This PDF file contains the front matter associated with SPIE Proceedings Volume 13218, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Aero-assisted orbital transfer maneuver in atmosphere is the key technology to obtain a significant fuel savings and the resulting increased payload capabilities for space transportation. Therefore, achieving better aerodynamic performance of aero-assisted orbital transfer vehicle (AOTV) guarantees better orbital maneuverability. In this paper, the design activities for AOTV focus on the optimization and comprehensive performance analysis for the aerodynamic configuration of vehicle. A wing-body-type configuration is proposed for the disciplinary modeling. Corresponding geometrical parameterization is performed to provide quantitative design variables which can map the aerodynamic configuration and sensitivity analysis is completed aiming at filtering design variables for the optimization. Taking aerodynamic performance as objective functions, the AOTV configuration optimization with surrogate model is performed using an engineering-based rapid performance analysis approach. Compared with initial configuration, the obtained optimal configuration brings about better aerodynamic performance which results in a 21.3% increase in the lift-to-drag ratio and a 18.5% increase in the lift term. Meanwhile, the multidisciplinary design analysis for the optimal configuration is carried out to evaluate the comprehensive performance including aerodynamics, aerothermodynamics, and static stability of the vehicle rapidly in the process of aero-assisted orbital transfer missions. The results indicate that the design activities in this paper can provide a certain reference for the evolutionary configuration design of AOTV in the conceptual design phase.

To study the influence characteristics of downstream wave systems on shock wave/boundary layer interference (SWBLI) in hypersonic inlet, a model was designed which can generate a stable first shock wave by a linear com-pression ramp, and can simulate the change of the downstream wave system by changing the shape of the adjusta-ble compression ramp downstream of the first shock wave. The relation between different shapes of adjustable compression ramp and SWBLI generated by the first shock wave on the upper wall is studied. The simulation re-sults show that the downstream adjustable compression ramp has a significant impact on the SWBLI. Significant SWBLI is observed when the compression ramp is adjusted to be linear or convex. While by adjusting the compres-sion ramp to be concave, the area of the up-stream separation region can be effectively reduced or even eliminated. The results show that the upstream SWBLI can be influenced by the downstream wave system, and can be mini-mized or eliminated by adjusting the wave system.

Redundant flight control systems typically have high flexibility and customizability, suitable for different types of high-value drones. This article proposes a new architecture for a four degree redundant flight control system, which is based on the traditional four degree redundant flight control system architecture. By adding a CANFD bus to achieve signal interaction between flight control computers, the resulting voting values can be used as a reference for signal arbitration in the next cycle. This design can increase the reliability of the redundancy system and solve the problem of inability to distinguish faults when the signal voting is 2:2 in traditional designs. Finally, using the proposed method, a redundant flight control system was developed for a certain experimental drone, and its effectiveness was successfully verified through ground semi physical experimental testing.

Given the exponential growth in satellite numbers and mission demands, the imperative to sufficiently harness satellite observation capabilities has propelled multi-satellite cooperative observation into an inevitable trajectory. Task planning of multi-satellite is a typical NP-hard problem characterized by an extensive solution scale, which is conventionally addressed using a single heuristic algorithm. However, the employment of such algorithms is con-strained by limitations like premature convergence, thereby presenting challenges in tackling this problem. To overcome this issue, this paper initially establishes a parameter optimization problem for coordinated scheduling of multi-satellites with maximizing observation profit as the performance index. Secondly, a two-layer solution architecture is proposed based on Tabu Search and Genetic Algorithm (TS-GA) feedback optimization to decompose the original problem into subproblems of mission allocation of multi-satellite and several single-satellite mission scheduling. The simulation results demonstrate that TS-GA facilitates acquiring a superior observation scheme. Owing to the implementation of a load-balanced strategy, TS-GA exhibits faster convergence and achieves a more reasonable distribution of planning results.

The Dubins curve holds significant application potential for fixed-wing unmanned aerial vehicle (UAV) formation flying and obstacle avoidance. For the purpose of accelerating its practical application, a consistent method for generating Dubins paths of different dimensions suitable for fixed-wing UAV is proposed, and the corresponding flight experiments are verified. First, a computationally lightweight Dubins path generation approach, featuring a closed-form expression, is employed to plan feasible two-dimensional paths for UAVs. For the reasonably simplified three-dimensional path problem, different geometric methods are utilized to extend the 2D path vertically for different flight path angles, achieving a threedimensional path that meets all specified constraints. Thereafter, the integral flight experiment architecture that includes off-the-shelf hardware and elaborately designed software is suggested to realize the flight test. Finally, the comparative experiments of flight parameters were performed to determine the effect of different parameters on the path tracking results, especially tracking period and waypoint selection. The path flight experiments confirm that the fixed-wing UAV can effectively execute the planned path of different dimensions in a real complex environment. Moreover, the experiments reveal that fixed-wing UAVs have systematic lateral errors in tracking the Dubins path.

Traditional updating methods based on numerical simulation are computationally expensive and are not suitable for model updating with limited resources or time constraints. The computational model updating calls for effi-ciency improvements urgently to address this issue. In this study, a computational model updating method that replaces numerical simulations with surrogate models is proposed to reduce computational costs. A Kriging model is established using the thermal conductivity and emissivity of each layer of the multi-layer insulation structure as input and the temperature of the inner surface of the structure as output. Compared to numerical simulation, the Kriging model offers a significant improvement in computational efficiency, resulting in a three-order-of-magnitude reduction in computational costs while maintaining a prediction accuracy within 0.02%. The proposed method successfully updated the computational model with a maximum relative error of only 0.015%. The method provided can serve as a valuable tool for the rapid thermal design and parameter inverse identification of multilayer thermal insulation structures.

In order to increase the combat radius and flight time of the sub-aircraft, low-cost sub-aircraft are used to carry out reconnaissance and strike missions. The unmanned carrier aircraft transports the unmanned sub-aircraft to the destination and launches the sub-aircraft from the launch cylinder. During the launching process, small air-launched foldable UAVs are susceptible to carrier's airflow interference, which affects safety and stability. In order to study the separation process of sub-aircraft launching and avoid the risk of collision, XFlow software was used to simulate the launching process under the working condition of no side wind, backward horizontal launching, carrier cruising speed of 40m/s and launching speed of 5m/s. The simulation recorded the trajectory of the sub-aircraft dropping, and the data showed that sub-aircraft could be separated safely. From the section velocity nephogram and surface velocity nephogram of the flow field during ejection, there is obvious interaction between the sub-aircraft and the trailing edge of the carrier, but the sub-aircraft does not have much influence on the flow field near the surface of the carrier . Under the same working conditions, an air-launch separation test was carried out. In the launching process, the carrier aircraft is basically not affected by the sub-aircraft separation throughout the whole process, while the sub-aircraft is affected by the flow field of the carrier aircraft's wing in the initial stage of placement, which produces a certain degree of interference, and there are fluctuations of no more than 10° of pitch angle and roll angle within 2s out of the launch cylinder. With the sub-aircraft gradually moving away from the carrier, the interference of the sub-aircraft by the carrier is gradually weakened, and safe separation can be achieved.

This paper investigates the three-dimensional (3-D) homing guidance problem with blind cone constraint. And an optimal guidance approach is proposed to address this issue. The proposed optimal guidance law is designed based on the optimal 3-D pure proportional guidance (PPN) with an additional bias term by lever-aging the predictor-corrector concept and optimal event-trigged control. The terminal impact vector of PPN is first analytically predicted with the Rodrigues’ rotation formula and its impact vector dynamics is established driven by the bias term. Then the bias term is designed as an event-triggered controller with optimal control theory. The controller will be triggered if the impact vector will fall into the blind cone and force the impact vector to deviate from the blind cone. The main benefit of the proposed guidance law lies in its optimal nature and robust characteristics. Hence it outperforms the impact-angle-control guidance law with preassigned an-gle. Theoretical analysis is performed to demonstrate its command characteristics and reveal its working principle. And numerical simulation results are presented to support our findings.

In response to the configuration problem before cooperative tasks of heterogeneous aircraft, the task scenario of multiple unpowered aircraft completing material delivery task was first determined. Secondly, considering behaviors such as cooperative detection during the task process, and factors such as survival probability considering the speed and maneuverability of both parties, cooperative positioning, cooperative target recognition, and cooperative deployment were modeled. With cost-effectiveness ratio as the indicator function, a mathematical model is provided to measure the quality of configuration results. We designed two types of particle encoding: quantity configuration operator and grouping operator, then combined discrete particle swarm optimization(PSO) algorithm and differential evolution algorithm(DEA) to design a double layer search algorithm to optimize quantity allocation and grouping simultaneously. The simulation results of de-signing scenario parameters show that this method can obtain the optimal quantity configuration and grouping results.

Hybrid aquatic-aerial vehicle (HAAV) susceptible to tremendous impacts when entering water at high speeds, leading to structural damage and internal component failure. Improving the buffering performance of the head structure of HAAV is crucial. In this work, an impact resistant metamaterial with negative Poisson's ratio (IRMN) was proposed by introducing the pores existing in the microstructure of bamboo into the honeycomb metamaterial. Compression deformation tests and finite element analysis were conducted on the metamaterials fabricated by additive manufacturing. The deformation of IRMN exhibited a nonlinear response with compressive loads. Facing small loads, the presence of pores inhibited the growth of the effective stiffness of IRMN by changing stress distribution, and the structure was more prone to absorb energy through deformation. Facing larger loads, the effective stiffness of IRMN climbed sharply driven by auxetic effect, and the structural stability was enhanced to prevent damage. When the compression amount of samples increased to 20 (mm), the reaction force of IRMN improved by 177.30% compared to traditional honeycomb structure, presenting a better resistance to external force. Therefore, IRMN possessed the potential to be an efficient energy absorption structure due to its greater stiffness, stronger energy absorption and better stability.

The inlet performance of an air-breathing aircraft plays a key role in its cruise flight. The uncertainty and random disturbances in inflow conditions pose a challenge to the inlet performance. This paper conducts research on the optimal design of the supersonic inlet taking into account the uncertainty of the inflow to improve the robustness of the inlet performance. The polynomial chaos expansion method is used to conduct uncertainty analysis, and the expansion coefficient is obtained through the sparse grid point allocation method. Sensitivity analysis of the inflow uncertainty parameters is further conducted to determine the key influencing parameters. Finally, combined with uncertainty analysis and gradient-based optimization method, the supersonic inlet is optimized considering uncertainty. The results show that under the condition of inflow disturbance, in order to meet the flow requirements of the engine, the capture area of the uncertainty optimal design is larger than that of the deterministic optimal design. The optimization design method considering uncertainty can effectively improve the robustness of the inlet performance.

The pyrolysis and coking reactions play an important role in the fuel heat transfer within regenerative cooling channels. A numerical simulation was conducted to investigate the thermophysical properties and heat transfer characteristics of engineering fuels. A two-dimensional heated tube model was constructed to perform simulations on the heat transfer characteristics of hydrocarbon fuels. The comparison was made between engineering fuels regarding the differences in thermal cracking coking characteristics using the MC-Ⅱ model. The surrogate models for the thermophysical properties of fuels were established at 3 MPa and 4 MPa. The numerical results indicate that in comparison with HF-I, the heat transfer efficiency of HF-II is lower due to a combination of its thermophysical properties and distribution characteristics of pyrolysis products. Moreover, the high concentration of aromatic hydrocarbon in the pyrolysis products of HF-2 promotes non-catalytic coking. At 15 minutes, the maximum thickness of the wall coking layer for HF-1 is approximately 0.01 mm, while for HF-II it reaches about 0.16mm. The fuel inlet temperature significantly impacts the amount of thermal cracking coking in the condition of HF-II. At an inlet temperature of 400 K, the wall coking amount is approximately four times greater than that observed at 300 K.

