Search Results (501)

On 14 February 2025, the outer cladding of the Chornobyl New Safe Confinement (NSC) was damaged by an explosion caused by a one-way attack unmanned aerial vehicle (UAV), creating a hole of about 15 m in diameter and requiring about 300 penetrations to be made in the cladding during firefighting. This created an urgent need to assess radiation dose rates above damaged areas to support repair planning and worker radiation protection. This study presents a UAV-based survey of the equivalent gamma dose rate distribution above the damaged northern side of the NSC outer cladding. The survey used a bespoke system, integrating a multirotor UAV, an AccuRad Personal Radiation Detector (PRD), onboard data acquisition and transmission modules, and ground-based and server-side analytical components. Measurements were performed under real post-incident field conditions, including restricted flight zones, wind-induced turbulence, proximity to large metallic structures, and electronic warfare interference. The dataset was filtered for Global Positioning System (GPS) reliability, transformed into a metric coordinate system, and processed for spatial interpolation and mapping. The resulting distribution showed a spatially non-uniform radiation field: the main damage zone had relatively low equivalent gamma dose rates, whereas the highest values, up to 1092 μSv/h, were recorded over areas of the NSC closest to the Shelter Object. The study demonstrates UAV-based radiation mapping of a damaged large-scale confinement structure and provides data supporting Chornobyl Nuclear Power Plant repair planning. Full article

Centrifugal spraying systems are widely used in plant protection unmanned aerial vehicles (UAVs) due to their flexible droplet size adjustment and low-volume application capabilities. These systems can typically generate a wide range of volume median diameters from 50 to over 300 micrometers depending on rotational speed and disc structure. However, field performance is governed by a complex multi-physics coupling process rather than atomizer performance alone. Droplets released from the atomizer undergo near-field expansion and are subsequently entrained by rotor downwash. While strong downwash significantly improves deep canopy penetration compared to traditional application methods, it also dynamically reshapes droplet trajectories and size spectra through high-shear wake vortices. A critical comparative gap identified in this review is the severe discrepancy between static indoor atomization models and dynamic field transport. Current research lacks continuous spatial-temporal tracking of droplet size spectra under these complex field conditions. To address this, this review synthesizes the continuous mapping among droplet generation, spray plume transport, and canopy deposition. Precision application requires coordinated matching of flight parameters, aerodynamic downwash, and canopy architecture rather than single-parameter optimization. Future research must focus on the dynamic reconstruction of droplet size spectra and multisource perception-based feedback to shift centrifugal spraying systems from empirical parameter adjustment to mechanism-driven, closed-loop coordinated control. Full article

To investigate the nonlinear dynamic characteristics of magnetic suspended dual-rotor systems, this study examines periodic and quasi-periodic responses induced by bearing nonlinearities, including flux leakage and magnetic saturation effects. A nonlinear dynamic model is established using the finite element method, incorporating unbalance excitation and nonlinear bearing forces. A comprehensive parametric analysis is conducted to evaluate the effects of rotational speed, initial stiffness, and initial damping on the system’s dynamic responses and bifurcation behavior. The results reveal the occurrence of period-5 and quasi-periodic vibrations under nonlinear bearing conditions. In the quasi-periodic regime, low-frequency components dominate, and the force–current characteristics of the magnetic bearings spread over a wider band, reflecting a multi-valued force–current relationship. Furthermore, decreasing initial stiffness and increasing damping advance the onset of quasi-periodic responses and reduce the corresponding critical rotational speed. Notably, through real-time control adjustment, quasi-periodic motion can be converted into periodic motion, thereby distinguishing the system from conventional mechanically supported rotor systems. Experimental results obtained from a magnetic suspended dual-rotor test rig validate both the bearing-force model and the dynamic model, and further reveal periodic variations in system response under different speed ratios. Full article

