A data-driven approach for flutter boundary prediction is proposed, which adopts a deep learning model to extract flutter features from measured signals, thereby enabling the analysis of aeroelastic system stability. Following a modeling strategy that leverages structural acceleration response signals, a dataset is constructed from experimental data acquired from wind tunnel tests, and a multidimensional feature system and a set of comparative models are subsequently established for performance evaluation. Comparative analytical results reveal that the integration of power spectral density (PSD) with the Bayesian optimization Transformer-long short-term memory hybrid model can markedly enhance the efficacy of feature extraction and the accuracy of flutter boundary prediction. Experimental validation demonstrates that the proposed method achieves a mean prediction error of 3.73% for unseen working conditions of the wind tunnel model and 4.14% for data obtained from a single flight test sortie. Furthermore, a prediction error below 10% is achievable at approximately 70% of the critical flutter speed, which could contribute to enhanced early warning performance in flutter tests.

The flying-wing configuration offers inherent advantages in aerodynamic efficiency and stealth; however, conventional fixed-wing designs face fundamental performance trade-offs when tasked with multi-role missions. This paper introduces a multidisciplinary design optimization (MDO) framework for a morphing wing unmanned aerial vehicle (UAV) to overcome this limitation. The proposed UAV integrates four complementary morphing strategies—shear-type variable sweep, variable span, morphing wingtip, and a continuously variable camber trailing edge—to adapt its geometry for different flight phases. An automated parametric modeling platform is developed, enabling the dynamic generation of 3D CAD models driven by design variables. This geometry is coupled with a suite of analysis modules for aerodynamics, propulsion, weight estimation, flight performance, and radar cross-section. The multi-mission profile, including takeoff, climb, cruise, turning, and landing, is decomposed into several phase-specific single-objective optimization subproblems, which are solved using an elitist real-coded genetic algorithm. The results quantify the optimal morphing configurations for each phase, demonstrating significant performance gains over the baseline, such as a 17% increase in range. Critically, the study analyzes the trade-off between aerodynamic benefits and the weight penalty of morphing mechanisms, revealing that both range and maneuverability are the most sensitive to the added weight. The proposed framework uses mission-phase-specific optimum geometries to define the required morphing envelope, actuation ranges, and net performance benefit of a candidate morphing flying-wing UAV after considering mechanism-induced mass penalties. This framework provides a quantitative basis for mission-driven morphing decisions and establishes a viable approach for designing highly adaptive next-generation UAVs.

Eddy-current sensor-free control based on reusing Hall sensors of a bearingless slice motor system can reduce the volume, cost, weight, and the impact of shear on transmitted liquid. However, the algorithm will fail in the presence of the PM’s third harmonic. Hence, this article presents the eddy-current sensor-free control algorithm based on the two negative sequence coordinate transformation in parallel with different frequencies (TNSPDF). The random and disordered signal in the Hall output is modulated into asymmetrical component about the displacement vector angle through negative sequence coordinate transformation at different electrical frequencies, achieving decoupling between the displacement vector angle and the motor electrical frequency. The interference signal does not lead to any pulsation in the estimated displacement; rather, it evolves into a significant coefficient for the purpose of displacement identification. The validity and effectiveness of the proposed method are verified through experiments on a bearingless permanent magnet slice motor system.

To clarify how platform motion influences riser vortex-induced vibration (VIV) and to characterize the response under simultaneous boundary forcing and uniform current, tests were performed on a riser model exposed to both platform sway motion and uniform current in a wave-current flume. The effects of these factors were studied by changing the incoming current velocity, platform motion amplitude, and platform motion frequency at several levels. The results indicate that, under platform sway motion alone, the riser response appears at the same frequency as the platform motion. Under coupled action, at low Ur values, platform motion determines the dominant response frequency of the riser, while disruption of the first-order “lock-in” condition suppresses its VIV response. In this range, combining the independently evaluated contributions of platform motion and uniform current through linear superposition results in an overprediction of fatigue damage. At high Ur values, platform motion redistributes vibration energy along the span, enhances higher-order modal participation, and promotes the transition of vibration from standing waves to traveling waves. The linear superposition method results in an underestimation of fatigue damage in this range.

The bearingless slice motor employed in ventricular assist devices must deliver not only ultra-clean operation but also exceptionally low speed fluctuations to ensure precise flow control. While feed-forward compensation for cogging torque within the vector control framework can mitigate these fluctuations, the predictive accuracy of such strategies is limited by existing analytical models. These models, which are grounded in conventional magnetic field modulation theory, often neglect the critical modulation effect of stator saturation, leading to significant errors. To address this gap, this article introduces a novel analytical method for cogging torque based on a synchronous rotation saturation modulation (SRSM) factor. First, the modulation mechanism of the SRSM factor is analyzed. Second, the air gap permeance was reconstructed by introducing the SRSM factor, allowing for the complete and accurate determination of the harmonic pairs that generate cogging torque, thus achieving accurate analysis of cogging torque. Finally, experiments are conducted to verify the effectiveness and correctness of the proposed analytical method.

