump. The results show that the main reason of flow-induced noise is the pressure fluctuation caused by rotor-stator interaction between impeller and guide vane. The pressure fluctuation can be reduced by increasing the impeller and vane blade number and applying the alternate loading technique. After optimization，the noise of fuel pump is decreased by 6.5 dB.

The turbine blades of aero-engines are subjected to cyclic high-low cycle loads in actual service environments，which is a typical high-low cycle micro motion fatigue condition. The frequent occurrence of fatigue fracture in turbine blades due to fretting fatigue seriously affects the safe operation of aero-engines. In order to study the high-low cycle fretting fatigue problems of hot end component materials，this paper designs an Inconel718 tenon connection simulation component and conducts high-low cycle composite fretting fatigue tests on it. Three different load/frequency experiment conditions were designed to compare the life distribution of the simulated parts under different conditions. The results show that high/low cycle load has significant influence on fretting fatigue life. With the increase of high/low cycle load or frequency，the fretting fatigue life of joints decreases. The test results have proven that the high-low cycle fretting fatigue test of the tenon joint structure effectively reproduces the actual service condition of turbine blades. By displaying the explicit finite element analysis，the predicted crack initiation location shows less dispersion compared to the experimental results.

The damage effect of the explosion shock wave generated by the explosion of the air to air missile warhead on the aircraft skin structure is influenced by various factors，and the function mechanism is relatively com plex，so that a large number of experimental and computational samples are required to evaluate the damage of shock waves to aircraft skin structures accurately. The static explosion experiments of aluminum alloy reinforced plates with fixed supports are performed，and their dynamic response and deformation patterns under shock wave loading are analyzed. The finite element analysis software LS-DYNA is used to simulate the structural response under explosive impact，and the simulation model is validated by comparing with the experimental results. The results show that the target plate is prone to tensile failure with tearing at the fixed boundary when the hole area ratio of the reinforced plate exceeds 1‰，and increasing the hole diameter or the number of holes enhances the risk of perforation damage between holes. The target deformation increases with the incident angle of explosion，and the target deflection can increase by more than 30% when the angle increases from 30° to 60° at a constant explosion distance.

At present，the most widely used control algorithms in the field of active noise control（ANC）are the classical FxLMS algorithm and its improved algorithms，which are applied to noise control in large spaces and areas such as the turboprop aircraft cabin，the amount of algorithmic calculations will be rapidly expanded with the increase in the number of channels of the ANC system，and the real-time requirements of algorithms are difficult to meet. Sequential Partial Update FxLMS（SPU-FxLMS）algorithm effectively solves this problem，but its convergence performance is weaker than that of the FxLMS algorithm. In this paper，the improvements to the SPU-FxLMS algorithm for the problem of slow convergence are made，so that the algorithm can be converged with a faster speed in the early stage of the operation，and then converge with a lower speed after converging to a smooth state. After converging to a steady state，the algorithm continues to run with a low computational capacity. The theoretical derivation and simulation analysis of the improved algorithm are carried out. The results show that the algorithm has good noise reduction performance and robustness while further reducing the amount of computation，and has a good prospect for engineering applications.

Experimental modal analysis is a method of measuring the natural vibration characteristics of a structure through experiments. The analysis results are mainly used to modify the structural dynamic models and provide data support for structural dynamics，aeroelastic analysis and vibration control design. This article systematically reviews the research progress of experimental modal analysis methods at home and abroad，starting from two aspects：classic experimental modal analysis methods and modern modal analysis methods，and summarizes the basic principles of the two mainstream methods，the classic phase resonance method and the phase separation method， briefly introduces the experimental modal analysis methods developed in recent years，and summarizes the characteristics of different modal analysis methods. Finally，the current problems and possible future development trends of experimental modal analysis methods are given.