The accurate trajectory prediction of an incoming missile enables defense systems to effectively neutralize potential threats, thereby protecting civilian populations, military personnel, and infrastructure. Current researches focus on prediction under the assumption of knowing the attack target at the beginning of the engagement, which is seldom the case in reality. To deal with this issue, an intent recognition model based on a Gated Recurrent Unit (GRU) neural net-work is proposed in this paper. The inputs of the network are the available measurement information between the target and incoming missile, while the outputs are one-hot labels. To increase the training speed of the network and enhance its generalization capability, the adaptive moment estimation (Adam) algorithm is adopted for the training process. Based on the information from the network, a cubature Kalman filter (CKF), which integrates a higher-degree cubature rule to approximate the state distribution of the nonlinear dynamic system, is introduced to estimate the state and predict the trajectory of the incoming missile. Simulations present the transition process of the network and demonstrate that the proposed method achieves faster convergence and higher prediction accuracy compared to traditional approaches that are solely based on Kalman filters.

With the increasing number of space missions, the quantity of spacecraft and space debris has surged dramatically. The technology for on-orbit servicing (OOS), applied in space debris removal, retrieval of defunct spacecraft, rendezvous and docking, has developed greatly in the field of aerospace. The real-time six degree-of-freedom pose estimation of space objects holds significant value in on-orbit tasks such as spacecraft rendezvous and docking, on-orbit capture and servicing, as well as space debris detection and removal. In this paper, a continuous space-craft pose estimation method based on Kalman filtering and Long Short-Term Memory (LSTM) networks is proposed. A one-stage pose estimation network is designed for a single-frame image, employing a multi-scale structure to enhance pose estimation accuracy. Additionally, an LSTM network considering Kalman filtering is introduced, which explores temporal information to further improve the continuity and robustness of pose estimation. The proposed method is validated on both simulated and experimental datasets. Experimental results demonstrate certain advantages of continuous pose estimation method in terms of pose estimation accuracy and continuity.

For the attitude control problem of jet-driven spacecraft, this paper proposes a reinforcement learning (RL) based attitude control optimization algorithm (LAC), which optimizes the controller/policy's energy consumption while satisfying stability constraints. The algorithm incorporates three neural networks: the control policy network, the Lyapunov neural network, and the energy neural network. The control policy network directly outputs the forces of the jet thrusters, implicitly solving the thrust distribution optimization problem under the given control torque. The Lyapunov neural network and the energy neural network are respectively utilized to describe the stability constraints and energy consumption of the control policy network. The proposed control policy optimization algorithm employs the Lagrange multiplier method to optimize the control policy network, to minimize the energy consumption with the sample-based stability constraints. Numerical simulation results demonstrate that, compared with traditional RL algorithms and attitude control methods, the proposed attitude control algorithm exhibits significant advantages in terms of energy consumption.

Making good use of Space Station and maximizing its value is the important work in the manned spaceflight field currently. The time and frequency resources in Chinese Space Station are better than that loaded in the navigation satellite. Thus the accuracy of Space Station CV(common-view) time comparison can be better than GNSS(Global Navigation Satellite System) CV that realizes the highest CV accuracy now. But the low orbit characteristic of Space Station magnifies the effect of geometric distance error on CV time comparison, and the geometric distance error is one kind of main errors that need to be researched detailed in order to improve Space Station CV performance. In the paper, the magnifying phenomenon of geometric distance error on CV time comparison is analyzed in theory. Then the factors affecting geometric distance calibration are studied, including orbit error, attitude error, calibration error of antenna phase center, Space Station movement, and so on. Based on simulation experiments, the quantitative effect of these errors on CV time comparison are analyzed. The simulation results show that the Space Station geometric distance error affects the CV accuracy most greatly, and its root mean square error is about 150 pico-seconds. The simulation also shows that the attitude error causes about 20 picoseconds CV errors and the CV error caused by calibration error of antenna phase center or Space Station movement factor is in the magnitude of several pico-seconds. In order to realize the Space Station CV accuracy of several hundred or ten pico-seconds magnitude, the effect of orbit error, attitude error, calibration error of antenna phase center and Space Station movement can’t be ignored. Reducing Space Station’s orbit error is the most efficient way for CV accuracy improvement.

The potential applications of airborne launch cluster unmanned aerial vehicles (UAVs)are enormous. However, planning the trajectory of the carrier aircraft to maximize efficiency while ensuring its safety presents a challenging task. This paper addresses a complex combinatorial optimization problem of a single carrier aircraft conducting multiple UAV release tasks. A comprehensive UAV path planning model has been developed to accurately depict the impact of the carrier aircraft's flight path on task effectiveness. Additionally, we propose an improved non-dominated sorting genetic algorithm-II (INSGA-II) algorithm aimed at finding the optimal release points and sequences. By introducing selection operators, hybrid crossover operators, and an enhanced elite retention strategy, we have made various improvements to the NSGA-II algorithm, enhancing its global search capability and performance. Simulation results conducted in two different scenarios thoroughly validate the effectiveness of the proposed algorithm. A comparison with the original NSGA-II algorithm reveals that the INSGA-II algorithm can find better solutions within an acceptable number of iterations.

The prediction of junction flows, such as those formed around a wing-fuselage intersection, remains a challenge owing to the strong anisotropy. Traditional eddy viscosity models(EVMs) usually predict a non-physical separation. To solve this problem robustly by higher-order methods, this paper proposes alternative scale-providing Reynolds-stress models(RSMs) in which the specific dissipation rate ω transport equation is replaced by λ (λ = 1/⁸√ω = ⁸√τ) in the framework of the original SSG/LRR model . The new scale-providing variable could improve the calculation robustness of turbulence models especially in high-order numerical methods owing to its natural boundary conditions and small gradient near the wall. Besides it is also combined with γ-Re_θt transition model to extend its applications. In addition, some EVMs such as γ-Re_θt SST , SST k-w and SST k-w　with quadratic constitutive relation(QCR) are also implemented as comparations. The solution polynomials of the mean-flow and turbulence-model equations are both discretized by five-order weighted compact nonlinear schemes(WCNSs). NASA Juncture-Flow experimental data is used for validation. Finally, both the velocity components and Reynolds stresses near and upstream of the junction region predicted by the new RSM are better than the EVMs. The calculated range of junction separation zone is also well aligned with experiments. Therefore, the scale-transformed RSM model has successfully improved prediction accuracy in the juncture region compared to eddy viscosity models.

The Multiple Airport Regions (MARs) encompass many busy airports. These airports have high operating density and frequent aircraft movements, making them susceptible to disruptive events. Such disruptions may have a significant impact on the safety and efficiency of air transport systems. This study constructs a New York MARs network model using the complex network theory. Five types of disruptions affecting flight operations were studied, revealing that airspace, carrier, and late aircraft affect flight delays most frequently, while adverse weather leads to the longest delay times. Moreover, 49.36 % of flight delays often result from the simultaneous occurrence of multiple disturbances, with the combined effects of carrier and late aircraft being the most frequent. To assess disturbance effects, a flight cancellation and delay network was constructed to examine the impact of New York MARs on nationwide flight operations using robustness analysis. The results show that flight delays have a greater impact on national flights than flight cancellations due to frequent occurrences. Notably, carrier, airspace, and late aircraft are the most influential factors for flight delays. These findings help to develop more effective flight recovery strategies for different disruptive events and ensure the normal operation of the aviation system as a whole.

This paper focus on parameter-dependent modeling and analysis of morphing wing UAV(MWUAV)’s longitudinal dynamics. Firstly, the nonlinear parameter varying (NPV) model is developed and transformed into input-dependent linear parameter varying(ID-LPV) model using “jacobian linearization” (JL) method. After that, the parameter-dependent flight envelops and dynamic stability are analyzed based on the ID-LPV model and unstable region is found and based on which, the stable operation points are selected. Then, the control effectiveness is analyzed in the linear model and nonlinear simulation is also performed to validate the analysis result, which is consistent with the linear analysis result. Both the linear and nonlinear results reveal the control effectiveness for altitude control using morphing.

To address the problem of the JPS (Jump Point Search) algorithm lacking goal orientation in the pathfinding process, resulting in the presence of many redundant nodes along the explored path and affecting search efficiency, particularly difficult to meet the real-time requirements of high-speed movement for MAV, this paper proposes a JPS algorithm with a backtracking greedy strategy (BG-JPS) based on the greedy approach. Firstly, the type of nodes added to the priority queue during the search process is optimized. Secondly, the goal orientation of the jump point search process is enhanced by estimating the cost value to the destination. Then, through backtracking update the priority of the exploration direction of nodes between two adjacent exploration processes. Finally, simulation experiments are conducted on two-dimensional grid maps of different sizes and complexities. Simulation results show that compared to the JPS algorithm, the BG-JPS algorithm reduces the number of expanded nodes by 30% to 68% and shortens the search time by 16% to 53% across various types of maps, while maintaining similar path lengths. The improved BG-JPS algorithm can effectively addresses the problem of low search efficiency in large-scale scenarios due to the lack of goal orientation in the JPS algorithm.

This paper is based on the theory of sliding mode control, proposing a cooperative guidance law considering target maneuver and impact angle constraints in a three-dimensional environment. Initially, a cooperative interception guidance dynamic model with target acceleration is established. Subsequently, to address the issue of estimating the maneuvering target acceleration, an adaptive second-order sliding mode observer is proposed, which autonomously adjusts design parameters based on estimation errors and provides real-time compensation in the acceleration command. Furthermore, on the normal direction of the line of sight (LOS) and the LOS direction, a cooperative guidance law, which is based on a novel consistency protocol and terminal sliding mode guidance law are introduced to achieve simultaneous saturation attack on the target, ensuring finite-time con-vergence of the LOS angular rate. The finite-time stability of the designed guidance law is demonstrated through Lyapunov theory. Finally, the effectiveness of the proposed guidance law is verified through numerical simulations.

Polarization/Inertial/Celestial (PIC) integrated navigation system presents a promising solution for attitude information acquisition in unfamiliar and electromagnetic interference environments at night. However, the fusion strategy and the installation errors among polarization sensor (PS), star sensor (SS), and inertial measurement unit (IMU) can affect system accuracy. To improve the system performance, this paper proposes an enhanced nighttime attitude determination method for PIC integrated navigation system. In comparison with existing schemes, a novel system model is devised, wherein installation errors are augmented into the state variables, with the angle between moon vector provided by PS and star vector provided by SS being utilized to establish measurement models. By this means, simultaneous estimation of attitude misalignment angles and installation errors can be achieved. Furthermore, in order to enhance the nighttime environmental adaptability, a trimodal fusion strategy is presented, which could assess the effectiveness of the polarization sensor and star sensor, and selects and switches between Polarization/Inertial/Celestial (PIC) mode, Polarization/Inertial (PI) mode, and Inertial/Celestial (IC) mode. Finally, a series of simulation experiments validate the feasibility and effectiveness of the proposed approach.

