Electric propulsion (EP) systems usually have multiple independent adjustable parameters, such as discharge voltage and operating current which strongly influence thruster performance, plume morphology, and plasma stability. For magnetically enhanced hollow cathode thrusters (MHCT), plume distortion and deflection often occur under multi-parameter coupling, potentially affecting plume symmetry and thrust-vector stability. Therefore, rapid steady-state plume diagnosis under different operating conditions and reliable parameter-selection strategies are needed. In this work, a physically constrained three-dimensional plume reconstruction method is proposed based on multispectral imaging and a distribution surrogate model. A parametric plume distribution is constructed using prior physical information, and the electron temperature and electron density fields are reconstructed through residual optimization coupled with a xenon collisional-radiative model and line-of-sight projection. The reconstructed plume-core morphology shows good agreement with the multispectral observations and probe-based validation data. Using this method, the projected plume eccentricity and divergence characteristics are analyzed under different voltage and keeper-current conditions. Based on the reconstructed spatial evolution, a plume-symmetry regulation map is established to identify operating conditions with reduced plume-core displacement and acceptable divergence. The proposed method provides a non-intrusive diagnostic and parameter-selection approach for evaluating steady-state plume asymmetry in compact electric propulsion systems.

To address the challenges of degraded estimation accuracy, tracking delays, and filter divergence in traditional air data reconstruction algorithms for aircraft operating in complex wind fields and performing high-maneuverability maneuvers—mainly caused by model uncertainties and time-varying noise—this paper proposes an adaptive air data reconstruction method based on coarse-to-fine consistency detection. First, a parallel coarse-to-fine dual-channel processing architecture, grounded in a flight dynamics model, is established. In the coarse estimation channel, nonlinear least squares (NLS) optimization combined with sliding-window preprocessing is employed to obtain wind speed references without significant phase lag. In the fine estimation channel, a modified Sage-Husa extended Kalman filter (MSH-EKF) is developed, incorporating wind speed as a state variable. Second, an innovative coarse-to-fine consistency detection mechanism is introduced, which dynamically generates a filter divergence criterion threshold based on the deviation between coarse and fine estimates. When a sudden disturbance is detected, the algorithm adaptively triggers state prediction covariance inflation and noise-bounded update, thereby mitigating the covariance mismatch caused by abnormal innovations. Finally, simulation validation is conducted using a high-fidelity nonlinear F-16 aircraft model under superimposed composite wind fields and alternating maneuver conditions. The results indicate that, compared with the traditional Sage-Husa EKF algorithm, the proposed method reduces the root mean square error (RMSE) of the estimated true airspeed, angle of attack, and angle of sideslip by 74.02%, 39.53%, and 28.12%, respectively. The method effectively resolves the trade-off between fast tracking, noise suppression, and robustness to strong disturbances, providing high-quality air data inputs for highly reliable autonomous navigation and control of aircraft.Further frequency-band-separated error analysis shows that the CF-AEKF suppresses estimation errors of true airspeed and angle of attack across low, medium, and high frequency bands, and significantly reduces high-frequency errors in sideslip angle, verifying the frequency robustness of the proposed method against multi-scale disturbances in composite wind fields.

Martian quadrotors require enlarged rotor disks to generate lift in the rarefied atmosphere, which can lead to increased rotational inertia and limited control-moment margin. Variable-pitch rotors provide a promising means of expanding control authority, but their assessment requires aerodynamic models that remain usable under post-stall, zero-thrust-crossing, and reverse-thrust conditions. This paper presents a robust modeling framework based on blade element momentum theory that combines a full-angle airfoil database generated using computational fluid dynamics, calibrated sectional correction factors, a signed momentum formulation, and a residual-based inflow solver. The model was evaluated using low-pressure chamber measurements obtained in room-temperature air at 720±25Pa. Across the tested pitch range of -30° to 30°, the proposed solver returned finite thrust and torque predictions for all operating points, whereas the linearized fixed-point blade element momentum theory baseline did not converge at the negative-pitch points. On the common converged points of the baseline, the proposed method reduced thrust root-mean-square error by 74.5%–81.4%. A Monte Carlo attainable-moment analysis further showed that, for the representative vehicle and sampling ranges considered, the constant-rotor-speed variable-pitch case increased the estimated convex-hull volume of the control-moment envelope by a factor of 24.46 relative to the fixed-pitch 20° baseline. These results indicate that the proposed aerodynamic framework can support full-range rotor-load prediction and quantitative control-authority assessment for Martian variable-pitch multirotors.