Vertical take-off and landing (VTOL) configurations incur a structural weight penalty that reduces payload fraction and endurance compared to conventional fixed-wing and multirotor aircraft of comparable gross weight. To extend the endurance of VTOL UAVs, this work presents the design, analysis and control of a novel unmanned tilt trirotor aircraft with tandem wings, named Gong-H, featuring VTOL capability and high aerodynamic efficiency. A prototype of this aircraft was built with the rotor system mounted between tandem wings with a high wing coverage rate, which can achieve a more compact structure than other VTOL aircraft. The control forces and torques are provided not only by the rotor system in VTOL flight mode and the two tandem wings in cruise mode, but also by both the rotor system and wings in transition mode. Additionally, Computational Fluid Dynamics (CFD) simulations are conducted to optimize the wing configuration to improve the efficiency of cruise mode. Moreover, an airspeed-scheduled hybrid control framework based on incremental nonlinear dynamic inversion (INDI) and PID is adopted for different flight modes to improve the robustness of control and the stability of flight mode switching. Hover experiments confirm improved power efficiency compared to tilt quadrotor configuration, which extends endurance time and increases range. Additionally, complete flight cycle field experiments were conducted to demonstrate the aerodynamic feasibility of the prototype, including VTOL flight, cruise flight, and transition flight modes. Control surface redundancy tests and comparative INDI-PID validation under asymmetric disturbances further verify the practical robustness of the control framework. This work provides a design concept of VTOL aircraft and a practical solution for VTOL applications. Full article

The rotary vane vacuum pump plays a key role in the vapor recovery process at gasoline stations, where its geometric configuration directly influences system efficiency and stability. To address the limitations of conventional designs, this study develops a multi-objective optimization framework using particle swarm optimization (PSO). Under fixed chamber dimensions and specified constraints, the optimal design parameters are identified. The optimized pump achieves a 12.8% increase in average theoretical flow rate over the reference pump. Correlation analysis reveals that the exhaust port start angle has the strongest influence on performance, exhibiting a trade-off between compressed chamber pressure and exhaust pulsation. The rotor radius shows strong negative correlations with all objectives, while the intake port end angle is found to be a redundant parameter. Constraint sensitivity analysis indicates that the rotor radius and exhaust port start angle respond stably to variations in key constraints. Numerical simulations confirm a well-matched exhaust process, with the exhaust pulsation ratio minimized at an exhaust port start angle of 235°. This systematic approach provides an effective methodology for enhancing pump performance while respecting geometric constraints. Full article

Axial-flux permanent-magnet (AFPM) machines are becoming an increasingly promising solution for electromechanical systems requiring high power density. In particular, their use is expanding to electric vehicles (EVs), the aerospace industry, and advanced industrial applications, such as renewable energy applications. Their compact design, high torque-to-mass ratio, and relatively high efficiency make AFPM machines an attractive alternative to traditional radial-flux solutions. However, their integration for widespread application remains limited due to challenges in design, manufacturing, thermal management, and control systems, which ultimately also have an economic impact. This article presents a comprehensive and systematic review of AFPM machines, covering key aspects, including topology classification, design methodologies, electromagnetic modelling, optimisation methods, materials and manufacturing processes, and advanced control strategies. A structured, multi-level classification of AFPM machines is presented, incorporating stator and rotor configurations, magnetic circuit structures, winding types, and materials, thereby providing a unified overview of existing designs. Furthermore, the article presents an in-depth analysis of the sizing equations used to calculate and estimate the parameters, approaches to electromagnetic modelling (including the finite element method and magnetic equivalent circuits), and modern optimisation methods based on artificial intelligence. Particular attention is paid to materials science and new manufacturing technologies, such as soft magnetic composites, printed circuit board stators, and additive manufacturing, as well as to thermal management solutions required for high-power-density applications. This work provides a unified reference framework for researchers and engineers and outlines future directions for the development and industrial adoption of AFPM machines. Full article

