Search Results (4,651)

Accurate fatigue life prediction of aircraft landing gear is crucial for ensuring flight safety and preventing catastrophic structural failures. However, traditional empirical methods face significant limitations in capturing complex multiaxial loading conditions, while machine learning approaches suffer from lack of interpretability in critical safety applications. To address the dual challenges of prediction accuracy and model interpretability, a multi-agent reinforced symbolic regression (MA-RSR) framework is proposed by integrating multi-agent reinforcement learning with symbolic regression (SR) techniques. Specifically, MA-RSR employs a collaborative mechanism that decomposes complex mathematical expressions into parallel components constructed by independent agents, effectively addressing the search space explosion problem in traditional SR. The system incorporates Transformer-based architecture to enhance symbolic selection capabilities, while an intelligent masking mechanism ensures mathematical rationality through multi-level constraints. To demonstrate effectiveness of the proposed method, validation is conducted using SAE4340 steel multiaxial fatigue data and landing gear finite element simulation. The MA-RSR framework successfully discovers two mathematical expressions achieving R² of 0.96. Compared to traditional empirical formulas, MA-RSR achieves prediction accuracy improvements exceeding 50% while providing complete interpretability that machine learning methods lack. Furthermore, the multi-agent collaborative mechanism significantly enhances search efficiency through parallel expression construction compared to existing symbolic regression approaches. Full article

Shape memory polymer composite (SMPC) hinges have been researched as deployable structures in space missions due to their stable and controllable shape recovery behaviors. The elastic energy of the fabrics plays a dominant role in predicting the recovered shape of the hinges, as it strongly drives shape restoration. In this research, the shape recovery behaviors of SMPC hinges are numerically investigated by applying an equation that accounts for the hysteresis characteristics of the fabric reinforcement. The constitutive equation integrates the Mooney–Rivlin model, a viscoelastic, stored energy model, to characterize the hyperelastic properties varying with time, temperature, and shape recovery behaviors of the SMP matrix. Additionally, polynomial functions are introduced to represent the hysteresis effects and energy dissipation behavior of the fabrics. Since the elasticity of fabrics significantly affects the shape recovery of SMPCs, the developed constitutive equation enables accurate prediction of the recovered configuration. Finite element method analysis is performed based on this model and validated through comparison with experimental results. Finally, the constitutive equation is applied to investigate the shape memory response of SMPC hinges. The simulations present the significant design factors to increase the shape recovery ratio of the SMPC hinges. Full article

The cislunar space navigation satellite system is essential infrastructure for lunar exploration in the next phase. It relies on high-precision orbit determination to provide the reference of time and space. This paper focuses on constructing a navigation constellation using special orbital locations such as Earth–Moon libration points and distant retrograde orbits (DRO), and it discusses the simplification of planetary perturbation models for their autonomous orbit determination on board. The gravitational perturbations exerted by major solar system bodies on spacecraft are first analyzed. The minimum perturbation required to maintain a precision of 10 m during a 30-day orbit extrapolation is calculated, followed by a simulation analysis. The results indicate that considering only gravitational perturbations from the Moon, Sun, Venus, Saturn, and Jupiter is sufficient to maintain orbital prediction accuracy within 10 m over 30 days. Based on these findings, a method for simplifying the ephemeris is proposed, which employs Hermite interpolation for the positions of the Sun and Moon at fixed time intervals, replacing the traditional Chebyshev polynomial fitting used in the JPL DE ephemeris. Several simplified schemes with varying time intervals and orders are designed. The simulation results of the inter-satellite links show that, with a 6-day orbit arc length, a 1-day lunar interpolation interval, and a 5-day solar interpolation interval, the accuracy loss for cislunar space navigation satellites remains within the meter level, while memory usage is reduced by approximately 60%. Full article