Optical emission spectroscopy (OES), as a highly sensitive real-time monitoring method, has been widely applied in swift lifetime evaluation of Hall thrusters. However, as the erosion rate of ultra-long-lifetime magnetically shielded Hall thrusters reduced by an order of magnitude, traditional OES becomes insufficient for real-time monitoring. To address this bottleneck, this study proposes a high-sensitivity monitoring strategy utilizing image spectra rather than traditional line spectra. By distinguishing the 2D Gaussian morphology of signal peaks from noise point clouds, a specialized high-dimensional filtering algorithm was developed to extract weak signals from complex backgrounds. The system achieved a 4.9-fold improvement in detection lower limit compared to conventional methods, enabling the reliable extraction of sub-ppm erosion signals. Beyond satisfying the rigorous monitoring requirements of magnetically shielded Hall thrusters, this method demonstrates significant potential for analyzing trace contaminants in general vacuum systems. Furthermore, a multi-spatial-position synchronous spectral measurement technique was developed to characterize the spatial distribution of erosion products, providing experimental validation for erosion transport theory models. This work establishes a robust monitoring system for magnetically shielded Hall thrusters’ erosion characterization, addressing the critical lack of rapid optimization and efficient evaluation methods in the long-life design of next-generation Hall thrusters.

A numerical investigation of a vortex ring impinging asymmetrically on a finite-width flexible plate at Re=500, 1500, 2500 is conducted. Results reveal that 3D vortex dynamics significantly influence the plate’s energy harvesting efficiency. At Re=500, high viscosity inhibits the secondary vortices formation at the plate edges/upper wall and enhances primary vortex ring (PVR) stability, resulting in a smooth load decrease. In contrast, Re=1500 and 2500 generate substantial secondary vortices. Under the PVR’s induction, these secondary vortices lift and entangle in PVR, inducing high compression and torsional of PVR vortex tube, which leads to its energy dissipation. Notably, at Re=2500, high turbulence instability promotes stronger secondary vortices, resulting in significant impact energy loss of PVR. Concurrently, these vortices coupling also enhances PVR deformation and vortex shedding, impeding energy transfer to the plate. This interaction results in a smaller increment in energy harvesting efficiency from Re=1500 to Re=2500. Our analysis reveals that the flexible plate’s harvesting efficiencies don’t increase monotonically with the Reynolds number. Instead, the energy harvesting efficiency tends to saturate around Re=1500. This phenomenon is governed by the interplay of 3D vortex evolution, coupling effects, viscous dissipation, and turbulent diffusion, with potential implications for ocean vortex energy harvesting devices optimizations.

The hydroforming performance of trailing arms is governed by the coupled effects of feed parameters, pressure schedules and frictional characteristics. Improper parameter matching readily induces typical forming defects such as wrinkling, cracking and uneven wall thickness. To address this issue, a multi-objective optimization method for hydroforming is proposed in this study. Taking the maximum wall thickness, minimum wall thickness and die-to-workpiece gap of the tubular blank as optimization objectives, and the internal pressure and right-side axial feed velocity as design variables, an integrated numerical simulation framework combining the Archive-based Micro Genetic Algorithm (AMGA) and LS-DYNA is established to analyze the hydroforming process. By adaptively adjusting the key control points of internal pressure and axial feed loading curves, the developed method expands the solution space and realizes the automatic optimization of loading paths. The results reveal that the maximum wall thinning rate of the tubular component drops from 20.4% to 14.8%. Meanwhile, the wall thickness uniformity is improved and forming defects are effectively suppressed while the thickening rate remains stable. Furthermore, a complete round of optimization calculation involving thousands of finite element solutions can yield a complete set of Pareto non-dominated solutions. In this paper, the AMGA multi-objective optimization algorithm is adopted to acquire the optimal loading paths, and physical prototype experiments are carried out relying on self-developed 2000 T hydroforming equipment. Comparisons between measured and simulated wall thickness values of the tubular component show that the maximum relative error is controlled within 7.46%, which verifies the reliable engineering applicability of the proposed optimization scheme and provides new insight into the process optimization for forming similar structural components.