The heat source analysis and quantitative calculation of heat production of the bearing-support structure system can provide a reliable basis for the thermal protection design of the bearing cavity. Through theoretical analysis of heat transfer and tribology，a heat generation analysis model for the bearing-support system of an aircraft engine is established. 1D thermal-fluid coupling calculations of the bearing-support system are carried. The intermediate bearing support frames of the aero-engine compressor and turbine are analyzed for heat generation separately to evaluate the effects of different heat sources on the heat generation of the bearing-support system under cruise operating conditions. The results show that the wall temperature of the right frame of the compressor intermediate support system increases radially upward by 1.73%. The heat transfer coefficient（HTC）increases radially upward by 20 times due to the presence of interstage sealing between the main flow path and the disk cavity. Among them，the heat sources with the highest percentage of heat generation are through the support walls，bearings，and seals，and heat generation by the seals in the bearing-support system accounts for 29% in the intermediate bearing support frame of the compressor and 35% in the intermediate bearing support frame of the turbine.

High-entropy alloys（HEAs）have attracted considerable attention from the research community as a pioneering alloy design paradigm over the past two decades. They have fundamentally challenged traditional design paradigms and exhibited exceptional mechanical properties and functional characteristics，thereby positioning themselves as promising candidates for significant engineering applications in the future. Recent advancements have unveiled several alloy systems that demonstrate exceptional performance across diverse metrics，including low-temperature fracture toughness，high-temperature strength，impact resistance，radiation tolerance，and fatigue resistance. These qualities render HEAs highly attractive materials for research with substantial application potential in critical domains such as deep space exploration，deep-sea investigations，low-temperature superconductivity，and advanced nuclear energy technologies. This paper will briefly introduce the concept and classification of HEAs，and review the experimental progress of HEAs under various extreme conditions such as extremely low temperatures，high-speed impacts，and high nuclear radiation. We also summarize the strategies for enhancing the strength and toughness of HEAs，and extract the deformation mechanisms and physical and chemical properties of HEAs under different extreme loads. It is foreseeable that the main development direction of HEAs will be to form microscopic fluctuations in chemical composition and construct multi-scalestructural ordering efficiently through fine adjustment of the selection and proportion of alloying elements and optimization of heat treatment processes. For comprehensive studies on HEAs subjected to extreme loads，it is essential to explore their microscopic deformation mechanisms further while proposing innovative strategies designed to address inherent trade-offs between strength and toughness. The integration of state-of-the-art simulation techniques combined with advanced characterization methods will be crucial for improving research efficiency while providing insights into microstructural behavior. Additionally，tailored optimization approaches should be implemented for distinct advantageous systems and phase structures，particularly those capable of activating dislocation movements，twinning，phase transformations and incorporating novel processing methodologies such as additive manufacturing. Finally，conducting more realistic simulation experiments that closely replicate extreme environments along with generating relevant engineering data are vital steps toward accelerating the practical application of HEAs in challenging settings.

This paper explores the application and development trends of artificial intelligence (AI) technology, particularly machine learning and natural language processing in the field of failure analysis. Failure analysis is a crucial method for ensuring the reliability and safety of equipment, and is widely used in aerospace, automotive manufacturing, electronic devices, and other fields. Traditional failure analysis methods often rely on expert experience, which is time-consuming and laborious. By integrating AI’s powerful data processing capabilities with traditional methods, the accuracy and efficiency of analysis have been significantly enhanced. In terms of failure mode diagnosis, AI can rapidly and accurately identify various fault modes and provide precise diagnostic results. In failure cause diagnosis, AI integrates data from multiple sources to uncover complex failure factors and potential causal relationships, improving diagnostic reliability. In failure prediction, machine learning can accurately forecast material lifespan and strength, reducing experimental time and costs. In failure prevention, AI offers new approaches to effectively reduce the risk of failure and lower product maintenance costs. The paper also looks forward the future development prospects of AI in failure analysis and highlights challenges and recommendations in the areas, such as data quality improvement, model optimization, interdisciplinary collaboration, and ethical and safety issues.