The integration of sensor networks within aircraft structures for large-area load localization enables accurate assessment of structural health and appropriate maintenance, which is of great significance for the safe upkeep of aircraft. The technology of structural electronics integration offers new concepts for the integration of sensor networks with structures. Inspired by this, this chapter presents the realization approach of integrating the sensor network and structure based on screen printing. The method has the advantages of large-area fabrication, batch fabrication, simple equipment, low cost, and good substrate and ink adaptability, which is conducive to the preparation of flexible sensor networks and their integration with structures. Based on this approach, the integrated design and preparation of the large-area load localization sensor network and structure were accomplished, and the load localization function was verified with a localization accuracy of 90

To improve optimization efficiency in the conceptual design of Blended Wing Body (BWB) Unmanned Aerial Vehicles (UAVs), an adaptive Kriging-based surrogate modeling framework is established. This framework addresses the high computational cost inherent in repeated numerical simulations in multidisciplinary analysis (MDA). First, a streamlined MDA model integrating geometry, mass, aerodynamics, and flight performance was developed. Subsequently, three optimization strategies, comprising a baseline non-adaptive Kriging model, an exploration-oriented strategy, and an exploitation-oriented strategy, were implemented and compared for the objective of maximizing flight range. To ensure robustness and mitigate stochastic bias, 15 independent randomized trials were conducted for each strategy. Statistical results demonstrate that the exploitation-oriented strategy delivers superior performance, with the median optimization result achieving a 14.5% range enhancement over the baseline design. Notably, for this representative optimal configuration, the discrepancy between the Kriging prediction and the numerical simulation is a mere 0.48%. Finally, a dual-method parameter sensitivity analysis identifies fuel mass as the most influential parameter, followed by the center wing span. The proposed framework provides an efficient and robust methodology for the global optimization of BWB UAVs.

To investigate the dynamic characteristics of wake interference and the collision evolution mechanisms of tandem cylinders with unequal diameters. A series of water-tank experiments were conducted to examine the effects of coupled diameter ratio and spacing ratio on the frequency characteristics, displacement responses, and acceleration responses of tandem cylinders. The results demonstrate that the responses of the upstream and downstream cylinders differ significantly from those of isolated cylinders. The dominant frequency and displacement amplitude of the downstream cylinder are strongly influenced by the upstream wake shear layers and vortex disturbances. Under different diameter ratios, the downstream cylinder exhibits two vibration modes: wake‐induced amplitude amplification and wake‐envelope‐restricted amplitude suppression. Critically, collision events are identified under small spacing (S/D= 3) and high Vr conditions, particularly for Dr = 0.5 and 2.0, where geometric asymmetry and enhanced relative motion reduce the effective clearance. A combined criterion based on relative net clearance and transient acceleration spikes is established to diagnose collision. The findings highlight that collision is a coupled two-parameter phenomenon governed by both spatial confinement and hydrodynamic excitation intensity, providing essential insights for the design and risk assessment of multi-cylinder offshore systems.

The research aims to propose a basic parameter estimation method for high-speed vertical take-off and landing (HSVTOL) aircraft, balancing rotor and fixed-wing mode requirements. Flight profiles and performance indicators are defined based on mission phases, and maximum take-off weight is estimated using the fuel fraction method. A pre-estimation model for a turboshaft–turbofan variable cycle engine (TSFVCE) was established, and the conversion between thrust and power was conducted. Constraints related to different performance requirements were analyzed, and the relationship between the rotor and the wing was established, resulting in the generation of constraint diagrams for the selection of basic parameters. This method allows for the rapid and effective estimation of basic parameters, including maximum take-off weight, rotor disk loading, and wing loading. Two tiltrotor aircraft were analyzed using this method. The estimated results closely matched actual values, with errors within a reasonable range. These findings demonstrate the method’s reliability and provide a reference for HSVTOL conceptual design and engine power matching.

At present,the research on supersonic civil aircraft wings mainly focuses on the low sonic boom design and supersonic drag reduction technologies.There are relatively few studies on the wing structural design.Therefore,a multi-level optimization method for the wing structural design in the preliminary design stage of supersonic civil aircrafts was proposed.It included the parametric modeling of the wing structural layout,the automatic generation of the finite element model for the structural size optimization,construction and training of a surrogate model for the deep neural network.And the optimization was solved based on the deep neural network.The analysis results show that the proposed optimization strategy could quickly design the wing structure of the supersonic civil aircraft.The deep neural network model has higher prediction accuracy than the traditional surrogate model.Thus,the proposed approach can improve the efficiency of the preliminary design for wing structure.