Abstract An electromagnetic-driven separation ejection mechanism for on-orbit replacement units is studied. This mechanism features versatility and rapid adjustability of ejection force, enabling adaptation to different working conditions with distinct advantages. Experimental tests confirm the deployed satellite’s average separation velocity of 0.121 m / s, relative separation velocity of 0.16 m / s, peak angular velocity ≤ 1° / s, excellent repeatability, and 3.73% relative standard deviation.

Hypersonic reentry trajectory optimization must satisfy stringent terminal conditions and path constraints involving heat flux, dynamic pressure, load factor, and no-fly-zone (NFZ) avoidance under strongly nonlinear dynamics. This paper proposes SHARP-SCP (Shape-constrained Hierarchical Arc-length Reformulated Projection), a Bezier-based sequential convex programming framework that uses arc length as the independent variable and parameterizes states and controls with piecewise control points. The Bezier convex-hull property transfers linear state/control bounds from dense collocation nodes to sparse control points, ensuring continuous segment-wise satisfaction and reducing inter-node leakage. In the arc-length/log-velocity domain, the limits on heat flux and dynamic pressure are exactly reconstructed as linear inequalities under an exponential-atmosphere model, while only the aerodynamic term in the load factor constraint requires sequential approximation. Arc-length Gauss collocation induces velocity-adaptive time spacing, concentrating nodes in high-speed segments without mesh refinement. With virtual control, projection updates, and hierarchical refinement, SHARP-SCP converges from simple initial guesses and reduces total constraints by 42.9% relative to pointwise enforcement. Compared with hp-ARSCP and hp-ARPM on maximum-terminal-velocity and minimum-total-heat-load tasks, it achieves near-benchmark terminal performance, consistent NFZ avoidance, smoother controls, and runtimes below 47.9% of those of hp-ARSCP and below 3.04% of those of hp-ARPM. Local nonlinear integration confirms dynamic feasibility. A 200-case Monte Carlo study with initial-state, aerodynamic, and density perturbations demonstrates robustness under hard terminal-time and terminal-speed constraints.

Plasma-assisted combustion has proven to be an effective approach to improve the poor combustion characteristics and NO emissions of ammonia, and a detailed investigation of its combustion process and underlying mechanisms can facilitate the industrial application of ammonia combustion in the energy sector. In this study, a zero-dimensional model for gliding arc plasmaassisted ammonia combustion was developed by integrating relevant reaction mechanisms and coupling two open-source software packages, ZDPlasKin and Cantera. Numerical results regarding gas temperature and species concentrations indicate that plasma generates a substantial amount of active radicals, promotes multiple reaction pathways, and enhances combustion completeness, particularly under high equivalence ratio conditions. Furthermore, an optimal discharge configuration exists that achieves a balance between combustion performance and NO reduction. The zero-dimensional model established in this work is capable of effectively capturing the chemical effects of excited species, which provides a valuable basis for the development of optical diagnostic and predictive systems-a direction that will be the focus of our future research.