As the turbine inlet temperatures of aero engines continue to rise， there is an urgent need to develop a new generation of single-crystal superalloys and their thermal protective coatings for turbine blades. In order to meet the stringent requirements for the comprehensive performance of high-temperature structural materials in the complex service environments of aero engines， the intelligent design research of single crystal superalloys and thermal protection coatings has been gradually carried out at home and abroad in recent years under the promotion of material integrated computational engineering and material informatics. This paper reviews the latest research progress in the design of novel single-crystal superalloys and thermal protective coatings by utilizing multi-scale computational simulations and machine learning methods. The findings confirm that multi-scale computational simulations offer robust theoretical support for understanding the strengthening and toughening mechanisms of single-crystal superalloys， as well as the oxidation resistance and diffusion protective mechanisms of thermal protective coatings. Additionally， the study highlights the reliability and significant potential of machine learning in constructing intrinsic "composition-structure-property" relationship for high-temperature structural materials. This approach paves an intelligent and efficient new pathway for the rapid development of next-generation high-temperature single-crystal superalloys and thermal protective coatings.

With the global energy transition and increasing environmental requirements，hydrogen-mixed gas turbines as a high-efficiency and low-emission energy conversion equipment has been widely concerned. This paper reviews the development status of hydrogen-mixed gas turbines domestically and internationally，analyzes the characteristics of hydrogen combustion in gas turbines，explores the impact of hydrogen combustion on complex components and the application of high-temperature materials，and analyzes the performance requirements for hot-end component materials operating under high temperature，high pressure，and corrosive conditions，as well as the main challenges and potential solutions in current material development. The effects of water vapor and hydrogen embrittlement during hydrogen combustion on gas turbine alloys and thermal barrier coatings are discussed in detail.Water vapor accelerates the oxidation and corrosion of alloys，leading to a decline in mechanical properties. Furthermore，hydrogen embrittlement significantly affects the toughness and durability of alloys，increasing the risk of crack propagation and fracture. In terms of the problems，future research should focus on multi-field coupling simulations and accelerated corrosion tests，considering the factors such as temperature，pressure，and different atmospheres to establish realistic environment simulators to evaluate alloy and coating performances. Additionally，the combined effects of hydrogen and water vapor on high-temperature alloys and thermal barrier coatings should be emphasized. This includes investigating the diffusion mechanisms of hydrogen in alloys，interactions with lattice defects，and the microscopic processes leading to hydrogen embrittlement. Building oxidation models in high-temperature water vapor environments，clarifying the dissociation and adsorption mechanisms of water vapor at high temperatures，the hydroxylation of protective oxide films Al2O3 and Cr2O3，and the growth behavior of non-protective oxides（e.g.，spinel） are also essential.

Main-shaft bearings are vital safety components in aeroengines made of bearing steels with outstanding combinational properties. The material is supposed to exhibit high surface hardness，high fracture toughness，high temperature resistance，fatigue resistance and corrosion resistance. However，under harsh operation conditions bearing steels are prone to rolling contact fatigue（RCF）that leads to bearing failure，severely endangering flight. Therefore，accurately predicting the RCF lives of bearing steels is key to the reliability of aeroengine. This manuscript reviews important results and progress in the RCF and life prediction of aeroengine bearing steels and suggests future research directions. Firstly，special stress state as a result of the Hertzian contact between rolling element and raceway is introduced，where shear stress components peak at the subsurface.This explains the origin of complexsubsurface-originated RCF mechanisms in bearing steels and indicates subsurface-originated RCF to be an important failure mode of bearing steels under ideal conditions. Meanwhile，with increasing contact pressure，the response of material evolves from elastic mode to plastic mode. Besides，due to the harsh service environment of aero-engine bearings，surface-originated also takes place and hence the competition between these two mechanisms is present. Next，three methodologies for RCF life prediction are summarized，being probabilistic models，mechanistic models and numerical models，with their advantages and limitations analyzed. Probabilistic models are well developed and widely employed by industry，but they are in nature a kind of statistical models without accounting for RCF mechanisms and are hence lacking scientificity; Deterministic models predict RCF life via describing physical processes，which are rich in science but poor in accuracy due to their simplification; numerical models balancing both engineering practice and scientific characteristic is a powerful tool to tackle the problem of RCF life prediction，although their accuracy requires further improvement. Finally，it is suggested that future research may focus on solving key scientific problems in RCF，modifying life prediction models via inserting RCF mechanisms and applying artificial intelligence in RCF life prediction.