In order to improve mathematical model accuracy of electromechanical actuator (EMA) and solve the problems of low-frequency response and large overshoot for nonlinear systems by using traditional proportional integral derivative (PID) algorithm, a fuzzy single neuron (FSN)-PID algorithm is proposed. Firstly, a complete multi-nonlinear dynamic model of EMA is constructed, which introduces internal friction and current limiter of brushless direct current motors (BLDCMs), dead zone backlash of gear trains, and LuGre friction between output shaft and fin. Secondly, a FSN-PID controller is introduced into the automatic position regulator (APR) of EMA control system, where the gain coefficient K of SN algorithm is adjusted by fuzzy control, and the stability of the controller is proved. In addition, simulations are conducted on the response effect of different fin positions under different algorithms for the analysis of the 6° fin position response; it can be concluded that the rise time with FSN-PID algorithm can be reduced by about 4.561% compared to PID, about 1.954% compared to fuzzy (F)-PID, about 0.875% compared to single neuron (SN)-PID, and about 0.380% compared to back propagation (BP)-PID. For the 4°-2 Hz sine position tracking analysis, it can be concluded that the minimum phase error of FSN-PID algorithm is about 0.4705 ms, which is about 74.44% smaller than PID, about 73.43% smaller than F-PID, about 17.24% smaller than SN-PID, and about 10.81% smaller than BP-PID. Finally, wind tunnel experiments investigate the actual high dynamic flight environment and verify the excellent position tracking ability of FSN-PID algorithm. Full article

Flying cars are an important vehicle for future urban air mobility. Mainstream flying cars predominantly adopt the e-VTOL-like configuration. Unlike traditional aircraft, these flying cars must be operated by a single pilot. The corresponding hybrid ground-flight control scheme remains immature, with only a few reliability analyses focused on flight safety. Based on the single-pilot operation (SPO) concept, this paper designs a hybrid control scheme for e-VTOL-like flying cars and proposes a restricted driving mode for the the take-off and landing stages and an autonomous driving mode for the cruising stage, respectively. Taking the landing phase as an example, a fault mode analysis and fault tree analysis are conducted for the restricted driving mode, focusing on factors that are sensitive to flight safety. A fault probability analysis is performed of the landing control unit in the restricted driving mode. The calculated probability of the top event occurring is 1.98 × 10⁻⁸ per flight, which proves the feasibility of the design meets the safety requirements. This study provides a foundation for a safety assessment of driving modes in future designs of flying cars. Full article

To improve the optical concentrator ratio of space solar power stations (SSPSs), this paper proposes a deployable segmented solar concentrator (DSSC) based on an afocal reflective system. First, a novel concept of an afocal reflective concentrator composed of segmented primary and secondary mirrors is introduced, and the deployable mechanism for the segmented primary mirror is described in detail. Subsequently, a model for the comprehensive error of the deployable mechanism with 3D revolute joint clearances and link length errors is established based on the “massless link” equivalent model of the clearance in revolute joints and the homogeneous transfer matrix. Sensitivity analysis evaluates the impact of various geometric errors of the deployable mechanism on the comprehensive error. Finally, a prototype experimental system is built to verify the concentration ratio of the concentrator and the pose error of the deployable mechanism. The experimental results show that the DSSC geometric concentration ratio reaches 5.36 to 6, and the optical concentration ratio reaches 24.7 to 32.2. The repeatability of the deployable mechanism is ±50 µm and ±1.2′, meeting the tolerance requirements of the optical system. The proposed afocal reflective DSSC can be used for solar energy concentration, improving the utilization of solar energy. Full article

Very low Earth orbit (VLEO) satellites are confronted with the challenge of orbital decay caused by thin atmospheres, and the volume and power limitations of micro satellites further restrict the application of traditional electric propulsion systems. In response to the above requirements, this study proposes an innovative scheme of radio frequency plasma micro-thrusters based on magnetic nozzle acceleration technology. By optimizing the magnetic nozzle configuration through the system, the plasma confinement efficiency was significantly enhanced. Combined with the mixed working medium (5 sccm Xe + 10 sccm air), the thrust reached 1.7 mN at a power of 130 W. Experiments show that the configuration of the magnetic nozzle directly affects the plasma beam morphology and ionization efficiency, and a multi-magnet layout can form a stable trumpet-shaped plume. The air in the mixed working medium has a linear relationship with the thrust gain (60 μN/sccm), but xenon gas is required as a “seed” to maintain the discharge stability. The optimized magnetic nozzle enables the thruster to achieve both high thrust density (13.1 μN/W) and working medium adaptability at a power level of hundreds of watts. This research provides a low-cost and miniaturized propulsion solution for very low Earth orbit satellites. Its magnetic nozzle-hybrid propellant collaborative mechanism holds significant engineering significance for the development of air-aspirating electric propulsion technology. Full article