Challenges in trajectory planning are encountered by fixed-wing unmanned aerial vehicle (UAV) swarms operating in environments with unknown obstacles. In this study, a distributed real-time trajectory-planning method that integrates a distributed model predictive control (DMPC) framework with an adaptive Gaussian collocation strategy (DA-GCMPC) was developed. This method leverages a distributed iterative computational framework based on DMPC to reformulate trajectory planning as an optimal control problem. To address the fixed-resolution limitation of conventional distributed MPC formulations, a complexity-aware adaptive collocation mechanism is introduced. The novelty of the method lies in adapting the collocation transcription resolution of each local MPC problem according to the instantaneous planning complexity. This mechanism selects the collocation type online according to maneuvering demand, obstacle density risk, and neighboring-UAV interaction risk, enabling the planner to balance real-time computation and constraint-handling capability under limited perception. We decomposed the UAV energy consumption and formulated the total energy consumption of the swarm as the objective function. An optimal control sequence was derived using the Gaussian collocation method by integrating obstacle avoidance constraints for fixed-wing UAVs and environmental limitations. Comparative simulations against the implemented fixed-discretization interior-point and SQP baselines showed that the proposed DA-GCMPC method achieved lower computation time and better trajectory quality metrics under the tested simulation settings, with average per-step computation times below 80 ms. In addition, an eight-UAV semi-physical hardware-in-the-loop validation was conducted to verify the real-time executability of the proposed method in a closed-loop flight control system.

Mars exploration imposes a fundamental design contradiction on rotorcraft: generating sufficient lift in the rarefied atmosphere requires significantly enlarged rotors, whereas strict launch mass constraints and the need to maximize payload capacity demand an extremely lightweight structural design. This conflict forces the adoption of long, slender rotor arms, which introduce significant structural flexibility and inherently destabilize conventional rigid-body control systems. To address this, this study presents a Motion Decomposition PID (MD-PID) control strategy. The method utilizes real-time coupling force estimation to decompose measured motion into rigid-body and flexible components, applying feedback control acting exclusively on the virtual rigid-body states to decouple the control loop from structural vibrations. Simulation results demonstrate substantial improvements: positional drift during hovering is reduced by 97.9%, and tracking accuracy during vertical ascent improves by 99.3%. Notably, the MD-PID controller enables the stable execution of complex maneuvers that induce divergence in traditional PID schemes. This approach ensures robust stability for Mars missions while maintaining computational simplicity.

To further explore the intrinsic correlation mechanism between the channel wall erosion of Hall thrusters and low-frequency oscillations, this study innovatively employs a convolution algorithm to process the time-domain signals of anode current and cathode current through convolution operations, and systematically analyzes the time-frequency domain characteristics of the current convolution signals. Under the experimental condition of keeping the cathode propellant flow rate constant, by adjusting key operating parameters such as anode voltage, anode flow rate, and excitation current, the focus is placed on studying the relationship between the low-frequency characteristics of the current convolution signals and the erosion product signals (B I relative light intensity). According to the experimental results, the signal after current convolution processing contains two different main frequencies with a frequency of 100 kHz as the boundary. Based on the proportion of these two different main frequencies, they are defined into three modes, namely Bell of Convolution (BOC), Transition of Convolution (TOC), and Jet of Convolution (JOC). Among them, in the BOC mode, the signal has significant "envelope waveform" structure. When the thruster operates at a discharge voltage of 210 V and a volumetric flow rate 8sccm, with adjustments to the excitation current, it is found that the B I light intensity of erosion products in the JOC mode is lower than that in the BOC mode and TOC mode. Moreover, the B I light intensity shows a high correlation with characteristic parameters such as the occurrence frequency of the "envelope waveform" structure in the BOC mode, and its dynamic evolution behavior presents obvious regular variation characteristics under different combinations of operating conditions. (c) 2026 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The rarefied Martian atmosphere imposes a fundamental design contradiction for quadrotor UAVs: to generate sufficient lift, the vehicle requires large-span rotors and extended supporting structures, yet strict launch mass limits and the critical objective to maximize payload capacity demand extreme structural lightweighting. This conflict inevitably leads to high-aspect-ratio rotor arms capable of significant elastic deformation, rendering the traditional rigid-body assumption employed in quadrotor control invalid. To address this, we develop a rigid-flexible coupled dynamic model using the Floating Frame of Reference (FFR) formulation and Lagrangian mechanics, treating the rotor arms as continuous Euler-Bernoulli beams. Unlike simplified lumped-parameter approaches, the present formulation preserves the distributed structural representation of the flexible arms and captures their coupling with the central rigid body. Numerical simulations show that a benchmark rigid-body controller may become unstable for the present compliant baseline configuration under Martian-relevant conditions, driving the system to instability even during near-hover maneuvers. We identify the failure mechanism as a control-structure positive feedback loop, where control inputs inadvertently excite structural modes via parasitic force injection. Furthermore, modal analysis indicates that, for the present baseline rotor-arm configuration, the low-frequency response is dominated by fundamental bending modes, while torsional modes do not appear within the retained frequency range of interest. These findings indicate that structural flexibility should be treated as an important design consideration for Mars rotorcraft and suggest that structurally aware control architectures may be necessary when compliance becomes non-negligible.

