Aiming at the problem of rapid repair of the debonding defect between the solid rocket motor insulation layer and the case in the battlefield environment, a comparative performance analysis of the bonding materials required for the rapid repair of the debonding between the nitrile rubber insulation layer and the steel case is carried out through experiments, and the adhesives suitable for the corresponding conditions and performance requirements are screened out. Firstly, combined with the requirements for the rapid repair of the debonding between the solid rocket motor insulation layer and the case, the curing conditions and performance indicators required for the adhesives used for rapid repair are analyzed. Further, mechanical property and ablation tests of 11 kinds of adhesives from three major categories, namely acrylate, epoxy resin, and silicone, are conducted. Finally, a grouting machine for rapid repair is designed and a fluidity test is carried out. The test results show that the X701-1 adhesive can meet the curing conditions and performance requirements for the rapid repair of the debonding between the nitrile rubber insulation layer and the steel case.

Aerodynamic configuration design is an important technology for hypersonic vehicles. Combined with other relative specialties, it is the key to obtain good flight performance and ensure essential flight quality. As a fundamental research area of modern hypersonic vehicles, air-breathing vehicle has become an indispensable way to realize the sustainable hypersonic flight. The typical hypersonic air-breathing vehicles are focused on and the design concept of configurations is investigated. Proposed from the perspective of combined-cycle propulsion systems, the relationship between propulsion systems and aerodynamic configuration is studied which provides a reference for the aerodynamic configuration design work.

With the wide application of cognitive technology in the military field, cognitive Electronic Warfare (EW) has become the inevitable trend of future military war. Given the development of EW combat object in the cognitive direction leading to a decline in the operational effectiveness of traditional EW, an in-depth exploration and analysis of key technologies in cognitive electronic warfare are conducted, including cognitive reconnaissance, cognitive jamming, jamming evaluation, and dynamic knowledge base. Moreover, the basic concepts of cognitive EW are sorted out, by analyzing the numerous challenges to traditional EW. Then, the system architecture and composition of cognitive EW are studied. On this foundation, the key technologies of cognitive EW are summarized. Finally, based on the characteristics of cognitive EW, the development direction of cognitive EW has been prospected.

In the final assembly process of various solid and liquid rocket models, there are many tasks involved, such as the docking of the rocket body and the transfer of the entire rocket body workstation. Currently, the completion of this series of complex tasks mainly relies on manual guarantee. When the operator's skills are insufficient, the factory quality of the rocket body cannot be guaranteed. And in recent years, with the new production of larger tonnage and diameter rocket models, it has caused a significant physical consumption of workers and also reduced labor productivity. Through long-term technological breakthroughs and physical verification experiments, a large tonnage electric propulsion device with lightweight, ultra overload, stepless speed regulation, and adjustable interface tooling has been developed, which solves the problems of difficult docking of most sections of the rocket body, high labor intensity of the entire rocket body workstation transfer, and intermittent overload of the rocket conveying pipe during cabin penetration in the overall aerospace assembly.

A TDOA joint optimization model (TDOA-PSO-NI-GD) that integrates Particle Swarm Optimization (PSO) and Newton's Iteration-Gradient Descent (NI-GD) method is proposed in response to the problem of insufficient positioning accuracy of multi-stage rocket debris, which improves the localization performance through the synergistic mechanism of global search and local optimization and constructs the multi-debris signal separation constraint model and the environmental interference compensation model. Experiments show that the model reduces the positioning error from 1~10 km to less than 0.5 km in the traditional single-stage optimization algorithm in the rocket debris recovery mission, and the multi-debris signal separation rate reaches 96.2%, and maintains the sub-kilometer accuracy under the mountainous terrain and strong wind disturbances; the validation of the Chan-Taylor algorithm combined with the least-squares method shows that its anti-jamming and positioning reliability are significantly better than that of the existing methods. The algorithm can be extended to mobile communications, unmanned vehicles and other fields, with both theoretical innovation and engineering application value.