All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to severe damage if resonance-prone operating conditions are not identified in time. Although fault diagnosis in DFIGs has been widely investigated using current, voltage, and flux signatures, comparatively fewer studies have examined fault-specific vibration behaviour under stator and rotor interturn faults (ITTFs), particularly through a coupled EM structural framework. In addition, prior vibration-based studies have not examined the influence of end winding ITTFs, its location, severity, and modal interaction investigating resonance risk. This paper considers vibration characteristics of a variable-speed 2.8 MW DFIG used in a grid-connected Type-3 wind turbine unit (WTU) at no-load operating condition. The DFIG is modelled in ANSYS Academic Research v 2022 R2 Maxwell for EM behaviour assessment for ITTFs in both stator and rotor windings along with modal analysis (MA) in ANSYS Workbench to examine the undamped stator and rotor modes over a range of frequencies. This coupled approach enables identification of vibration signatures associated with different ITTF types. The results show the magnetic flux density near faulty end-winding region increases with fault severity and ranges from 4.19 T to 4.39 T in proximity to faulty windings. A dominant modal frequency band of 60–65 Hz is identified, where stator and rotor modes coincide, creating probable resonance conditions. A severe vibration response is observed for single-phase stator ITTF, showing an amplitude of 2116 mm/s at 480 Hz for a larger number of shorted turns, indicating that asymmetric faults can produce stronger EM excitation than multi-phase faults. The main contribution of this paper is demonstration of a fault-specific, MA and vibration-based Condition monitoring system (CMS) implementation workflow for a DFIG. Unlike prior vibration-based studies that primarily focus on general machine vibration, mechanical faults, bearings, etc., this paper links stator and rotor ITTF induced EM excitation to modal characteristics, resonance behaviour, and measurable vibration signatures, establishing vibration analysis (VA) as a practical complementary technique for CMS of ITTFs in DFIGs. Full article

Conventional transient stability assessment in multi-machine power systems relies predominantly on fixed thresholds, which exhibit limited adaptability to varying operating conditions and fail to provide a unified analytical framework for rotor angle and voltage stability. To address these challenges, this paper proposes an adaptive threshold warning method based on geometric algebra. A multi-dimensional unified state vector incorporating generator rotor angles, speeds, electromagnetic powers and bus voltage magnitudes and phases is constructed to map system dynamics onto a high-dimensional geometric trajectory. The second- and third-order wedge products of this trajectory are computed to quantify disturbance severity and volumetric expansion preceding instability. An adaptive threshold mechanism is established utilizing sliding window robust statistics (Median Absolute Deviation) to track the trajectory’s instantaneous dimension in real time. Validation on the IEEE 39-bus system demonstrates that the proposed method issues a warning at t = 4.90 s, achieving a detection advance of 0.30 s relative to the conventional 30° rotor angle separation threshold. The method exhibits strong noise robustness with only 40 ms warning delay under 20 dB SNR conditions, and effectively captures rotor angle–voltage coupling characteristics. The geometric algebra framework offers a unified assessment tool with distinct advantages in computational speed, adaptivity, and interpretability. Full article

Global shifts in energy policy have contributed to an increase in electricity generation from renewable sources, which introduces unique issues with volatility and grid reliability. Robust grid-scale energy storage methods must fill the gap between generation and consumption. Flywheel energy storage (FES) is a mechanical technology that utilizes the stored kinetic energy of a rotating body, but is typically only suited for shorter-term frequency regulation due to significant windage losses. In this work, a novel Python 3.13-based simulation and optimization tool is presented and used to optimize geometric design parameters for efficiency, energy density, and other metrics. The simulation utilizes a 1 degree-of-freedom, multi-regime fluid friction model with a time-marching algorithm. The optimization functionality utilizes pyswarms, a particle swarm optimization package, with adjustable search parameters and cost functions to evaluate simulation results. Optimization parameters include geometric parameters of rotor radius, shaft radius, airgap width, and airgap height; material properties of mass and moment of inertia; and initial angular velocity. An optimal initial angular velocity is found for a particular geometry, lasting 30 times longer until self-discharge versus the worst values. This work can inform the design of flywheel systems to minimize windage losses and promote the technology’s utility for longer-term energy storage. Full article