Martian variable-pitch quadrotors face coupled challenges from large rotor inertia, low atmospheric density, and nonlinear rotor aerodynamics. This paper proposes a Riemannian Manifold-based Control Allocation (RMCA) framework for allocating the commanded wrench in the combined rotor-speed and collective-pitch input space. The main contributions are threefold: a unified metric tensor is constructed to incorporate actuator bandwidth disparity and saturation constraints into the allocation process; a Robust BEMT aerodynamic operator is embedded to provide a full-envelope nonlinear mapping for high-collective and reverse-thrust regimes; and a null-space optimization mechanism is introduced to exploit actuator redundancy for task-dependent reconfiguration. Comparative simulations show that the proposed VP-VS RMCA method improves hovering allocation accuracy and reduces aerodynamic power relative to the baseline methods. In forward flight, the proposed method remains stable in the tested maneuver, while the two baseline allocation strategies lose stability. These results indicate that the proposed allocation framework can improve the utilization of variable-speed and variable-pitch actuation for Martian quadrotor control.

The unique pappus structure of dandelion seeds induces a leeward separated vortex ring, significantly enhancing aerodynamic performance for long-distance flight. However, the vortex evolution dynamics and their impact on stability during transient takeoff remain unclear. Fluid-structure interaction simulations were conducted to investigate the pappus takeoff at wind speeds of 0.5-3 m/s. Results demonstrate that the active motion of the pappus fundamentally alters the wake topology compared to fixed models, promoting a stable, radially expanding separated vortex ring. Mechanism analysis reveals stability arises from a dynamic relay initiating with unsteady inertial forces (significantly augmented by added mass effect) and rapidly evolving into wall-induced stretching or viscous dissipation. Whether governed by the coupling of inertial stretching and added mass (high Reynolds numbers) or viscous diffusion (low Reynolds numbers), these mechanisms consistently drive a generalized radial expansion of the wake. This expansion smooths transverse velocity gradients and maintains the steady evolution of the leeward low-pressure zone, ensuring progressive stabilization. Based on these findings, a transient stability criterion centered on an equivalent characteristic velocity is established, quantitatively identifying the critical transition from the unstable to the stable regime. This study offers mechanistic insights for the bio-inspired stable design of passive micro-aircraft and underwater vehicles.

In recent years, the rapid development of commercial satellite projects, such as low-Earth orbit (LEO) communication and remote sensing constellations, has driven the satellite industry toward low-cost, rapid development, and large-scale deployment. Commercial off-the-shelf (COTS) components have been widely adopted across various commercial satellite platforms due to their advantages of low cost, high performance, and plug-and-play availability. However, the space environment is complex and hostile. COTS components were not originally designed for such conditions, and they often lack systematically flight-verified protective frameworks, making their reliability issues a core bottleneck limiting their extensive application in critical missions. This paper focuses on COTS solid-state drives (SSDs) onboard the Jilin-1 KF satellite and presents a full-lifecycle reliability practice covering component selection, system design, on-orbit operation, and failure feedback. The core contribution lies in proposing a full-lifecycle methodology that integrates proactive design-including multi-module redundancy architecture and targeted environmental stress screening-with on-orbit data monitoring and failure cause analysis. Through fault tree analysis, on-orbit data mining, and statistical analysis, it was found that SSD failures show a significant correlation with high-energy particle radiation in the South Atlantic Anomaly region. Building on this key spatial correlation, the on-orbit failure mode was successfully reproduced via proton irradiation experiments, confirming the mechanism of radiation-induced SSD damage and providing a basis for subsequent model development and management decisions. The study demonstrates that although individual COTS SSDs exhibit a certain failure rate, reasonable design, protection, and testing can enhance the on-orbit survivability of storage systems using COTS components. More broadly, by providing a validated closed-loop paradigm-encompassing design, flight verification and feedback, and iterative improvement-we enable the reliable use of COTS components in future cost-sensitive, high-performance satellite missions, adopting system-level solutions to balance cost and reliability without being confined to expensive radiation-hardened products.