The e ^N method based on linear stability analysis is currently one of the most widely used methods for transition prediction; however, the selection of the transition criterion N_T value shows significant scatter at high Mach numbers. The linear stability analysis and e ^N method are used to conduct stability analysis and N-factor envelope calculations for the lifting calibration model at Mach numbers of 5 and 8, and for Reentry F at a Mach number of 20. Combining the transition onset locations obtained from wind tunnel results and flight data, the calibration of the transition criterion N_T value at high Mach numbers is carried out. The results show that for the lifting calibration model, the transition criterion N_T is approximately 5.3 to 6.5 under different angles of attack at Mach number of 5, and approximately 4.8 to 5.3 at Mach number of 8. For Reentry F, the transition onset locations vary significantly at different altitudes, but the transition criterion N_T does not change significantly, being approximately 9.55 to 9.73.

International Space Station has been in orbit for more than 20 years, forming a relatively mature cargo transport system and exploring the development path of low-cost and highly reliable commercial cargo transport system. As China's Space Station enters the stage of application and development, the demand for materials up and down will significantly increase. It will be particularly important to form a rich and stable cargo transport system and significantly reduce cargo costs under normal operating modes. The development and current situation of cargo transport system of the International Space Station are analyzed, the composition of the International Space Staion, commercial orbital transportation service plans, and recent cargo transportation situations are focused on, providing reference and suggestions for China's Space Station's cargo transport system.

Establishing an accurate aerodynamic model is of great significance for analyzing the aerodynamic characteristics of aircraft and designing reliable flight control systems during the aircraft design process. Multi-source data fusion of aerodynamic data from different sources, such as wind tunnel tests and flight tests, is currently a popular method for unsteady aerodynamic modeling by intelligent algorithms. However, traditional fusion algorithms have shortcomings such as high requirements for flight data sources and weak generalization capabilities. Thus an improved intelligent modeling method based on Physics-Informed Neural Networks (PINNs) is proposed to integrate static wind tunnel test data and flight data. Compared to traditional PINNs, the physical loss constraints in improved PINN are reversely constructed to enable feature extraction from different and discrete flight data. The static wind tunnel data are incorporated into both the input and loss function of neural network to construct residual estimates. So the differences between ground and flight aerodynamic data are effectively corrected. The predictive aerodynamic characteristics for different motion forms demonstrate that the improved PINN not only has high aerodynamic prediction accuracy but also exhibits excellent generalization capabilities.

The missile cabin structure is used to form the shape, connect and install the subsystems, and bear various loads. The loads that the missile needs to bear in the flight stage mainly includes shear load, bending moment, axial load, external pressure, thermal load, ect. In order to verify the structural stability and strength performance of the missile cabin structure under multi-load cooperation, it is necessary to carry out the research on the structural strength test. The equivalent treatment method of test load and the design of coupled loading scheme are focused on. The study of structural strength test method of a certain missile cabin under multi-load is carried out, which provides a reliable test basis for the calculation, optimization and modification of the cabin structural strength.

The sparse reconstruction theory can obtain distance information in the emitters localization. In the case of traditional emitter sparse reconstruction poor algorithm performance and off grid, an Off-Grid and multiple emitters direct localization algorithm are proposed based on GDP distribution and Sparse Bayesian Learning (SBL). This GDP-SBL-DPD algorithm assumes that the reconstructed signal follows a Generalized Double Pareto (GDP) distribution and leverages a coarse-to-fine search and signal hyper parameter quadratic updating method to enhance the performance of Emitters Direct in off-grid scenarios. Simulation results demonstrate that the GDP-SBL-DPD algorithm outperforms the grid mismatch algorithms based on Orthogonal Matching Pursuit (OMP), Alternating DirectionMethod of Multipliers (ADMM), and SBL coarse-to-fine search in multiple emitters grid mismatch scenarios, with higher accuracy and stronger robustness.