In high-performance applications, a constant increase of power densities in electrical machines leads to a proportional rise in temperature, which significantly affects its performance and life expectancy. To reduce the temperature rise impact on processing performance, usually, a cooling system will be equipped on the high-power density electrical machine, which can take away the heat in time keeping the machines in the best temperature range. The idea of this paper: primarily is to analyze the heating and heat transfer of stators of electrical machines, consecutively employ parameters in different operating conditions; by using computational fluid dynamics (CFD) simulation to find the thermal parameters of the cooling system. Based on the simulation, the influence of the cooling channel position on the cooling effect is evaluated, which provides a reference for the design of the stator. Also, the impact of the coolant flow on the cooling effect was analyzed. The simulation results are compared with the theoretical calculation results. Some enhancements of heat exchange within cooling tube are adopted. The cooling effect under different designs is analyzed and evaluated based on several established performance criteria.

The control of unmanned aerial vehicle (UAV) swarms represents a complex field of study, chiefly due to the conflicting behaviors observed among individual UAVs and the impact of external movement disturbances on the swarm. However, the fission-fusion dynamics of UAV swarms in response to unknown dynamic disturbances have received comparatively less attention than their behavior in static flight. An unknown dynamic interference environments fission-fusion for heterogeneous UAV swarm via reinforcement (DEFHRL) learning algorithm is presented, which effectively addresses the challenge of fission-fusion control within unknown dynamic interference environments. Firstly, we develop a heterogeneous swarm self-organized fission-fusion control framework that enables multi-swarm fission-fusion maneuvers for UAV swarms. Next, we introduce a topological fission selection algorithm that facilitates control of fission selection under minimal interaction loads, effectively enabling controllable swarm sizes. Finally, we introduce a subgroup adversarial algorithm, grounded in reinforcement learning, designed to conduct dynamic adversarial engagements against unknown interference with minimal resource expenditure. Simulation experiments show that UAV swarms, when operating in dynamic heterogeneous environments, can successfully execute self-organized fission-fusion maneuvers, effectively safeguarding the primary swarm against heterogeneous interference.

This paper provides a concise overview and comparison of high-temperature sandwich structure materials. Specifically, it focuses on the advantages of polyimide/quartz fiber materials within a resin-based composite framework. Additionally, the study explores trends in metamaterial development and highlights existing challenges. Comparative analyses of various sandwich structure types and their respective strengths are presented. Notably, recent innovations proposed by scholars have aimed to broaden microwave absorption bandwidth, enhance microwave absorption depth, and improve high temperature resilience. In the context of sandwich structures, we investigate the impact of geometric parameters, absorber/impregnation layers, and layer count on absorption capabilities. Furthermore, this paper delves into research related to thermal protection of composite sandwich structures in high temperature environments. Specifically, the degradation modes of mechanical and electromagnetic properties under elevated temperatures were analyzed. Notably, this paper observes a decline in static load-bearing capacity and a reduction in inherent frequencies for sandwich structures exposed to high temperatures, revealing gaps in current research. Finally, this paper emphasizes key directions for advancing high-temperature composite material absorptive sandwich structures. These include achieving high strength, high modulus, and improved toughness. Moreover, absorptive properties should extend beyond high-frequency ranges to encompass low-frequency domains. Attention to absorption depth, width, and incident angles is crucial. Additionally, enhancing high-temperature resistance and integrating structural functions are essential future development pathways.

The effect of turbulence intensity on element flow separation in compressors has been well-established at different Reynolds numbers. However, the impact of turbulence intensity on the secondary flow is still not clearly understood and requires further investigation. Therefore, to explore the impact of turbulence intensity on the flow field structure and loss characteristics of the compressor cascade at different Reynolds numbers, this paper utilizes the RANS numerical simulation method to conduct steady-state calculations for the controlled diffusion stator cascade UKG030.3 under various Reynolds numbers and turbulence intensities. The results indicate that there is a different turbulence intensity corresponding to the minimum total pressure loss coefficient for each Reynolds number, which increases as the Reynolds number decreases. Under the high Reynolds number condition (Re=9.9×10⁵), the total pressure loss is insensitive to variations in incoming flow turbulence intensity, and the minimum total pressure loss coefficient occurs at a turbulence intensity of 2%. Under low Reynolds number condition (Re=2.2×10⁵), as the turbulence intensity increases and the laminar separation bubble disappears, there is a stronger momentum exchange on the suction surface boundary layer, resulting in intensified secondary flow. This leads to an increase in total pressure loss near the endwalls, with a turbulence intensity of 5% corresponding to the minimum total pressure loss.

This paper proposes a novel sliding mode guidance law with finite-time convergent theory against maneuvering targets with impact angle constraint and autopilot lag. To mitigate the external disturbance stemming from the target maneuver, an adaptive sliding mode disturbance observer(ASMDO) is used to estimate the target maneuver precisely. During the process of guidance law design, a fixed-time control theory is used during the reaching stage to guarantee the system state convergence time upper bound is relative to the flight time of the missile which can ensure that the stable time of the system state is less than the flight time to avoid large miss distance. Furthermore, the autopilot lag is approximated as a second-order link to be more practical in engineering. After the guidance commands are designed, a controller based on dynamic surface control is designed to track the designed acceleration commands. The Lyapunov method is applied to demonstrate the stability of the guidance law. Numerical simulations prove the effectiveness and progressiveness of the proposed guidance law.

The bio-inspired attitude and heading reference system (BAHRS) is capable of providing a reliable solution for determining attitude and heading determination under conditions of global navigation satellite system (GNSS) signal degradation. A critical challenge in BAHRS data processing is the fusion of polarization sensor (PS) and sun sensor, which significantly impacts system performance. In existing studies, however, observation signals extracted from PS and sun sensor are independently used as measurements when fused with the inertial measurement unit (IMU). The accuracy of the measurements from PS and sun sensors is not assessed, resulting in degraded fusion system performance. To improve the navigation accuracy of BAHRS, an adaptive fusion factor-based PS/sun sensor/IMU fusion strategy is proposed. Specifically, the fusion factor can be dynamically adjusted online based on the accuracy of PS and sun sensor measurements. Consequently, the optimal sun vector can be calculated for fusion with IMU, enhancing BAHRS navigation performance. Moreover, a BAHRS architecture is designed with an integration of compound eye PS and sun sensor. Based on the multi-direction observation structure of compound eye PS, the reliable direction of polarization (e-vector) and sun vector information can be obtained simultaneously, which improve the environmental adaptability of BAHRS. Finally, the effectiveness of the proposed fusion strategy is verified by the simulation, static ground test and unmanned aerial vehicle (UAV) flight test.

The rain ingestion flow field of a four-stage transonic compressor is numerically studied using Lagrange particle tracking method.Considering the breakup, collision and evaporation process of raindrop particles, the influence of water content on the characteristics of multiphase flow field and stable working range of compressor is studied, and the transport process of raindrop in multistage environment is discussed.The numerical simulation results show that the raindrop is broken by the aerodynamic shear force in the front stage of the multi-stage compressor. After colliding with the blade, the raindrop moves to the blade tip and converges near the inner wall of the casing under the centrifugal force.The raindrops are broken into smaller droplets at the back stage of the compressor, and the evaporation process occurs after mixing with high temperature air, thus effectively reduce the air temperature at the outlet of the compressor and improve the wet compression efficiency of the compressor. With the increase of water content, the stable working range of the compressor decreases significantly, and the total pressure ratio and wet compression efficiency increase.When water content ingestion accounts for 5% of the design flow, the stable working range is relatively reduced by 75%, at the design flow point the total pressure ratio is increased by 25%, and the wet compression efficiency is increased by 7.4%. Rain ingestion changes the flow angle matching between each blade row of the compressor. Compared with the design condition, the variation amplitude of the flow angle of attack increases with the increase of water content ingestion and number of stages, and the main variation range is concentrated in the upper half of the blade height. This research provide a reference for revealing the mechanism of multistage compressor rain ingestion flow.

It is significant to improve the performance of air throttling for combustion control in scramjet engines. Therefore, in order to achieve better combustion enhancement effects with less flowrate, the mechanism of air throttling has been studied in depth. The effects of steady air throttling on the flow field structure of an ethylene scramjet combustor are examined under the condition of isolator entrance Mach number of 3.0, the static temperature of 675 K, and the static pressure of 66 kPa by using numerical simulation. The influences of different jet mass flowrate, jet positions, and jet temperatures on the combustion property of the combustor are also investigated. The results demonstrate that the injection of steady air throttling into the cold flow field of combustor produces more shock wave structures and interacts with the boundary layer, which reduces the actual area of the flow path and leads to lower mainstream velocity and higher pressure. Moreover, the injection of steady air throttling into the combustion flow field of combustor enhances the mixing of ethylene with air, enabling higher combustion efficiency. The results also reveal that as the increasing of injected jet mass flowrate, moving forward of injection position, or the raising in temperature all enhance the combustion performance of combustor. Under the assumption of ensuring the same improvement impact of combustor combustion performance, compared with the 300 K jet, the steady air throttling mass flowrate at a total temperature of 1500 K can be reduced by at least 33.3%.

With the advent of unmanned aerial vehicle (UAV) swarm technology, countering UAV swarms has emerged as a pressing challenge requiring immediate attention. Employing UAV swarms with high efficiency-to-cost ratios to counter, disrupt, and intercept enemy UAV swarms has been proven to be a relatively effective countermeasure, prompting extensive research in this field. To comprehensively analyze the progress of intelligent decision-making technology in UAV swarm confrontation, this study initially examined the primary technical challenges faced by intelligent decision-making technology, outlining the establishment and resolution of submodels as the central theme. The study presents three primary models, namely, mathematical programming, game theory, and Markov decision processes, and provides an overview of their current applications and challenges based on relevant theories. Subsequently, the study elaborates on the solution methods for each mathematical model and emphasizes the reinforcement learning-based solving algorithm, highlighting its advantages in the domain of adversarial intelligent decision making. Finally, we summarize the current state and limitations of UAV swarm intelligent decision-making research and offer a perspective on future trends in this field, thereby offering novel avenues for further research.

With the rapid advancement of aerospace technology, interstellar exploration emerges as the next frontier in expanding human activities beyond Earth. The development of interstellar exploration robots stands as an essential and pioneering technological pursuit in this endeavor. Given the intricate topography and inhospitable conditions of extraterrestrial bodies, interstellar exploration robots encounter formidable challenges related to action, survival, durability, and more, thereby demanding elevated standards in robotic technology. This article provides a comprehensive overview of the current research landscape concerning interstellar exploration robots, both domestically and internationally. It systematically examines the present state of technology research, encompassing aspects such as basic configuration, overall structure, control technology, navigation, environmental sensing technology, and thermal control technology. By delineating the existing research status worldwide, the article aims to highlight the strengths and weaknesses of current technological approaches. Building upon this analysis, the article extrapolates future prospects for interstellar exploration robots. It assesses the technical advantages, drawbacks, and challenges encountered in current research, subsequently outlining prospective research directions and key areas of focus for the advancement of interstellar exploration robot technologies.