Based on a pre-constructed simplified chemical reaction mechanism for afterburning in exhaust plumes, this study integrates a gas–solid two-phase combustion flow model with numerical radiative transfer calculations to systematically explore the optimization of computational domains for exhaust plume simulations and reveal the regulatory mechanisms of flight parameters affecting on plume evolution. The results demonstrate that as altitude increases, the plume expands overall, the afterburning zone shifts rearward, and the peak radiation brightness is delayed but with a slight enhancement. Conversely, increasing flight velocity leads to axial elongation and radial compression of the plume, reduced afterburning intensity, and an overall decrease in radiative intensity. This study establishes a correlation between solid rocket motor flight parameters and plume dynamics, providing theoretical and practical guidance for suppressing infrared signature signals in solid rocket motors and designing multifunctional propellant formulations. Full article

The tethered space net robot offers an effective solution for active space debris removal due to its large capture envelope. However, most existing studies overlook the evasive behavior of non-cooperative targets. To address this, we model an orbital pursuit–evasion game involving a tethered net and propose a game theory-based leader–follower tracking control strategy. In this framework, a virtual leader—defined as the geometric center of four followers—engages in a zero-sum game with the evader. An adaptive dynamic programming method is employed to handle input saturation and compute the Nash Equilibrium strategy. In the follower formation tracking phase, a synchronous distributed model predictive control approach is proposed to update all followers’ control simultaneously, ensuring accurate tracking while meeting safety constraints. The feasibility and stability of the proposed method are theoretically analyzed. Additionally, a body-fixed reference frame is introduced to reduce the capture angle. Simulation results show that the proposed strategy successfully captures the target and outperforms existing methods in both formation keeping and control efficiency. Full article

This paper proposes a novel Guidance and Control architecture for close-range rendezvous and final approach of a chaser spacecraft towards a non-cooperative and tumbling space target. In both phases, reference trajectory generation relies on a Sequential Convex Programming algorithm which iteratively solves a non-linear optimization problem accounting for propellant consumption, relative dynamics, collision avoidance and navigation sensor pointing constraints. At close range, trajectory tracking is entrusted to a translational H-infinity controller, coupled with a quaternion-feed-back regulator for target pointing. In the final approach phase, an attitude-pointing strategy is adopted, requiring a six degree-of-freedom H-infinity controller to follow a reference roto-translational trajectory generated to ensure target-chaser motion synchronization. Performance is evaluated in a high-fidelity simulation environment that includes environmental perturbations, navigation errors, and actuator (i.e., cold gas thrusters and reaction wheels) modelling. In particular, the latter aspects are also addressed by integrating the proposed solution within a complete Guidance, Navigation and Control pipeline including a state-of-the-art LIDAR-based relative navigation filter and a dispatching function for the distribution of commanded control actions to the actuation system. A statistical analysis on 1000 simulations shows the robustness of the proposed approach, achieving centimeter-level position accuracy and sub-degree attitude accuracy near the docking/berthing point. Full article

Vertiports, as dedicated facilities for electric vertical takeoff and landing (eVTOL) aircraft, are essential to ensure the efficiency and sustainability of Urban Air Mobility (UAM). However, UAM infrastructure site selection has become increasingly complex due to limited land availability, complex spatial conditions, and the need to balance multiple objectives. Focusing on passenger-carrying UAM operations, this study proposes a systematic framework for vertiport site selection. First, key factors are classified into high, medium, and low levels across the safety, economic, and social dimensions, forming a modular evaluation system. A GIS-based spatial screening process is developed to identify potential vertiport locations. Subsequently, a variable representing the level of demand satisfaction is incorporated into a progressive coverage model specifically designed for vertiport site optimization. A hybrid algorithm is designed to solve the model. Using Shenzhen as a case study, the proposed approach is validated through real-world data. The results show that vertiport size and spatial requirements significantly influence the selection of suitable land types. High economic constraints may cause facility over-concentration, while setting standards aligned with regional functions better supports equitable access. Locating vertiports in high-demand areas enhances demand satisfaction levels, and both service capacity and range strongly influence overall system performance. These findings provide practical insights for future vertiport planning, promoting the efficient use of urban resources and supporting the successful implementation and sustainability of UAM. Full article