Rare earth permanent magnet materials are widely applied in critical fields such as aerospace，energy technology，and transportation，serving as critical materials in modern technology. The 1∶12-type（ThMn12）SmFe permanent magnet material exhibits magnetic properties comparable to Nd2Fe14B and possesses a higher Curie temperature. It exhibits the highest theoretical magnetic energy product among permanent magnets. Moreover，it consists of abundant elements，showing significant potential for application. However，this material faces challenges in thermal stability，leading to low coercivity，thus hindering its potential. This paper first analyzed the reasons for the poor thermal stability of the 1∶12 phase，concluding the influence of elements occupying different crystallographic sites on phase stability and intrinsic magnetic properties. Subsequently，we analyzed the key factors affecting the coercivity，elucidating the inherent relationship between preparation processes and coercivity. Finally，we proposed strategies for achieving high magnetic energy products in 1∶12 type SmFe permanent magnets，such as multi-site element Co-doping，control of cooling rate，and grain boundary encapsulation，providing important references for developing rare earth permanent magnets.

High-strength aluminum alloys have been widely used in aviation， aerospace and other industries because of their high specific strength and good machining property. Corrosion is an important factor affecting the safety and stability of high-strength aluminum alloys in service. Based on the preparation process of high-strength aluminum alloys， this paper focuses on the effect of structural evolution caused by heat treatment on the corrosion property of high-strength aluminum alloys. The corresponding relationship between the microstructure and corrosion behavior of high-strength aluminum alloys is analyzed. Research directions for improving the corrosion property of high-strength aluminum alloys are proposed. The segregation of elements and phases in high-strength aluminum alloys can easily lead to electrochemical inhomogeneity of microstructure， causing corrosion of substrate. Therefore， based on the optimization of composition， the melt casting process， deformation process and heat treatment process of high-strength aluminum alloys should be regulated to prepare the microstructure with uniform distribution of elements and second phases， and uniform electrochemical property， which is crucial for improving the corrosion property of high-strength aluminum alloys. In addition， the corrosion sensitivity of alloys is affected by the width of the precipitate free zone and the distance and distribution of the grain boundary precipitation phases of alloy. Thoroughly studying and clarifying the effect of various structures such as precipitate free zone on the corrosion behavior of alloys is the prerequisite for the preparation of high-strength aluminum alloys with high corrosion property. To balance the mechanical property and corrosion property of high-strength aluminum alloys， heat treatment methods such as aging and thermomechanical treatment should be optimized， and new composite heat treatment methods should be developed. Meanwhile， the test methods and evaluation methods for the corrosion property of high-strength aluminum alloys are discussed. In order to more efficiently and accurately evaluate the corrosion property and service safety of high-strength aluminum alloys， further research work should be carried out in the combined use of traditional evaluation methods with modern data processing technologies such as digital twin， virtual simulation and machine learning.

The thin-wall effect of single crystal superalloys refers to the phenomenon that when the thickness of the sample and the part is less than 1 mm，the lasting life is reduced， the creep rate is increased and other mechanical properties are significantly attenuated. With the development of the internal cooling structure of advanced aero-engine single crystal blade parts， the structural thickness of some areas decreases， making it a typical thin-walled structure. Thus， it is of great engineering significance to consider the thin-wall effect in the thin-wall region during the design and manufacture of blades. Creep performance is one of the most important properties of superalloys for turbine blade application. This paper summarizes the thin-wall effect in creep performance of the superalloys as well as some advanced experimental equipment in the study of thin-wall effect. Research on thin-wall debit effect of superalloys can be divided into two categories，one is the cause of thin-wall debit，including the relative enhancement of oxidation，more significance in anisotropy，changes in microstructure and the initiation or growth of defects，and the factors that influence the thin-wall debit effect including experimental conditions（temperature，stress，etc.），the processing methods（casting， machining）， geometric shape （rectangular cross-section， ring cross-section， film cooling holes）. Research on thin-wall debit effect is within the scope of engineering application，as a part of “component level/analog component level” in “building block” verification and evaluation technology，thin-wall debit effect research under service environment or near-service environment conditions is more valuable for application. For this purpose，a variety of advanced experimental equipment platforms have been developed to simulate one or several coupled service conditions（high temperature，high pressure，corrosion/erosion，centrifugal loading） of the blade in the engine. Future research on thin-wall effects should be carried out under conditions closer to actual service conditions by preparing specimens according to the actual blade manufacturing process and conducting experiments on the equipment that simulates the service environment.