Film cooling, as an effective approach of active heat protection, has found widespread use in cooling hypersonic vehicles. In this paper, a comprehensive investigation of the cooling efficiency considering multiple factors including nozzle height and cool stream speed has been conducted. Numerical simulations have been applied to re-veal that the cooling stream, with excellent wall adhesion performance, can effectively cool down the surface of the hypersonic vehicle. Particularly, by stabilizing other conditions, higher cooling efficiency can be achieved with larger nozzle height and Mach number. Notably, for small nozzle height, the effect of Mach number on the cooling efficiency can be amplified by the nozzle height, while for sufficiently large nozzle height, this effect tends to be stable. Consequently, with a trade-off between minimizing required cooling stream volume and maximizing the cooling efficiency, the optimized nozzle height is estimated to be 4mm in practical scenarios.

This article investigates the problem of UAV tracking three-dimensional trajectory and an optimal guidance law is proposed to guarantee minimum energy consumption. Based on optimal control theory, we first derive two-dimensional optimal path-point tracking guidance law. Then, the guidance approach is extended to three-dimensional for real application. The proposed method first calculates feature points of the pre-designated trajectory, and then guides the UAV to sequentially pass feature points to track the expected trajectory. The energy optimization can be proved by theoretical analysis and the numerical simulation results also indicate that the pro-posed method is feasible.

In recent years, aerospace engines under severe conditions such as high and low temperatures, ultra-high pressure, intense vibration, reuse requirements, have strict and high demands on the reliability of piping systems both in do-mestic and abroad. It is urgent to develop pipe seals with high-pressure capability, wide-temperature-range adaptability, vibration resistance. In the study, a seal joint with self-tightening cantilever structure for piping system is introduced and compared with other structures in the aspect of geometric characteristics, sealing performance and applications. The structure was then preliminarily dimensioned using the virtual orthogonal experiment method. By employing numerical simulation, the strength, stress and strain distribution under different compression ratio are obtained. The design structural parameters are theoretical verified by simulation with a maximum plastic strain of 0.093 during repeated use and a rebound rate of 89.95%. Leaking tests of the self-tightening seal joints under air gas and hydraulic water are carried out. Ten repetitions of the leakage tests were also carried out. The comparative results of experiments and simulation results show that the seal joints are reliable. The research results also indicate that the self-tightening seal joints have an excellent load-bearing capacity, environment adaptability, stability and are easily removeable and reusable when used in piping system. The self-tightening pipe seal joint has a potential of superior performance in aerospace engine piping systems in future.

Using engine thrust for flight control, also known as Propulsion-Controlled Aircraft (PCA), is a possible emergency control method after total failure of normal flight control system. However, the mechanism differences between PCA manipulation and conventional control surface, as well as the slow response of engines thrust, bring PCA control new characteristics and problems. This paper studies the longitudinal control problem of PCA. Firstly, the feedback effects of different parameters on longitudinal control were studied using the root locus method, revealing the PCA longitudinal feedback control mechanism, and clarifying the key control parameters. Furthermore, the basic assumption of PCA research is extended from traditional “trimmed state” to a more general “non-trimmed state”. A transition state control method for pitch trajectory based on vertical speed is proposed for the case of unbalanced jamming and unknown position of elevators. Then, a dynamic pressure based pitch control method is developed for trajectory control in equilibrium state. The results show that, the proposed transition control method can effectively suppress trajectory oscillations caused by unbalanced elevator jamming, enabling the aircraft to quickly stabilize in a new trim state, and can accommodate the maximum trim range of elevator jamming. The proposed steady-state control method has good control effect, and good robustness against wind interference and center of gravity changes, which can enable the aircraft to land safely in PCA mode.

∞The intake system is vulnerable to icing caused by the impact of supercooled water droplets. This study focuses on analyzing the intake by simulating free-stream and intake airflow conditions. It utilizes the self-developed soft-ware NNWICE of our research group to calculate the flow field using the Reynolds-Averaged Navier-Stokes (RANS) equations while simultaneously computing the water droplet trajectories using the Eulerian method. The investigation encompasses varying conditions of water droplet diameters (MVDs = 10, 20, 40 μm), inflow velocities ( U _∞ = 80, 100, 120 m/s), and air intake rates ( Q = 10, 30, 50 kg/s) to assess their impact on the distribution and changes of liquid water content (LWCs) along the pathway. The numerical simulation findings reveal that increases in water droplet diameter, flow velocity, and air intake rate amplify the asymmetrical effects on LWC distribution and the thickness of the protected area, particularly influenced by variations in intake flow rate and droplet size. Further-more, the study demonstrates a negative correlation between these parameters and the average LWC ( LWC_average ) and the three variables. Consequently, we introduce two comprehensive impact parameters, X₁ and X₂, representing the combined effects under free-stream and intake conditions, respectively. Initial error analysis suggests that X₁ and X₂, effectively characterize average LWC_average , offering valuable insights for future research on discrepancies between intake simulations and free-stream conditions.

Aluminum in solid rocket propellants is a highly desirable ingredient for many applications. This paper aims to have a deep understanding of the influence of high temperature particles in the plume on motor performance and bubbles of underwater jet. In this paper, a numerical computational model has been developed incorporating the dy namic meshing technique with multiphase Volume of Fluid (VOF) method which simulates the transient motion of a plume particle through the gas-fluid interface. Variation of the particle movement is investigated by varying solid-liquid contact angle, particle diameter and velocity. For values of Bo>8, plume particles move through the gas -fluid interface via the trailing transport configuration. Numerical calculations results which the form and breakup of tailing in conjunction with experiment in the references verifies the validity of this model. With this model, this paper also analyzes the characteristics of a particle in the plume, such as the form of cavity, rebound and velocity oscillations. The results of simulation indicate that critical velocity has the greatest impact on behavior of a particle; particle with different speed break up different regions of bubbles of underwater jet, thus both structure of jet and thrust characteristic of underwater solid rocket motor are affected, the plume particles which has critical speed show different characteristics. Besides, the diameter of plume particle and solid- liquid contact angle have a slight impact on the movement of plume particle.

The configuration of an unmanned aerial vehicle (UAV) swarm is flexible and offers significant cost advantages, making it widely used in various task scenarios. One typical application of UAV swarm is regional target search, which involves obtaining target information through collaborative search by multiple machines. This article focuses on the dynamic target search problem with known probabilities and adversarial and avoidance capabilities. Based on Bayesian theory, the posterior probability of the target is calculated by considering its existence probability and detection process, and the probability graph is updated accordingly. Considering the evasion ability of the target, the UAV's search process towards the target is modeled as a Markov chain, and the impact of target evasion actions on the probability distribution of target existence is analyzed. A probability transition model for target existence under adversarial conditions is established, and the probability graph is predicted. To improve the probability of discovering targets within a limited area and time, a multi- UAV collaborative search path planning method is designed. Simulation results, compared with different algorithms, demonstrate that the proposed method can effectively simulate multi-UAV collaborative search scenarios under adversarial conditions, generate efficient search paths, and exhibit strong adaptability to different scenarios.

To enhance the cooperative operation pattern of unpowered aircraft and solve the problem of spatiotemporal aggregation of both evader cluster and pursuer cluster, a cooperative strategy is proposed to ensure consistent encounter time and encounter position for each pursuit-evasion group. With the cooperative strategy, the trajectory is solved quickly based on improved Sequential Convex Programming (SCP). The cooperative strategy of evader cluster is designed, and the solution model for multiple pursuit-evasion groups can be transformed into a trajectory optimization problem under the constraints of fixed coordination time and coordination position for each group to be solved in a distributed manner. To satisfy the demands of precision and real-time guidance, this paper integrates the Receding Horizon Control (RHC) to update the coordination time and coordination position during flight, and solve the trajectory optimization problem in real time. The simulation results show that under the set initial state range, the cooperative strategy can promote the consistency of the encounter time and position of all pursuit-evasion groups. Improved SCP can solve the two-side spatiotemporal aggregation problem quickly in real time when combined with RHC.

The working process of a solid rocket scramjet can be summarised as the mixing and combustion of particle-laden fuel-rich jet(PFRJ) with supersonic airflow. A numerical simulation study was carried out to determine the influence of nozzle arrangement on the combustion of PFRJ. The effects of three factors, namely the number, angle and position of nozzles, on the combustion of PFRJ with supersonic airflow were investigated in terms of flow parameters, combustion efficiency, temperature distribution and particle trajectory, respectively. The results show that: (1) Increasing the number of nozzles increases the contact area between the PFRJ and the supersonic airflow. Increasing the nozzle angle not only increases the penetration depth of the PFRJ, but also distributes them more widely in the span direction. (2) Nozzle angle has little effect on the combustion efficiency of PFRJ. However, when the nozzle position is arranged on both sides, the combustion efficiency of gas and carbon particles in PFRJ is significantly improved. (3) The gas and particles have the characteristics of zoned combustion. Too concentrated heat release from the gas is not conducive to particle heating and ignition. Particle combustion requires a high temperature and oxygen rich environment. How to create and introduce particles into a high temperature and oxygen rich environment is the key to improving particle combustion efficiency. The low combustion efficiency of boron particles has become the main reason for limiting the energy release of PFRJ.

In this study, an improved Grey Wolf Optimization (GWO) algorithm was designed to optimize the deployment of multiple interference unmanned aerial vehicles (UAVs). First, a scenario model was constructed based on an electromagnetic wave propagation model. Second, using multi-UAV multi-target interference as the task objective, an interference effectiveness evaluation function was built by introducing a low-coverage-efficiency reduction factor based on the global interference-to- noise ratio. An improved GWO algorithm with a reverse learning strategy was employed to solve the task optimization problem, and simulation experiments on interference UAV deployment tasks under different task pressures were conducted. The results show that, compared with the traditional GWO, the proposed algorithm exhibits a superior adaptability under different task pressures represented by the ratio of drones to targets: in high task pressure scenarios, the convergence speed of deployment schemes generated by the improved GWO algorithm has increased by 7.71%; under moderate and low task pressures, the stability of interference efficiency in the generated schemes has improved by nearly 30%; and the interference efficiency across different task pressures remains largely consistent. This demonstrates that the capability of improved GWO algorithm to accommodate interference UAV deployments across diverse task pressure scenarios, excelling particularly in high-pressure environments.

The INS/CNS integrated navigation method based on the Strapdown Inertial Measurement Unit and Star Sensor combines the advantages of the two navigation methods, which can achieve high dynamics and high accuracy of integrated navigation. The system error model of traditional INS/CNS integrated navigation strapdown installation needs to linearize the inertial misalignment angle and the installation errors of inertial and star sensors, and establish high-order observation equations. When the installation error is large, it will affect the accuracy of misalignment angle, thereby affecting the effectiveness of integrated navigation. This article focuses on the characteristics of INS/CNS strapdown installation systems and studies a linear error model with only inertial misalignment angle. The effectiveness of the model method is demonstrated through mathematical simulation, and the accuracy of the misalignment angle is calculated. In the process of solving the misalignment angle in this model, there is no need to separate installation errors, which reduces system complexity.

Complex separated flow that occurs under conditions of high angle of attack or high maneuverability flight of advanced aircrafts, induces aerodynamic phenomena like sudden changes, dynamic hysteresis, and periodic oscillations, which produce unfavorable effects on control system and flight safety. With the rapid evolution of flight vehicles, numerous studies on dynamic characteristics by wind tunnel test and numerical simulation conducted by research institutes and universities have laid solid foundation for the prediction of aircraft dynamic characteristics. The present paper summarized recent improvements of key technologies such as test model motion simulation, unsteady aerodynamic measurement and flow/motion integrated numerical simulation. A dynamic derivative test system based on the electronic cam was successfully established with test frequency up to 10Hz, a high bandwidth aerodynamic test technology based on accelerometer array was first proposed with the test bandwidth larger than 1000Hz, and the integrated aerodynamic/kinematic simulation technology based on Adams Prediction-Correction Scheme was developed, with unsteady flow patterns of typical configuration been simulated accurately.