Since 2019, Starlink satellites, with their innovative flat-panel design and unprecedented number in orbit, have transformed the traditional satellite industry. Due to their mass production characteristics, flat-panel satellites face a pressing need for satellite layout optimization design (SLOD), particularly for feasible optimization results applicable in engineering. Existing layout optimization algorithms often focus on theoretical optima, computational efficiency, and multi-objective capabilities. Most algorithms are validated exclusively through numerical or CAD-based simulations, leaving their engineering applicability under-reported. This paper establishes a simplified mathematical model of SLOD with consideration for the key features of flat-panel satellites. Furthermore, we propose a differential evolution algorithm that leverages local optima for the layout optimization design of flat-panel satellites. By making targeted and limited improvements to initial human-designed layouts, the algorithm generates practical engineering solutions that significantly enhance the stacking efficiency, mass properties, and thermal distribution of flat-panel satellites. Finally, the effectiveness and engineering feasibility of the algorithm were verified through the design of Longjiang-3, China’s first flat-panel satellite, and the results were also validated in orbit. Compared with the baseline configuration, the optimized layout reduces the principal moment of inertia by 6.6% and the satellite module height by 3.5%. It also achieves a significant improvement in thermal power uniformity across the structure. Overall, the key layout metrics are enhanced by 26%. The present research results provide a theoretical basis and engineering solutions for the SLOD of flat-panel satellites. Full article

Based on the analysis of solar array current data from a certain MEO-orbiting satellite, this paper reveals its short-period fluctuation characteristics and underlying mechanisms. The study finds that when solar panels face the sun during the light period, the output current exhibits significant short-period fluctuations in addition to being influenced by long-period factors such as sun–earth distance, incident light intensity changes, and space irradiation attenuation. Through theoretical analysis, we first confirm that the root cause of these short-period variations is the temperature change in the shunt circuit caused by load fluctuations, which in turn affects the output current characteristics. Unlike traditional methods that use static characteristic factors such as incident angles, this paper innovatively proposes using load current as a key characteristic factor. For asymmetric solar panel fault scenarios, load current, time phase, and fault-wing output current are used as characteristic factors to adaptively predict the current of normal wings. Meanwhile, feedforward neural network (FNN), Recurrent Neural Network (RNN), and long short-term memory (LSTM) are used for output current prediction. The experimental results show that these methods can accurately capture the short-period fluctuations caused by load mutations and adapt to the fluctuation trend of the normal wing during the prediction of current changes in the faulty wing. It is worth noting that, limited by the short-period fluctuation prediction scenario, the inherent advantage of LSTM in long-sequence prediction is not fully reflected. Full article

Numerical simulations were performed using the RANS (Reynolds-averaged Navier–Stokes) approach to analyze the flow field around an aircraft during the landing rollout phase with thrust reversers deployed. The objective was to characterize the flow structure modifications induced by the reversed jet flow and to assess its impact on the aerodynamic performance of various control surfaces. The results demonstrate that the reverse jet flow introduces significant disturbances to the flow field, substantially altering the aerodynamic load distribution over the airframe and causing a marked reduction in overall lift. High-lift devices are particularly susceptible to these effects: the pressure distributions on both the leading-edge slats and trailing-edge flaps are severely disrupted, resulting in a notable degradation of their lift augmentation capabilities. The rudder retains a generally linear response characteristic, though a slight reduction in effectiveness is observed. In contrast, the elevator exhibits a pronounced asymmetry in control effectiveness, with significantly greater degradation under positive deflection compared to negative deflection. This study elucidates the complex interference mechanisms associated with thrust reverser-induced flows and provides valuable insights for the optimization of thrust reverser system design and the enhancement of flight control strategies during the landing phase. It further delivers the first quantitative evaluation of elevator response asymmetry and accompanying lift degradation caused by reverse jet plumes, supplying design-ready metrics for reverser integration. Full article

Accurate state estimation for quadrotors under wind-induced disturbances remains a critical challenge in dynamic outdoor environments. Existing model-based and data-driven approaches often struggle with real-time adaptation and catastrophic forgetting when faced with continuous wind disturbances. This paper proposes an online continual physics-informed learning framework that integrates physics-informed neural networks with continual backpropagation to address these limitations. The physics-informed neural networks architecture embeds quadrotor dynamics into the neural network training process, ensuring physical consistency, while continual backpropagation enables continual learning from real-time streaming data without compromising previously acquired knowledge. Experimental validation on a simulation platform demonstrates the accuracy and robustness of the framework in ideal and wind-disturbed scenarios. Full article