Research advances in fluid-structure interaction (FSI) during vehicle water entry, encompassing theoretical modeling, experimental testing, and numerical simulation are reviewed. The theoretical analysis systematically traces the evolution from classical potential flow theory to nonlinear multiphysics-coupled models, while critically analyzing their applicability and limitations in complex entry scenarios. Experimental investigations summarize measurement techniques for capturing transient parameters and revealing physical mechanisms, highlighting their crucial role in validating theoretical and numerical frameworks, with particular attention to instrumentation constraints and boundary condition effects. Numerical advancements are examined through grid-based and meshless methodologies, emphasizing their computational characteristics in resolving multiphase flow evolution and FSI dynamics. Finally, current technical bottlenecks are identified, followed by forward-looking perspectives on multiscale coupling modeling and intelligent algorithm integration.

The cryogenic exhaust valve is a key component of the liquid rocket propulsion system, and the main failure mode is the stuck guide. To improve its action reliability, a "metal-nonmetal" composite guiding structure is proposed. The non-metal hot pressing forming process is studied, and the theoretical calculation and simulation analysis of the guiding clearance variation under low temperature are carried out. An experimental system is built to verify the reliability of the forming process of the composite guiding structure and the rationality of the clearance calculation. The research results show that the nonmetal composite guiding structure of the cryogenic exhaust valve can adapt to the low temperature operating conditions, and has higher action reliability and tolerance to contaminants.

Permanent magnet synchronous motor (PMSM), owing to its high power factor, high efficiency, and high power density, have been widely employed in aerospace vehicles to enable high-dynamic servo motion. However, during long-term tracking control or attitude holding, PMSMs are prone to interturn short-circuit faults (ITSC). Under servo operating conditions, the fault signals exhibit non-periodic characteristics in the time domain, which poses considerable challenges for fault diagnosis. To address this issue, an ITSC diagnosis method is proposed based on the high-frequency negative-sequence current. First, a simplified analytical model of PMSM with ITSC faults is established to reveal the characteristic impacts of the fault on electrical quantities. Second, a high-frequency voltage signal is injected into the control system, and the high-frequency current response of the motor is extracted through a band-pass filters. Finally, the negative-sequence component of the high-frequency current is calculated as the diagnostic indicator, enabling real-time fault identification. By employing the high-frequency negative-sequence current as the fault feature, the proposed method can effectively distinguish healthy and faulty states of the motor under servo conditions, while improving both diagnostic speed and robustness. Simulation results demonstrate that the proposed method achieves reliable diagnosis under servo operating conditions with rapid variations in position, speed, and load, with a diagnostic time of less than one fundamental cycle, showing strong potential for engineering applications.

In the future reusable space transportation system, the plane-symmetric reusable launch vehicle has a high development priority, and the plane-symmetric launch vehicle control technology is one of the critical technologies. Firstly, the research significance and difficulties of plane-symmetric and liquid propellant rocket are analyzed according to the engineering requirements. Then, the research progress is summarized from four aspects, including attitude control, active load relief (LR) control, elastic vibration suppression and liquid sloshing suppression. Finally, in view of the unsolved problems in the existing research and the new problems brought by the special structure of liquid propellant plane-symmetrical rocket, prospecting its future development and putting forward several feasible research directions from the requirements of high-precision, high reliability and intelligent.

The airline-flight-mode launch capability is essential for future spaceports and a key indica-tor of their space launch capacity. Spaceports face challenges in improving this capability. These challenges include a lack of top-level planning, infrastructure pressure, an urgent need for technology upgrades, and management and safety risks. To tackle these issues, this anal-ysis proposes ten countermeasures. These strategies cover system architecture, overall lay-out, operation modes, rocket families, and testing and launch technologies. They provide valuable guidance for spaceports to enhance their airline-flight-mode launch capability.