A titanium alloy collision friction ignition device was used to conduct collision and continuous friction between TC4 titanium alloy rotating rod and TA7 and other titanium alloy collision samples.Combined with SEM and other microscopic analysis，the anti-ignition performance and products of TA7 and TC11 titanium alloys were studied，and the experimental results under this special friction condition were obtained. The research results show that the friction contact pressure Pf and the combustion chamber pressure P can be effective test parameters to evaluate the titanium alloy impact ignition process. The critical ignition curves of the three titanium alloys drawn based on Pf-P are all linear laws，and the anti-ignition performance is：TC11 > TA11 > TA7. Microscopic analysis of the titanium alloy after impact ignition shows that the combustion reaction zone of the titanium alloy consists of four regions：the combustion product zone （CPZ），the oxide zone （OZ），the heat-affected zone （HAZ），and the friction product zone （FPZ） in total. The multi-layer structure of Al2O3 formed by TC11 after ignition is conducive to blocking the mutual diffusion of Ti，O and other elements，which is the main reason for its superior anti-impact ignition performance.

The as-cast microstructure of 2024 high-strength aluminum alloy has an important effect on its thermal workability and end-use performance.The effects of Cu/Mg ratio and solidification rate on as-cast microstructure were investigated by regulating the Cu and Mg content and solidification rate of 2024 alloy. The results show that with the mass ratio of Cu/Mg increases from 2.1 to 4.1，the type of second phase in the alloy is not changed. However，the content of Al2CuMg gradually decreases，while the content of Al2Cu and Al23Cu（Fe，Mn） 4 gradually increases.When the solidification rate increases from 0.2 ℃/s to 2.4 ℃/s，the grain size is obviously refined，the average grain size decreases from 293.0 μm to 77.0 μm. Moreover，the dendrites become developed，and the dendrite arm spacing decreases，and the second phase becomes smaller and distributes more homogeneous in the matrix，and the content of Al23Cu（Fe，Mn） 4 insoluble phase obviously reduces. The formation of iron-rich insoluble phase can be reduced by reducing the Cu/Mg ratio and increasing the solidification rate，so as that the machining and mechanical properties of the alloy can be improved.

The manufacturing process of composites is crucial for ensuring structural efficiency and application reliability of their products. Computer-based process simulation plays a significant role in improving the manufacturing quality of composite components and reducing the manufacturing cost. Traditional process simulation relies on physical and chemical mechanisms in manufacturing of composites with the mathematical equations solved by numerical methods such as finite element/finite volume analysis and computer-aided design methods e.g. computer graphics. At present，it has been widely used in simulations of the lay-up of reinforcements/prepregs，the infiltration flows of resin，the curing behaviours of thermosetting resin，the heat transmission and exchange，and the nonlinear mechanics including residual stress and curing deformation predictions. Recently，artificial intelligence（AI）technologies have rapidly developed，its technical basis machine learning（ML），in combination with artificial neural networks（ANN），has been used in the field of lay-up process of fiber reinforcements，liquid molding processes，and autoclave processes，which aimed for data mining and developing reduced-order models. The former can establish relationships between process conditions and the curing quality or mechanical properties of the composite parts，while the latter can improve computational efficiency of the process simulation. However，due to the complexity，immeasurability，and high cost of manufacturing fiber-reinforced resin matrix composites，at the beginning of the AI age，it is difficult to meet the requirements of ML only by relying on the amount of data obtained by experiments. Also，data-driven AI technology faces uncertain issues regarding the representativeness，generalisability，and interpretability of the models. Therefore，traditional process simulation based on physicochemical mechanisms can provide a large amount of reliable data for data-driven ML simulation，and then through AI，more quantitative models describing the composite process can be established to expand the computable scope of process simulation. At the same time，as AI technology enhances the computational efficiency，the process simulation that meets real-time requirements can evolve into digital twins（DT）of the composite manufacturing process，which can provide new technical support for reducing the composite costs and improving the scientific whole-life cycle management.