Hazardous ionospheric gradient is a critical risk source to be monitored for navigation service supported by the ground-based augmentation system (GBAS). Carrier phase-based ionospheric gradient monitor can simultaneously be sensitive to multiple types of hazardous ionospheric gradients. The monitor is developed by using multiple spatially separated reference receiver antennas. The performance of traditional ionospheric gradient monitor is greatly depending on the baseline length and direction consists of antenna pairs. The null space ionospheric gradient monitor is widely adopted to reduce the dependence of ionospheric gradient monitoring on baseline selections. With the BeiDou system (BDS) widely providing navigation services in the civil aviation, the long-term ionospheric gradient monitoring facility based on BDS is under continuous construction. In this paper, we will focus on evaluating the sensitivity of multi-baseline collaborative ionospheric gradient monitoring based on BDS. A two-dimensional numerical simulation is utilized to verify the multi-baseline collaborative ionospheric gradient monitoring method. The simulation results have shown that the null space ionospheric gradient monitor has the smallest detection blind zones compared with the other traditional method. In addition, it has been proven that the real-time protection of hazardous ionospheric gradient by the multi-baseline collaborative ionospheric gradient monitoring method based on BDS is achievable.

This paper investigates the issue of impact-time-constrained guidance problem for a gliding missile and proposes a machine learning-based approach. A three-hidden-layer Deep Neural Network (DNN) is adopted with each layer included 100 neurons to realize the accurate prediction of the time-to-go of proportional navigation guidance (PNG), and an analytical impact time constrained guidance (AITCG) law is developed using the outputs of the DNN. Then a bias term is developed to nullify the difference between the predicted time-to-go and its desired value. The main benefit of this approach lies in its accurate time-to-go prediction with DNN for a highly nonlinear system. Hence the impact time will be corrected in quite an efficient manner. Simulation results demonstrate that the trained DNN accurately estimates the time-to-go and the AITCG law can meet the need of the impact time control. Numerous Monte-Carlo simulations are performed to support our findings.

The internal flow dynamics within transonic compressors are characterized by a complex interplay of phenomena including shock waves, turbulent boundary layers, and vortices. Among these, the interaction be-tween shock waves and turbulent boundary layers (SWTBLI) stands out as a significant challenge in transonic compressor flow fields. This paper employs a high-precision Computational Fluid Dynamics (CFD) approach, utilizing the k-ω turbulence model, to analyze the flow behavior of Rotor37 within the transonic com-pressor. Specifically, we focus on studying the SWTBLI phenomenon within the rotor channels. The obtained results agree with the experimental values, and the total pressure ratio calculation error is less than 4%. Notably, due to the significant losses caused by shock waves, the adiabatic efficiency of Rotor 37 calculated is slightly lower than the experimental values. The calculation procedure developed in this paper can accurately predict the details of the shock wave/turbulent boundary layer interference in the rotor blade passages, which indicates that the CFD calculation procedure is suitable for flow calculation of transonic compressors.

This establishes a mathematical model rooted in blade element-momentum theory, to accurately predict propeller aerodynamic loads under oblique inflow conditions. Leveraging this model, we achieve rapid computa-tion of propeller aerodynamic loads. High-precision CFD methods verified the aerodynamic load calculation procedures of the propeller under different inflow angles, and the calculation errors of procedures were all within 10%. Under the same oblique flow angle condition, the aerodynamic load change rules on propellers with different blade numbers were analyzed. The calculation results show that the pulsation amplitude of the bending moment and tangential force of the single propeller blade increases with the number of blades. In addition, the max value of the bending moment and tangential force of the propeller increase with the number of blades within a small fluctuation range. The number of fluctuations in a rotational cycle is the same as the number of blades.

The Internet of unmanned aerial vehicles (UAVs) is a flying ad hoc network (FANET) of multiple UAVs connected via wireless links, where the UAV nodes share information and cooperate with each other through real-time communication. To improve the system capacity, the data packets of different links transmit in parallel where some of the UAVs work as relaying nodes to forward data. Due to the interference of wireless channels and the dynamic topology of the network, parallel data routing is challenging in the Internet of UAVs. Traditional routing protocols may fail for three reasons: the wireless interference decreases the channel capacity; the dynamic topology makes it harder to keep the routing table; parallel data routing may cause path collision. As a result, we propose a cooperative routing approach for parallel data transmissions in the Internet of UAVs with a deep reinforcement learning algorithm. The scenario can be modeled as a multi-agent path finding (MAPF) problem where each data packet can be treated as an agent. Specifically, each agent observes and evaluates its adjacent nodes’ features instead of keeping routing tables and selects one as the next hop until arriving at the destination. In order to encourage cooperation between the agents, the reward of their actions is set as the increment of system throughput rather than the rate of their own paths. With centralized training and decentralized execution (CTDE), the agents learn to cooperatively relay data with the deep q-learning (DQN) algorithm. Compared to traditional routing protocols in wireless ad hoc networks such as the ad hoc on-demand distance vector routing (AODV), our proposed algorithm can significantly improve system throughput and shorten the number of relay hops.

Introduced in this study is the fitting method in the computational aerodynamics field, which, through the motion grid, tracks the boundary between regions with mass and massless regions in the flow field, establishing an algorithm that accurately describes the flow field near this boundary. The domain does not include massless regions with singularity, and the computational grid is distributed only in regions with mass. The main work of this paper expands the original shock fitting method to shallow water equations, using weak solution descriptions of flow behavior near the wet/dry front based on local Riemann problems to address geometrically induced errors caused by grid coordinate trans-formations, the DEER algorithm based on discrete equivalent equations is introduced to eliminate errors in spatial metric discretization, achieving volume conservation law in finite difference methods. By comparing the new algorithms with thin-film algorithms using examples of dam break over a flat plane on dry beds and dry-bed generation, the research results show that on coarser grids, the new algorithm can capture accurate velocity fields near the wet/dry front that thin-film algorithms cannot discern, with higher resolution and computational efficiency compared to conventional methods.

Optimizing the aerodynamic layout is an important means to improve the flight efficiency of aircraft. For gliding unmanned aerial vehicles (UAVs) with foldable wings, represented by bionic flying fish, this work studies the optimization of wing surface shapes using surrogate models to improve the gliding distance of the UAVs. The wing surface shape is parameterized using Bezier polynomials, and the aerodynamic performance of a 3D bionic flying fish UAV is simulated using computational fluid dynamics (CFD) methods. A surrogate optimization model is established using Kriging method, and the Expected Improvement (EI) is selected to improve the fitting accuracy of the surrogate model. A three-degree-of-freedom gliding trajectory model of the aircraft is established, and the wing surface shape is optimized to maximize the gliding distance under specific operating conditions. The results show that the optimized wing surface shape has typical swept-back characteristics, and the leading edge of the wing surface deviates significantly from a straight line, exhibiting the morphological characteristics of a biological wing. The gliding distance obtained by optimizing the wing surface layout based on the lift-to-drag ratio is significantly smaller than that obtained by optimizing for the gliding distance. For different gliding conditions, the optimized wing surface shapes show significant differences. This indicates that there is a strong coupling between the wing surface shape and the flight conditions in determining the gliding distance. Therefore, in optimizing the wing surface shape, the flight conditions of the aircraft need to be considered appropriately to achieve the maximum gliding distance.

The trajectory optimization challenge, especially with multiple no-fly zones (NFZs), often leads to many local optima. Using mixed-integer programming (MIP) improves chances for finding global optima but at the cost of increased computation due to many binary variables. To speed up solving, this study uses variable substitution, which changes NFZ constraints into simpler upper and lower bounds and uses binary variables for path decision, matching the number of NFZs. Inspired by sequential convex programming (SCP), the issue with a mix of strategies that make the problem easier to solve is tackled, leading to the creation of the hybrid iterative convex programming (HICP) algorithm. Testing in different situations verify the effectiveness of the HICP algorithm. The HICP algorithm demonstrates robust adaptability and significant computational efficiency, capable of producing trajectories that navigate around the general NFZ in under 5 seconds, underscoring its substantial practical value.

In recent years, the threat of UAV swarm weapons to air security is increasing, the full coverage detection of the incoming target swarm and the acquisition of the global movement information of the target is the premise and key to achieve efficient interception. Therefore, this paper proposes a coverage-based cooperative searching method for UAV swarm under multi-sensor errors. First, according to the typical spatial distribution characteristics of the incoming target swarm, the studied problem is simplified to a two-dimensional plane. Then, the detection probability distribution function of the ground-based rader and UAV airborne seeker are established, respectively. Based on these functions , a cooperative searching assignment model for maximizing detection probability of target swarm is proposed, where the flight safety distance constraint of the prusuer UAVs is also considered. Subsequently, the grey Wolf algorithm is applied to solve the multi-constraint multi-decision variable optimization probelm and generate the expected formation and line of sight direction of the UAV. Numerical simulation demonstrates that the proposed algorithm can efficiently detect the target swarm with a field coverage probability of no less than 99%, and the allocation time does not exceed 1.2 seconds.

Based on the fluid momentum equation and its Reynolds-averaged form, the fluctuation velocity equation is derived. By assuming the incompressibility of fluctuation velocity and applying the Bernoulli equation to handle the viscosity term and pressure fluctuation term in the fluctuation velocity equation. Then drawing on the partial averaging approach of the GAO-YONG turbulence model for fluctuation velocity, the relationship between the derivative of fluctuation velocity and the derivative of partial average fluctuation velocity is established through the introduction of turbulence kinetic energy spectrum theory, thus obtaining a new partial average fluctuation velocity model equation. Finally, this equation is integrated into a CFD program to simulate turbulent boundary layer flow over a flat plate. After adjustment and optimization, the simulated boundary layer velocity distribution agrees well with experimental data, although differences exist in the distribution of fluctuation velocity compared to experimental data, especially in the log-law region, indicating that the model equation needs further study and improvement.

In order to study the low energy impact resistance of re-entrant star-shaped (RES) and re-entrant circular star-shaped (RECS) honeycomb sandwich panels with negative Poisson's ratio, the finite element model of honeycomb sandwich panels with composite laminates and ABS honeycomb was established by commercial software ANSYS/LS-DYNA. The impact response of composite sandwich panels with RES honeycomb and RECS honeycomb is analyzed numerically at low impact energies of 10J,15J and 30J. In this paper, impactor displacement versus time curves, contact force versus time curves and energy absorption ratio of sandwich panels under different impact conditions are analyzed and compared. The simulation results show that under the same impact conditions, the damage depth of RECS honeycomb sandwich panels is greater than that of RES honeycomb sandwich panels, and the difference is more obvious when under in-plane impact. In addition, the impactor has a lower rebound speed after impacting RECS honeycomb sandwich panels, that is, the RECS honeycomb sandwich panels has a higher energy absorption ratio. According to the above results, it is concluded that RES honeycomb sandwich panel has better low energy impact resistance than RECS honeycomb sandwich panel, but the latter has better energy absorption performance.