The new generation of rocket-borne electrical system architecture fully embodies the characteristics of distributed information synthesis, which can realize the physical separation of rocket-borne electrical system, information sharing and dynamic resource allocation through appropriate unified real-time network design, reduce the impact of cross-domain information interaction, and improve the determinacy, reliability and fault-tolerant ability of system networking. Combined with the different real-time guarantee ability of real-time network flow control mechanisms, the information transmission requirements of rocket-borne integrated electronic system are analyzed, the time-sensitive flow control mechanisms are selected, the message and traffic type are matched, the time trigger window is designed through the joint optimization of path and scheduling, and the network simulation model is built using the OMNet++ to simulate and evaluate the performance of the network system. Through simulation, the matching relationship between all traffic and time-sensitive network flow control mechanisms in typical rocket-borne integrated electronic system are verified, and the feasibility of time-sensitive network application in rocket-borne integrated electronic system is demonstrated.

A primitive time synchronization method is proposed based on the FC-AE-1553 bus technology, aiming at the comprehensive development of onboard measurement systems and the background demand for real-time data sensitivity. This method enables each node in the FC-AE-1553 bus to have the same-time reference. On the basis of time synchronization, a scheduling timing based on time synchronization wasdesigned to collect real-time data from various NT nodes, meeting the requirements of real-time data for onboard measurement systems. The experimental results show that the FC-AE-1553 bus designed has nanosecond time synchronization, dual redundancy, and other functions, which meet the application requirements-of onboard measurement systems and improve the comprehensive level of onboard measurement systems.

Addressing challenges such as low data storage efficiency, weak real-time data retrieval responsiveness, and the separation between data storage and analysis in space missions, an integrated data-access-computation platform architecture is proposed. First, based on the characteristics of data acquisition and usage in the aerospace domain, a requirements analysis for the integrated platform is conducted. Subsequently, an overall architecture is constructed, outlining its core business processes and functional framework. The functional architecture comprises five layers: infrastructure, data acquisition, data storage, data computation, and data application, supporting multi-source heterogeneous data acquisition, operator invocation, task scheduling, and timed execution. Following this, a full-chain technical solution for real-time data acquisition, storage, retrieval, and computation is designed in detail, targeting the core functions of the integrated architecture. This solution provides decision-making support for space missions and lays a technical foundation for intelligent data analysis. Finally, key technologies are elaborated, including intelligent generation of aerospace test reports, data flow modeling, and visual analysis process orchestration.

To address the challenges of strong nonlinearity, high uncertainty, and rapid time-varying parameters during the reentry phase of high-speed vehicles, this study proposes an end-to-end intelligent attitude control method based on an improved Twin Delayed Deep Deterministic Policy Gradient algorithm, aligned with the demands of intelligent spacecraft development. To overcome the issues of training instability and convergence difficulties in TD3-based attitude control learning, two key innovations are introduced: a hybrid reward mechanism combining continuous tracking error penalties and sparse task-completion rewards is designed within the Markov Decision Process framework to synergistically guide agent convergence. Prior knowledge constraints derived from modern control theory are incorporated into the training process, proposing a behavior cloning-based optimization strategy for the Actor network to balance expert experience imitation and cumulative reward maximization. Simulation results show that the proposed method can accurately track the three-channel attitude commands under 14 combinations of parameter deviations.

This research addresses the challenge of high computational resource demands and extended simulation cycles associated with three-dimensional aerothermal numerical simulations for complex-shaped hypersonic vehicles. To overcome this limitation, the application of machine learning-based multi-source data fusion methods in aerodynamic thermal design is investigated, utilizing substantial datasets accumulated during past development projects. The characteristics of various data types, including aerodynamic thermal engineering/numerical simulation and ground/flight test data, are analyzed. Employing Latin hypercube sampling and batch submission techniques, a numerical simulation dataset is constructed, and a multi-source heterogeneous aerodynamic thermal database is established. Grid normalization algorithms for configurations involving rudder rotation and localized deformation are developed. Based on clustering and region matching algorithms, simulation data are partitioned, extracted, and statistically analyzed. Deep learning-based approaches for aerodynamic thermal data fusion and intelligent agent modeling are researched, with predictive accuracy validated using a specific lifting body aerodynamic configuration.