Two degrees of freedom (2DOF) and 1DOF active-controlled bearingless motors are favored for their cost-effectiveness and simplified control systems; however, their passive suspension characteristic leads to severe rotor vibrations at critical speeds under certain operating conditions. While existing literature has extensively studied this phenomenon, this paper provides a comprehensive review by categorizing the research into two main aspects: rotor vibration causes and suppression methods. The critical speed calculation formula is first introduced, followed by an analysis of the vibration's causes. Subsequently, the suppression methods are further classified into three categories based on their implementation approaches-motor design-based methods, control algorithm-based methods, and hybrid methods combining both-and each category is discussed in detail. Finally, conclusions summarize the main points and suggest future research directions.

Small land-air robots with rapid response and field operation capabilities hold significant potential for emergency rescue and field exploration applications. However, achieving stable and efficient mode transitions, along with effective terrain adaptability, remains a challenge. This letter presents a novel land-air robot, Flybot, which combines a bicopter UAV with a dual active-wheel, self-balancing wheel-legged base. Unlike traditional air-ground robots, this paper designs a single-drive, five-link leg structure that enhances lateral stability and terrain adaptability. By optimizing the five-link joint, we minimize energy consumption in ground mode, resulting in improved efficiency. Additionally, this paper establishes a hybrid dynamics model to describe Flybot's mode transitions and introduces a novel hybrid transition controller that leverages acceleration and throttle data to determine transition states. Finally, the adaptability and reliability of the robot are verified by the ground obstacle crossing experiment and the air-ground continuous motion experiment in the field, and the effectiveness of the hybrid transition controller of the robot is demonstrated. The weight-to-power ratio of the Flybot in air mode is 5.18 g/W, and the weight-to-power ratio in ground mode is 309 g/W, indicating the high efficiency of the Flybot.

The low-frequency pulse load poses a new challenge to the reliability of the power supply system. To adapt to sudden changes in pulse frequency, higher requirements are imposed on the dynamic performance of the converter. The conventional proportional-integral (PI) control cannot simultaneously ensure both excellent dynamic and steady-state performance. The capacitor energy balance control method can achieve high dynamic performance. However, it requires additional output compensation for the converter’s active current, and its implementation complexity hinders widespread adoption. This article develops an optimized dynamic PI control strategy for three-port rectifiers to address low-frequency pulse load challenges, leveraging capacitor charge balance control (CBC) for enhanced performance. By analyzing the optimal transient trajectories of voltage and current during pulse frequency step changes, the corresponding dynamic controller parameters are prestored based on actual operating conditions. When the pulse frequency changes, rapid active current adjustment within a single pulse cycle is achieved by modifying the outer-loop parameters. This approach maintains the decoupling voltage recovery curve near its optimal trajectory without requiring additional compensation. A three-port rectifier prototype was developed, and experimental results validate both the effectiveness and feasibility of the proposed control method.

Aircraft smart skin for structural health monitoring (SHM) plays an important role in the design and maintenance of advanced aircraft. To ensure its large-area monitoring function, large-scale and lightweight sensor networks are required, but they are difficult to implement due to limitations in structural design, manufacturing process and additional weight from cables. To solve this problem, the design method of lightweight and fully expandable piezoelectric (PZT) sensor networks (EPSNs) for aircraft smart skin is proposed. An EPSN includes a PZT array, a signal interface, and expandable signal transmission cables between them. The PZT array adopts both the stretchable island-bridge structural design and shared signal transmission wires design, thus can be designed and manufactured on a small scale and then deployed to a large area for applications with only a few signal wires and monitoring channels. To secure the electrical connections after deployment, signal transmission cables are also expandable. Based on this method, a 6 x 9 EPSN is designed and manufactured by the flexible printed circuit (FPC) process, ensuring its flexibility, light weight and high reliability. It can be fully expanded to 5894 % of its original size and integrated with a composite skin structure for impact and damage monitoring validation. The monitoring area reaches more than 2 m2, but the additional weight introduced is only about 8 g/m2. Results demonstrate that it achieves impact monitoring with 95 % accuracy and damage monitoring with 100 % accuracy for simulated damage. Moreover, a real and complex aircraft smart skin for SHM is realized and validated based on a 7 x 7 EPSN and a T800 wing-box panel. Results show that even on complex structures, the EPSN still has an impact monitoring accuracy of 82.5 % for 20 typical impact positions and a damage monitoring accuracy of 100 % for simulated damage as small as 10 mm x 10 mm x 0.5 mm and real impact-induced damage. This demonstrates the feasibility of EPSNs in large-scale and lightweight aircraft smart skin.