This paper presents a three-dimensional leader-follower spatiotemporal cooperative guidance method, to address the issue of intercepting incoming small low-altitude unmanned aerial vehicle (UAV) using UAV swarm. A three-dimensional engagement geometry between the UAV and the target is established in the line-of-sight (LOS) coordinate system, to eliminate the small angle assumption and linearization requirement. Based on the LOS coordinate, a finite-time angle-constraint guidance law is designed for the leader UAV, en-abling the leader UAV to intercept the moving target at the desired angle. Based on the multi-agent consensus theory, multiple follower UAVs without airborne seekers form a spherical encirclement formation around the leader. And the center position and radius of the encirclement formation is adaptively regulated according to the current information of UAVs. As a result, simultaneous interception against the target is achieved without estimating time-to-go and avoiding collisions between UAVs. The convergence and stability of the proposed guidance law is proven based on Lyapunov theory. Simulation results demonstrate that the proposed law can simultaneously intercept the target with a spherical encirclement formation.

To improve the aerodynamic performance of ducted propeller, the circumferential kinetic energy of the propeller is recycled by introducing swirl recovery vanes (SRVs) downstream of the blade to generate extra thrust and improve the propulsion efficiency. In this paper, the influence mechanism of duct propeller with SRVs are studied by using high-fidelity CFD method in hovering condition, the relationship between SRV design parameters and propulsion efficiency improvement is illustrated from SRVs axial position and number of SRVs. The research shows that SRVs have coupled flow interference with the blade and duct, the thrust and power consumed by the blade are reduced, but the thrust generated by the SRVs makes up for this loss, while the SRVs as a fixed component do not consume power, resulting in a 5.08% increase in propulsion efficiency, and the highest propulsion efficiency when the SRVs are located at 47% of the duct chord length, the best number of SRVs is six. In addition, the SRVs generates a torque in the opposite direction of the propeller counter-torque, reducing the ducted propeller counter-torque by 63.1%.

The rotor system of a certain type of aerospace transfer pump adopts a SiC-PEEK sliding bearing pair. During operation, the phenomenon of SiC particle shedding from the bearing surface occurs. To investigate the influence of SiC particles on the operating characteristics of sliding bearings, this article sets up a sliding bearing test rig to simulate the working conditions of the aerospace transfer pump, and conducts bearing operation experiments using this platform. Suspensions of SiC particles with different particle sizes and concentrations are injected into the lubricating water used for bearing operation. The current fluctuations during the operation of the sliding bearing are observed, and the changes in bearing morphology before and after the experiment are compared and analyzed. The results show that SiC particles do not affect the bearing operation stability, but increase the operating power. The current at the moment of startup is twice that of stable operation. At the same time, it is found that the addition of SiC particles will aggravate the abrasive wear of the bearing.

Accurate perception of flow data in flight is critical for the navigation, guidance, and control of aircraft. Flush Air Data Sensing (FADS) is a new type of non-intrusive flow sensing technology that mainly uses distributed pressure sensors on the surface of an aircraft to indirectly sense flow parameters without deployment mechanisms. For wide-speed range flight air data measurement, this research constructs a multi-physical parameter flow sensing system based on a dimensionless input-output neural network model. The flow sensing system combined with the data-driven model can realize high-fidelity real-time perception of multiple flow parameters such as Mach number, angle of attack, and sideslip angle under wide-speed range conditions. This study adopts a data-driven feature sparsity method to realize the model compression without compromising accuracy. The data-driven feature sparsity method decreases the storage space and computing time of the flow sensing algorithm for a resource-constrained embedded computing platform. The system performance and reliability of the proposed framework were tested on the embedded computing platform. The experimental results show that: the measurement error of the Mach number is less than 0.05; the measurement errors of the angle of attack and sideslip angle are both less than 0.6 degree.

The unmanned air vehicle (UAV) can provide a wider field of view for tanks to improve their survivability. And an optimal guidance law that makes UAVs follow a circular trajectory around the tank is proposed by introducing a relative reference frame. The guidance law consists of two phases: the first phase is for surveillance orbit entry, in which the UAV enters the orbit from the direction that is tangent to the circular orbit around the tank; and the second phase is for orbit holding, in which the UAV tracking circular orbit even though the tank performs active maneuver. Mathematical methods are used to analyze the convergence of lead angles and acceleration in the first phase and the convergence trend of path errors in the second phase. Numerical simulations are performed to validate the proposed guidance law.

Composite materials have been widely used in the aerospace industry due to their high specific strength, high specific stiffness, good heat resistance and great designability. In practical situations, composites may be stroked by foreign objects under compressive prestress. Therefore, it is of great engineering meaning to investigate impact resistance of composite materials under prestress. In the present work, the impact responses of composite plate subject to compressive prestress are studied experimentally and numerically. At first, a series of ballistic impact tests were conducted on composite plates through gas gun system where a specially designed fixture was employed to exert uniaxial compressive prestress on the target plate. Then the corresponding numerical models were established in ABAQUS. Combining the experimental and numerical results, the effects of pre-compressive stress on the impact responses of composite plate were analyzed. Results show that under uniaxial compressive prestress, four damage mechanisms including the weakening of flexural stiffness, the increasing of bending stiffness mismatch coefficient, the deformation of center and the inhibition of matrix crack growth are found. Layering angle of the target plate is believed to be the controlling key to different damage mechanism.

With the rapid development of Beidou satellite navigation system, the relative positioning application based on Beidou is becoming more and more widespread, and the scenario of installing two or more antennas on the carrier is also concerned. If the prior baseline length constraint information that can be accurately measured in advance is strictly integrated into the observation model of relative positioning, it can not only effectively improve the strength of the observation model and enhance the reliability of the whole cycle ambiguity calculation, but also improve the accuracy of relative positioning to a certain extent. How to fully integrate the prior baseline length constraint information into the observation model and design a reasonable and effective full-cycle ambiguity search strategy under the new objective function has become the difficulty and challenge to realize the relative positioning technology of baseline length constraint. In order to improve the reliability of the relative positioning solution, this paper makes full use of the baseline length information between the two antennas of the mobile carrier, and provides a high precision relative positioning method with baseline length constraints. The standard LAMBDA algorithm is extended to the relative location of the baseline length constraint, and the effective search of the whole week ambiguity is realized. The experimental results show that the proposed method uses the base line length information of double antenna which is not fully used in the actual scene to improve the relative positioning solution effect, and has higher reliability than the traditional unconstrained solution.

This paper investigates the impact-angle-constrained guidance problem for anti-ship missiles equipped with strapdown seekers with limited field-of-view. A homing guidance law with switching logic is proposed to satisfy impact-angle constraint and field-of-view limitation. Based on optimal control theory, the impact-angle-constrained term is derived analytically. Then a biased term is designed for restricting look angle when it tends to exceed the pre-designed boundary value. Numerical simulation results demonstrate that the proposed guidance law can work perfectly with different impact angle constraint or look angle limit. Furthermore, the proposed approach requires smaller acceleration capacity and less energy consumption than the other two comparative methods.

Our work revolves around remote sensing object detection, where the scarcity of annotation information poses a significant challenge and hinders adequate training. To address this issue, we concentrate on semi-supervised object detection methods (SSOD), which offer a promising solution into alleviate the problem of limited labeling information.However, in our specific scenario, the self-training nature of these methods, coupled with the filtering mechanism of pseudo-labeled frames, tends to amplify noise due to the arbitrary angular rotation of remote sensing data objects. In light of these challenges, we propose a novel remote sensing task-specific SSOD framework called Splitting Detectors (SLD), which mitigates noise accumulation caused by remote sensing data characteristics. SLD has the following two innovations: (1) The SLD decouples detectors, mitigating task conflicts and thus reducing noise accumulation. (2) The SLD uses the mean-teacher semi-supervised method to train the classification head and the self-supervised method for the regression head respectively, which reduce inaccurate pseudo coordinates error caused by rotation. The Experiments on dota-split datasets demonstrate the considerable superiority of our proposed framework to other state-of-the-arts.

Aiming at the complex environment, unexpected situations, and multi-constraint problems faced by unmanned aerial vehicle (UAV) mission planning systems in dynamic scenes, an online task allocation method based on improved dynamic ant colony labor division (IDACLD) is proposed. The typical scene of multi-UAV task allocation is described, and a heterogeneous multi-UAV multi-constraint model is established via multigroup settings. According to this framework, the environmental stimulus and response thresholds of the dynamic ant colony division of labor model are redesigned, the coupling between task allocation and path planning is considered, and the RRT* algorithm is used to complete path cost estimation, which makes the task allocation result more reasonable in environments containing obstacles. Considering cases involving UAV faults, this study proposes different fault handling strategies to distinguish different fault types and better fit the actual situation of UAV missions. Simulation results demonstrate that the proposed method can quickly and effectively solve the task allocation problem of multiple UAVs in a dynamic environment.

Airborne distributed position and orientation system (POS) relies on transfer alignment to achieve high-precision motion information of remote sensing imaging payloads at three nodes. However, the flexibility effect between nodes severely affects the transfer alignment accuracy, which in turn limits the improvement of baseline measurement accuracy. Aiming at this problem, an array POS system is designed on the basis of quasi-rigid distributed POS, and the fiber grating sensor is used to obtain deformation information to assist the main system to provide high-precision measurement information to the sub-system for transfer alignment. Finally, a ground dynamic test verification platform is built to verify the baseline measurement accuracy. The experimental results show that the array POS can achieve accurate measurement of flexible baselines between multiple nodes, and the baseline measurement ac-curacy is within 0.17mm under the condition of 5.6m baseline, which can provide theoretical support for the application of array POS.

This paper proposes a three-dimensional (3-D) impact time and angle control guidance (ITACG) considering the limit of vehicle's speed to realize the spatio-temporal interception against a moving target. Firstly, a relative coordinate system with its origin attached on the target is constructed, based on which the engagement kinematics is formulated. Then, the guidance law is designed based on the prediction-correction concept in the reference frame, naturally decoupling into normal and tangential directions for impact angle and time constraint, respectively. In the normal channel, the final impact angle of PN guidance is predicted, and then the deviation between the predicted and expected angle is eliminated by leveraging the optimal control theory. Simultaneous strike is guaranteed from transforming the predetermined attack time to the desired relative velocity considering the speed limit. Employing the principles of the optimal control theory, the optimal analytical solutions for both normal and tangential control are derived. In addition, the allowed impact time that considers the vehicle’s speed limit is calculated to judge whether the desired attack time is feasible. The proposed guidance law is proved its feasibility and effectiveness by numerical simulation and comparison in various engagements.

To address the issue of intercepting target unmanned aerial vehicle(UAV) swarms with UAV swarms (SIS), this paper proposes an accurate evaluator to solve the multi-pursuer multi-target assignment（MPMTA）problem, also known as the traditional Weapon Target Assignment (WTA) method, aiming to achieve high-probability interceptions. Firstly, the covariance analysis technique is introduced to calculate the mean and variance of the miss distance, which are combined with the damage radius of airborne warheads to accurately evaluate the probability of interceptions. Then, this accurate index is utilized to formulate the MPMTA model with the consideration of the target’s threat. Additionally, the improved Column Enumeration (ICE) method is introduced to solve the accurate model rapidly and exactly. The ICE method employs the marginal return optimization approach to determine the initial values for the column enumeration problem and effectively combines the advantages of heuristic algorithms in terms of computational speed and the optimality of exact algorithms. Numerical simulations validate the effectiveness of this method based on an accurate evaluator, demonstrating that the accurate interception probability model and precise algorithm enhance the accuracy of the MPMTA assignment problem.