High-Altitude wind is a critical factor affecting the recovery safety of reusable rockets, significantly altering aerodynamic loads, flight attitudes, and trajectories-especially during the aerodynamic deceleration phase (engine shutdown) of reentry, posing severe challenges to high-precision guidance and stable control. Currently, accurate advance prediction of landing site wind fields is difficult with poor real-time performance, necessitating a real-time estimation and prediction method independent of additional measurement equipment. This study addresses this gap by proposing a deep learning-based approach for wind field estimation and prediction, using directly measurable attitude angles and apparent acceleration deviations of the rocket as inputs to train a dedicated deep neural network. Furthermore, to solve the attitude control problem of Reusable Launch Vehicles (RLVs) during recovery, a non-recursive simplified high-order sliding mode control method with online wind disturbance compensation is designed to achieve finite-time convergence. First, a dynamic model for the attitude control of RLVs during recovery is established; second, based on homogeneity theory, a non-recursive simplified homogeneous high-order sliding mode controller is developed to realize finite-time tracking control during RLV recovery with uncertainties, effectively suppressing the chattering inherent in sliding mode control; finally, simulation results verify the effectiveness and engineering feasibility of the proposed method. The combined approach significantly reduces wind-induced disturbance torque and required control torque, enhancing the adaptability and control robustness of vertically recoverable rockets to wind fields.

Micro-cathode arc thrusters (mu -CAT) hold critical applications in the national economy, serving as primary propulsion systems for orbit maintenance and formation flying missions of small satellites. Compared to steadystate thrusters (e.g., Hall thrusters or ion thrusters), the performance and lifetime of the mu -CAT depend on the ablation state of the cathode. However, it is challenging to characterize ablation-driven plasma properties due to the lack of a method to determine the time-resolved metal ion densities from cathode ablation during single-pulse discharge. In this work, we present an OES method to determine the Ti+ and Ti2+ ion densities based on ionic lines from different ionization states, and observe the "three-stage evolution" of the plasma inside the electrode channel of the micro-cathode arc thruster with capacitive discharge mode based on the high-speed imaging subsystem. The time-resolved Ti+ and Ti2+ ion densities during the interelectrode plasma and the early stage of the anode spot period are determined by synchronously triggering the power processing unit of the mu -CAT and optical emission spectroscopy subsystem. Besides, the impulse bit during a single pulse is obtained, supported by the determined ion densities and time-of-flight ion velocity monitoring method. Our method will help improve the engineering test efficiency and accelerate the design and development of the mu -CAT.

In this study, a distributed cooperative control scheme utilizing a flywheel array is proposed to suppress vibration of flexible space structure. The theoretical dynamic model of a flexible beam is derived, incorporating the flywheel characteristics and revealing the coupling relationship between the flywheel rotational speeds and the vibration suppression performance. The proposed distributed cooperative control law introduces consensus terms among neighboring controllers, and the connection topology among the controllers is represented by the Laplacian matrix. Subsequently, the stability of the system is analyzed under the condition of collocated sensors and actuators. Both theoretical simulation and experimental validation are conducted across uncontrolled, decentralized, and distributed cooperative control schemes. The numerical simulations confirm the validity of the established model and facilitate the determination of appropriate control parameters. For physical experiments, an integrated control unit comprising a flywheel, an inertial measurement unit, and a microcontroller is designed to facilitate the implementation of the distributed cooperative control system. Both simulation and experimental results demonstrate that the proposed method improves vibration suppression performance and fault tolerance. In experiments, compared to decentralized control, the distributed cooperative control scheme improves the vibration attenuation within 5 s from 88% to 92%, reduces steady-state residual vibration by 25.9%, and maintains 95.7% control efficacy under single sensor failure for flexible space structures.