Bearingless permanent magnet lamella motors have become one of the research hotspots in the field of motors in recent years because of their lack of mechanical wear. The suspension accuracy of the rotor is one of the most important performance indicators of the bearingless slice motor, and the unbalanced magnetic pull greatly affects the suspension performance of the rotor. In order to improve the precision and stability of bearingless slice motors, it is crucial to understand and accurately compensate for the unbalanced magnetic pulling force. Therefore, studying the precise mathematical model of this force is essential to achieving high-quality levitation in these motors. To this end, for the unbalanced magnetic pull analysis model of the bearingless slice motor, this article summarizes and classifies existing analysis models from aspects such as modeling methods, modeling principles, modeling difficulty, and derivation processes, explain the analysis methods of various models and the advantages and disadvantages of the models. Finally, the analysis model of unbalanced magnetic pull is summarized and prospected.

This paper analyzes the magnetic field modulation effect in the integral slot winding permanent magnet synchronous machine (PMSM) from the perspective of air gap harmonic modulation considering the slotting effect. It is found that there is magnetic field modulation effect in the integral slot winding PMSM. This article classifies PMSM based on the winding structure, and shows that the magnetic field modulation effect commonly exists in PMSM with different winding structures, and from the perspective of multi-harmonic operation, this article explains the trade-off relationship between the harmonic content utilized in magnetic field modulation and the winding coefficient.

The magnetic field modulation theory effectively reveals the mechanism of torque generation in multi-harmonic working machines. In permanent magnet synchronous motors(PMSM), harmonic components of the magnetic field change significantly at different radial positions, making it difficult to describe the field distribution. Existing research suggests that there is no modulation effect in the closed slot of the stator, and errors exist in the quantitative analysis of torque generation. This paper explores the universal characteristics of magnetic field modulation effect in FSCW PMSM and makes following contributions:(1)Air gap is stratified to explored the distribution of modulated field, and revealing that modulation is a gradual process.(2)Analyze the impact of different slot opening conditions on magnetic field modulation.(3)Quantify the proportion of different harmonic magnetic field component, and combine the magnetic field modulation effect to determine the source of each harmonic, thereby obtaining the contribution of each harmonic to torque.The contribution of this article has a universal effect on the analysis of magnetic field of motors, and is a supplement and revision to the existing theory.

In recent years, there has been rapid development in electric aircraft, particularly electric vertical takeoff and landing (eVTOL) aircraft, as part of efforts to promote green aviation. During the conceptual design stage, it is crucial to select appropriate values for key parameters and conduct sensitivity analysis on these parameters. This study focuses on an electric tilt-rotor aircraft and proposes a performance analysis method for electric aircraft while developing a general design tool specifically for this type of aircraft. Subsequently, the impact of wing incidence angle, sweep angle, span, propeller solidity, battery-specific energy, and battery mass on range, maximum takeoff weight, and hover power are analyzed. The results show that the battery mass, wingspan, and wingtip chord length have great effects on the maximum takeoff weight; among these, battery mass had the greatest influence. In terms of range, the battery energy density has a great positive effect on range, while the increase in wing angle of incidence, wingtip chord length and battery mass have some negative effects on range.

There are two simultaneous issues in bearingless permanent magnet slice motors (BPMSMs): cogging torque and suspension force pulsation. Existing studies treat them as two separate parts without considering the potential relationship between them. To establish a theoretical basis for simultaneously reducing both components in the motor design stage, this paper proposes a method for analyzing the relationship between cogging torque and suspension force pulsation. An overview of air-gap field modulation is provided first. Based on this, the traditional motor theory is expanded to explain how cogging torque and suspension force pulsation are generated by the interaction of two modulated harmonics. The analysis also examines how adopting different winding structures affects the coupling relationship and the pulsation of suspension force. Finally, Finite Element Analysis (FEA) is used to verify the correctness of the theoretical analysis.

The more electric aircraft (MEA) electrical power system is designed with multiple types of redundancy to improve safety, consequently more attentions need to be paid to common cause failure. Considering common cause failure types of redundant systems, the comprehensive probability correction model based on multiple algorithms is proposed. The different common cause failure algorithms, such as ,9 , alpha , and the square root model are analysed for similar redundancy and non -similar redundancy systems with or without operational data, and the process for solving the common cause failure probability of system synthesis is investigated. Further research is carried out on the application of failure probability correction for aviation batteries and transformer rectifier units (TRU) of MEA. The results show that the proposed comprehensive probability correction model is effective, and can be applied to airborne complex systems. The research complements the safety assessment theory, and lays a foundation for the common cause failure probability correction and safety design of systems.