To investigate the altitude control issue of stratospheric airships, a dynamical model and a thermodynamic model of stratospheric airships were established. The Double Deep Q-Network (DDQN) algorithm, which introduces target networks and dual Q-value estimation to reduce the overestimation of Q-values and thereby enhances the performance of the DQN algorithm, was employed. The idea of artificial potential field method was introduced to improve the network convergence speed of DDQN algorithm. Taking the on/off state of the valve as the action input, the improved algorithm is applied to the altitude control of stratospheric airships and analyzed in comparison with the effect of fuzzy PID control. Simulation results show that the DDQN algorithm has significant advantages over the fuzzy PID algorithm in terms of response time, overshoot, and oscillation during the altitude adjustment process, with a steady-state error within 20 meters. Under the consideration of uncertainties, DDQN exhibits better robustness and convergence efficiency.

With the increasing frequency of civil aircraft flying across large water areas, there are more and more situations where civil aircraft flying in the air suddenly need to make forced landing on the water surface. This article uses the equivalent scaling factor of Airbus A320 λ= 1: 30.The model is the research object, and numerical simulations are conducted on the early stage of water forced landing of civil aircraft fuselage at 8 ° and 12 ° angles of attack (350ms). Research has found that compared to an angle of attack of 8 °, the maximum stress on the belly of the aircraft at a 12 ° angle of attack is greater, and the depth of the fuselage entering the water is smaller. In both cases, the maximum stress area appears at the connection between the wing and the fuselage; Before T=215ms, the descent speed at 12 ° angle of attack decreased faster. After T=215ms, the descent speed at 8 ° angle of attack decreased faster. The final result showed that the descent speed at 8 ° angle of attack decreased more than at 12 ° angle of attack.

As a highly integrated equipment system, it is of great significance to improve the reliability of airborne hardware for the function and safety of aircraft. With the increasing development of multi-electric aircraft and all-electric aircraft, the research and development of electric motors is indispensable. In the aspect of aeronautical motors, dual-redundancy permanent magnet synchronous motors (DR-PMSM) have been widely used in aviation field with high reliability requirements in order to reduce the probability of faults and to reduce the effect of faults. Based on the analysis of domestic and foreign technical literature of dual-redundancy permanent magnet synchronous motor, this paper summarizes the fault types and characteristics of dual-redundancy permanent magnet synchronous motor. And then, the measures to improve the reliability of dual-redundancy permanent magnet synchronous motor from two aspects of motor body configuration and control method are summarized. At last, the future development trend of this field and the new ideas of motor design are prospected.

A large number of space debris with rotational motion occupy scarce orbital resources, thus, a de-tumbling phase may be necessary prior to the capturing phase to reduce the risk of collision. A new contactless AC current de-tumbling method based on the principle of electromagnetic eddy current is proposed in this paper. Firstly, an analysis is conducted on external disturbances affecting the attitude of the debris and de-tumbling device, such as magnetic field perturbations. Compared to the electromagnetic forces acting on de-tumbling device, the influence of the geomagnetic force on detumbling device can be negligible. However, the geomagnetic torque acting on de-tumbling device cannot be ignored. Then, the advantages and disadvantages of the two AC current cases are compared and analyzed, and the method to increase the de-tumbling torque can be obtained by adjusting the frequency of the three phase AC current. Finally, the three-dimensional attitude dynamics of the uncooperative space target is established taking a spinning cylinder as the hypothetical target of de-tumbling. Simulation shows that the de-tumbling method is effective and the de-tumbling rate can be greatly improved by adjusting the frequency of the three phase AC current.

In the context of rapid urbanization and the substantial increase in logistics demand, the deployment of Unmanned Aerial Vehicle (UAV) delivery systems has emerged as a pivotal technology for augmenting delivery efficiency and enhancing customer satisfaction. This study tackles the intricate challenge of task allocation among multiple logistics UAVs within urban delivery scenarios, striving to simultaneously minimize transportation costs and maximize customer satisfaction by optimizing the task allocation mechanism. To-wards this objective, we have conceptualized a multi-logistics UAV task allocation model and engineered an avant-garde Improved Genetic Algorithm (IGA) to address this model effectively. The algorithm amalgamates a multi-round roulette selection strategy with a tournament selection mechanism, markedly augmenting the likelihood of selecting superior individuals. Through the amalgamation of sequential and two-point crossover techniques, alongside refined mutation probabilities adjustments, it considerably bolsters search accuracy and expedites the algorithm's convergence rate. Furthermore, the algorithm employs a variegated suite of crossover and mutation strategies to foster population diversity and ensure the preservation of elite individuals, concurrently facilitating the advancement of less fit individuals. Empirical simulation outcomes attest that the enhanced genetic algorithm secures approximately a 50% enhancement in the average fitness function value, adeptly engineering task allocation solutions that are cost-effective and yield higher customer satisfaction, thereby manifesting a pronounced competitive edge over conventional genetic algorithms. This inquiry not only unveils novel avenues for the refinement of UAV logistics delivery systems but also furnishes substantial theoretical underpinnings and pragmatic insights for the intellectualization of future urban community logistics distribution networks.

The super-resolution reconstruction based on sparse measurement information is an important issue in the field of experimental fluid dynamics, and using a small amount of information for high-precision turbulent flow field reconstruction has high research value. Traditionally, interpolation and reconstruction methods are used to reconstruct the flow field. In recent years, artificial intelligence technologies represented by deep neural networks have been increasingly applied to flow field reconstruction problems due to their advantages in handling high-dimensional and nonlinear function fitting problems. However, these methods do not fully consider the physical mechanisms followed by flow field evolution and require a large amount of high-precision data, which may result in high experimental costs. Physical Information Neural Network (PINN) is an unsupervised learning method that utilizes neural networks to fit solutions to partial differential equations of flow field evolution, thereby overcoming the strict requirements of traditional methods on data attributes. However, due to the complexity of the Navier-Stokes equations, the accuracy of traditional PINN methods cannot meet the modeling requirements. This article proposes a PINN based method that effectively combines test data and physical information, and applies this method to the problem of super-resolution turbulent flow field reconstruction. Using high-precision measurement data of turbulence in a square channel as the experimental dataset, the method was used to reconstruct a high-resolution velocity field based on downsampling information of turbulent flow field, and compared with traditional bicubic interpolation methods and flow field reconstruction methods based on Convolutional Neural Networks(CNN). The experimental results show that the PINN method proposed in this paper can quickly complete super-resolution flow field reconstruction using sparse flow field measurement information, and is insensitive to noise in the data. It has significant advantages in accuracy and robustness when the sampling ratio is large.

In this paper, a real-time unmanned aerial vehicle (UAV)-to-ground path loss prediction model via intelligent multi-modal sensing-communication integration is developed in the operational mode of Synesthesia of Machine (SoM). In the modeling process, a dataset including multi-modal sensing and communication data is constructed in AirSim and Wireless InSite to support the exploration of the non-linear mapping relationship between physical environment and electromagnetic space. To explore the mapping relationship between the environmental features extracted from multi-modal sensing image data in physical environment and path loss in electromagnetic space, a convolution neural network (CNN) is constructed and trained. Therefore, based on the dataset, the real-time path loss prediction in the UAV-to-ground scenario is achieved. Simulation results show that the prediction average mean square error (MSE) of the proposed model is 6.4641 × 10^-5 in the test set. The accuracy and utility of the proposed model are validated by comparing the prediction results of the model and ray-tracing (RT)-based results.

To support the development of multiple-unmanned aerial vehicle (multi-UAV) cooperation in emergency communications, an in-depth analysis of multi-UAV cooperative channel statistical properties is conducted in this paper. Based on the wireless channel simulation software, i.e., Wireless InSite, the ray-tracing technology based multi-UAV cooperative communication channel data in the urban earthquake rescue environment is collected. As a consequence, an accurate channel dataset for multi-UAV cooperative emergency communications is established, which provides a solid data foundation for unveiling the multi-UAV cooperative channel statistical properties. Based on the constructed dataset, the multi-UAV cooperative emergency communication channel statistical properties are derived and thoroughly simulated, including cooperative time auto-correlation function (TACF), cooperative space cross-correlation function (SCCF), cooperative Doppler power spectral density (DPSD), cooperative time stationary interval, and singular value spread (SVS). According to the derived and simulated multi-UAV co-operative emergency communication channel statistical properties, some conclusions can be drawn. Specifically, compared to scenarios without earthquakes, cooperative SCCFs between the channels related to different antennas in earthquake scenarios are smaller. Channels under earthquake scenarios exhibit smaller SVS than the scenarios without earthquakes.

In this paper, the propagation characteristics of unmanned aerial vehicles (UAVs) to ground under different frequency bands and scenarios are investigated. A new UAV-to-ground communication dataset that covers vari-ous conditions is constructed. We focus on the sub-6 GHz, 15 GHz, and 28 GHz frequency bands under urban and suburban scenarios with different vehicular traffic densities (VTDs) and UAV heights. Furthermore, we use ray-tracing technology to get high-precision channel impulse response (CIR) with Wireless InSite software. The CIR provides detailed insights into the propagation characteristics of UAV-to-ground communication channels. Some important channel statistical properties, such as space cross-correlation function (CCF), time au-to-correlation function (ACF), and Doppler power spectral density (PSD) are derived. The derived statistical properties play a crucial role in the understanding of wireless channels under different conditions. The UAV channel characteristics under multiple-frequency (multi-frequency) multiple-scenario (multi-scenario) conditions are adequately analyzed and valuable conclusions are further obtained. The simulation results demonstrate that frequency bands, VTD, and UAV heights have distinct impacts on UAV channel statistical properties.

As an emerging space propulsion technology, atmosphere-breathing electric propulsion (ABEP) system can operate for a long time in ultra-low earth orbit (ULEO) without carrying propellant from ground. However, the erosion of intake wall caused by the oxygen-contained atmosphere in ULEO will alter the wall characteristics to some degree, which influences the intake performance significantly. To analyze the influence of wall characteristics on intake performance, the direct simulation Monte Carlo (DSMC) method is used to simulate the gas flow in intake chamber under the mixed inflow of N₂ and atomic oxygen (AO). The density and velocity distribution of flow field for three intake configurations (parabola, cone and cylinder-cone type) are analysed under the varying wall characteristics (reflection coefficient σ from 0 to 1), and the corresponding variations of the collection and compression performance are also obtained. Results show that the increasing of σ leads to the decline of collection efficiency for all three intake configurations. The parabola type intake shows the highest collection efficiency of 93.67% when σ=0 under the specular reflection condition. The compression ratio increases with the value of σ for both parabola and cylinder-cone type, while the compression ratio for cone type intake initially increases then decreases, which reaches the maximum value of 44.36 when σ=0.5.

Conventional design methods of multirotor controllers are based on the inverse of kinematic and dynamical models, and their open-loop structure makes acceleration control defective. Therefore, this thesis designs an acceleration feedback-based controller to refine the thrust control structure and ensure strong robustness in the presence of inaccurate model and aerodynamic parameter estimates. In addition, to compensate for external disturbances and suppress the effect of high-frequency noise on the conventional observer, this thesis develops an adaptive dead-zone extended state observer, which ensures accurate and smooth disturbance estimation. The experimental results of the numerical simulations show that: 1) during hovering, when subjected to a sudden disturbance of 5 N, the AFBC converges faster, with a smaller maximal positional error and a stabilization error is less than 1 cm; 2) the maximum error of the proposed control strategy is less than 3 cm when tracking a dynamic circle with a radius of 2 m and a maximum speed of 2 m/s under a wind disturbance environment of 5 m/s. In summary, the proposed control strategy significantly improves the robustness, disturbance resistance, and tracking accuracy of the multirotor with model uncertainty in a complex environment.

In recent years, with the increasing adoption of robots and the limitations in the safety and efficiency of individual robots, the study of multi-robot formation navigation has gained widespread attention. However, achieving deadlock-free formation navigation with robots maintaining relative distances in obstacle environments remains a significant challenge, particularly in coordinating the tasks of obstacle avoidance and formation maintenance. Addressing this challenge, we propose a framework for robot formation navigation in obstacle environments. Initially, we employ formation-level global path planning to search for global paths that consider both translational and rotational movements of the formation, offering better coordination between obstacle avoidance and formation maintenance conflicts. Subsequently, through a distributed optimization algorithm for robot trajectories under formation constraints, we locally optimize the global paths, enabling robots to dynamically balance obstacle avoidance and distance maintenance tasks during navigation. Finally, we validate the effectiveness of this approach through simulation experiments, demonstrating its practical applicability in complex environments.

Despite the extensive application of Deep Neural Networks (DNNs) across diverse domains, their vulnerability to adversarial examples remains a notable concern. Simultaneously, adversarial patches afford the capability to camouflage one's equipment under DNN-based object detectors. However, the topic has been underexplored in optical remote sensing images (O-RSIs), especially regarding ship imagery. Meanwhile, existing methods for generating adversarial patches exhibit limited attack strategies and fail to effectively adapt to complex conditions during the optimization process. This paper introduces a new type of adaptive patch method for ship physical camouflage (ShipCamou). We designed adaptive components including physical adaptability and target scale adaptability, to meet the adaptability requirements of the adversarial patch under various physical conditions and different ship target scales. Additionally, we developed a new loss function that optimizes the adversarial patch by reducing the average confidence of the target and distorting the detection bounding boxes to deviate from their normal positions, significantly enhancing the attack efficiency of the adversarial patches. Experiments conducted on the HRSC-2016 maritime remote sensing image dataset against a variety of advanced typical object detectors in both white-box and black-box settings have demonstrated the notable adversarial camouflage effect of our proposed ShipCamou under multiple object detectors. Moreover, these effects were observed to transfer across different models. When compared to two typical adversarial patch methods, our approach outperforms them in terms of reducing the average precision and increasing the attack success rate. The results indicate that ShipCamou can deceive object detectors, effectively concealing our ships or other equipment requiring camouflage in O-RSIs.

To investigate the motion characteristics of the gas-solid two-phase flow within the nozzle's flow field, a computational model featuring a turbine rotor is established for the Jet Cat P200 turbo-jet engine. An enhanced stochastic orbital model is employed to simulate the trajectory of rarefied-phase flow particles within the engine's flow field. The distribution pattern and variation characteristics of the gas-phase flow field, gas-solid two-phase flow, and flow field particles at varying air intake total pressures were investigated through numerical simulation using CFD soft-ware. The study reveals that the air intake total pressure has a more pronounced impact on the total energy, density, and static pressure of the flow field. With the increasing of the air intake total pressure, the aforementioned variables will increase correspondingly. Compared to the pure gas-phase flow field, the gas-solid two-phase flow field exhibits similar changes under different intake total pressure conditions, and the effect of particles on the flow state of the field can be disregarded. Besides, it's observed that the intake total pressure has a more pronounced effect on the gas-solid two-phase flow of small-diameter particles.

The study of the characteristics of the pulsating velocity distribution in a flat plate turbulent boundary layer is important for the development of pulsating velocity turbulence models. In this paper, high temporal and spatial resolution measurements of velocity pulsations within the boundary layer of a flat plate turbulence are carried out in a wind tunnel using a laser Doppler velocimeter (LDV). By analyzing the measurement results, a mean velocity distribution curve is obtained, which is consistent with the turbulent velocity distribution curve given by other studies, confirming that the experimental setup of measuring the velocity in the flat plate boundary layer using LDV is reliable in this experiment. The analysis of the statistical results of the pulsation velocity reveals that the root mean square distribution of the pulsation velocity has a distinct inner peak and a small outer peak within the boundary layer, which is consistent with the results of recent studies and further characterizes the distribution of the pulsation velocity within the boundary layer. At the same time, the spectral analysis of the pulsation velocity reveals that the pulsation characteristics in different regions of the boundary layer are different, the pulsation amplitude in the logarithmic law region fluctuates from high to low, and the pulsation in the outer layer of the boundary layer appears to be intermittent.

The ice accumulation on the surface of the aircraft may fall off due to aerodynamic force, mechanical vibration, change of temperature and other reasons, causing serious damage to the downstream parts of the aircraft and constituting a flight safety hazard. To solve this risk problem, based on MC3 risk assessment method, this paper studies the discrete source damage behavior caused by ice fall on the tail of civil aircraft, and establishes the corresponding airworthiness compliance verification method system. Based on the icing and shedding of the wing surface, the critical ice type of the wing surface is determined by calculating the three-dimensional flow field data, and the ice shedding trajectory prediction model is established. Then, the constitutive model of the ice under high-speed impact is analyzed, and the finite element model of the impact of the ice on the tail is established, considering the impact velocity, attitude and impact Angle of the ice on the structural response of the tail. Finally, the system risk value of ice falling off on the tail under different impact conditions is introduced, and the airworthiness compliance verification method of ice falling off on the tail discrete source damage is established. This paper takes A380 aircraft as an example to verify the airworthiness compliance of tail damage caused by ice shedding under typical icing weather conditions, and proves the applicability of the airworthiness compliance verification method system. The method system combines experimental testing and simulation technology, which provides important theoretical support and verification method for the safe flight of aircraft.

Solid rocket scramjet has become a potential choice for the development of future hypersonic vehicles. A boron-containing solid rocket scramjet based on central strut injection was proposed in this paper, and direct-connect experiments and numerical simulations were carried out to verify the feasibility and performance of the scramjet. The engine realized stable combustion in the ground experiments at flight conditions of Ma6 and Ma4, with the combustion efficiency of 81.7% and 70.3% respectively. And the simulation results show that: (1)The simulation results were in agreement with experimental data, with the pressure error less than 4%. (2)The central strut injection mode can effectively increased combustion stability, avoided momentum loss and improved the combustion efficiency. However, the low combustion efficiency of B particles was still the key factor limiting engine performance; (3)The combined injection mode effectively improved the combustion efficiency and increased the gain thrust of the scramjet. And with the rose of Mach number, the increase amplitude of the particles combustion efficiency and the thrust improved, which were 44.8% and 12.8% at Ma 6, respectively.

In the context of the rapidly evolving low-altitude economy, low-altitude logistics, as a crucial component of the modern transportation system, has demonstrated its unique value, especially in the delivery process of high -value-added goods such as biopharmaceuticals that require high timeliness. The logistics delivery via drones necessitates a platform capable of safety regulation and command dispatch to ensure the safety and timeliness of logistics delivery. However, traditional ground transportation methods, susceptible to uncontrollable factors like traffic congestion, tend to result in low delivery efficiency and pose safety risks such as package swapping or damage. Thus, this study proposes an innovative solution: an intelligent delivery system for low-altitude drone logistics based on digital twin technology. The core of this system lies in the use of digital twin technology, combined with drones, diverse sensors, and remote communication networks, to construct a highly digitized virtual delivery environment. Through digital twin technology, drones are precisely designed within a virtual environment, which accelerates the design speed while enhancing design accuracy, ensuring that drones can meet the demands for efficient and precise delivery. Furthermore, the real -time monitoring and optimization capabilities of this technology enable the collection of drone flight data in real-time, monitoring their operational status, identifying issues promptly, and providing optimization suggestions, thereby improving the operational efficiency and safety of drones. The introduction of digital twin technology also allows the system to simulate complex real-world environments, such as densely built urban areas or mountainous regions, aiding drones in conducting preliminary tests and algorithm model training within a virtual environment, thus enhancing their ability to adapt to complex environments. Moreover, the system provides instant digital feedback and optimization suggestions to operators, supporting intelligent decision-making and further enhancing overall delivery efficiency. To verify the system's degree of digital twinning, this study also introduces a virtual -real mapping experiment. It involves fitting the drone flight trajectories in both virtual scenarios and actual physical scenarios, determining the twinning degree through a consistency ratio. Finally, a transportation route from Shenzhen Liantang Port to Pingshan Free Trade Zone was selected as the experimental case, showcasing the system's path planning and data visualization capabilities on this route. This research demonstrates the tremendous potential of drone delivery systems based on digital twin technology in promoting the digitalization, intelligence, and precision of low-altitude logistics delivery.

It is a very worthwhile research topic to investigate the effects of crack on the vibration of propeller structures in engineering practices. In this paper, responses of rotating composite laminated beams with a crack is analyzed under cyclic loading. Edge cracking is considered as a Rotating Massless Spring, then the governing motion of a cracked composite laminated beam in a rotating state are obtained by Hamilton's principle. The harmonic balance method is used to solve the intrinsic frequency of the system and the solution of the eigenvalue problem was obtained. Then the effects of parameters, such as crack depth, crack location, structural rotational speed and mounting angle on the free vibration of the structure are analyzed. The steady state response of the system is investigated using the Runge-Kutta method and derived the effect of crack parameters on the vibration response of the structure. The simulation results show that crack parameters, rotational speed and mounting angle have significant effects on the intrinsic properties as well as responses of rotating composite laminated structures.

Aiming at the problem that the guided projectile is difficult to implement in-flight alignment of roll angle with low-cost gyroscope, this paper proposes an in-flight alignment scheme based on the pitch angle velocity vector caused by gravity. The relationship between the rotation angular velocity measured by the gyroscope and the roll angle at the alignment time is established. In order to avoid the influence of uncalibrated MEMS gyroscope on alignment accuracy, the gyroscope error is modeled and included in the alignment equation. Then the gyroscope error is estimated and compensated by adaptive Adam algorithm. Consequently, the accuracy of alignment can be effectively improved. Mathematical simulations show that the alignment accuracy of the roll angle can be within 3°, and the bias and installation error angle of the gyroscope can be effectively calibrated, which can improve the accuracy of inertial navigation.

In order to improve the combustion efficiency of gas-particle two-phase gas in the combustor of solid rocket scramjet, the influence of the combustor length on the combustion characteristics of gas-particle two-phase gas under Ma6 and 25km inlet flow was studied by numerical simulation. The results show that the main area of fuel combustion is the first expansion section. In addition, part of the fuel is also burned in the equal straight section, which can maintain a high working pressure for the first expansion section to improve the combustion efficiency of the combustor. The second expansion section is conducive to gas expansion work and improves the total pres-sure recovery coefficient. The numerical results show that the gas phase components in the fuel-rich gas can burn quickly after entering the combustor, and the combustion efficiency of the granular phase fuel is the main factor determining the total combustion efficiency of the fuel. The combustion mode is determined by the heat release intensity of gas-particle two-phase gas in the combustor.