Wind turbine gearbox failures lead to substantial downtime and high maintenance costs. Although condition-monitoring systems are widely used, traditional life-extension methods that simply reduce power output often decrease revenue. Current research frequently treats life optimization and power generation independently, and as such lacks a quantitative link between control strategies and remaining useful life. To address this gap, this paper proposes a novel life-extension strategy that optimizes power generation by dynamically adjusting rotor speed and pitch angle. A transfer learning–long short-term memory model enhanced by multi-source information fusion is developed to predict remaining useful life accurately under conditions with limited fault data. Utilizing real operational data from 2 MW wind turbines in Northeast China, the study quantitatively analyzes the impact of variable-speed and pitch control. The results demonstrate that while both strategies extend life, variable-speed control offers superior effectiveness in improving remaining useful life. Furthermore, maximum power generation is achieved not at full capacity, but when the output is reduced to approximately 70% of the nominal power. At this optimal point, the proposed strategy increases power generation by up to 7.3%. This establishes a dynamic balance between operational safety and economic efficiency, overcoming the limitations of conventional methods. Full article

Proton exchange membrane fuel cell–battery hybrid power systems provide an effective solution to overcome the limited endurance of battery-powered multirotor unmanned aerial vehicles. However, the highly transient power demands of quadcopter platforms, combined with balance-of-plant losses and operational constraints, create significant challenges for reliable energy management. This study proposes a degradation-aware stress-mitigation model predictive control-based energy management framework to maximize mission endurance under realistic conditions. A control-oriented, physics-consistent model is developed using manufacturer polarization data from a 500 W Aerostak proton exchange membrane fuel cell. The model captures polarization behavior, balance-of-plant loads, battery dynamics, and direct current-bus power balance. The model predictive control strategy optimally allocates power by maintaining direct current-bus stability, regulating battery state-of-charge within safe limits, and constraining fuel cell power ramp rates to mitigate degradation. High-fidelity simulations are conducted under stochastic wind disturbances and mission-dependent load profiles, including takeoff, climb, cruise, and maneuvering phases. The results show continuous power delivery without unmet load demand. The hybrid system achieves a flight endurance of 220–224 min, consuming a total of 89.99 g of hydrogen at an average rate of 0.398–0.412 g/min, indicating a notable reduction under the considered operating conditions. Additionally, long-term analysis indicates that over 97% of initial endurance is preserved after 100 cycles, demonstrating robustness against fuel cell aging. An analytical real-time feasibility assessment further indicates that the control-oriented formulation is compatible with the computational resources of typical unmanned aerial vehicle-class onboard processors, while the integration of adaptive and robust predictive control techniques is identified as a direction for future work. Full article

In the paper, a systematic treatment of sensitivity analysis of multivariable cont rol systems within the framework of the characteristic transfer functions (CTFs) method is given. The CTFs method (also called characteristic gain loci method) allows one to associate with an N-dimensional multi-input multi-output (MIMO) system a set of N independent single-input single-output (SISO) characteristic systems and thereby to reduce the analysis and design of a MIMO system to the analysis and design of N SISO systems. The formulas determining the sensitivity functions of the CTFs and the sensitivity vectors of the canonical basis axes to small variations of parameters of general type MIMO systems are derived. The relations between the sensitivity functions of the open-loop and closed-loop MIMO systems are established. Two illustrative examples are considered. The first of them concerns the sensitivity of a two-dimensional non-robust system with a large degree of skewness of the canonical basis axes. In the second example, the sensitivity of the control system of a hexacopter (a multirotor UAV with six rotors) to small degradations in motors efficiency is analyzed. Full article

As unmanned aerial vehicle (UAV) systems evolve from automated execution toward autonomous decision-making, multirotor UAVs increasingly face complex dynamics, uncertain sensing conditions, and task-level autonomy demands. Reinforcement learning (RL) has emerged as a promising learning-based paradigm for addressing these challenges. Existing surveys on RL-based UAV control predominantly classify methods from an algorithmic or learning-paradigm perspective, while relatively little attention has been paid to the functional roles of RL policies within the control loop. This often leads to an unclear correspondence between algorithmic characteristics and the requirements of different control layers. To address this gap, this review proposes a biomimetic “spinal cord–cerebellum–cerebrum” framework, organizing existing RL studies into low-level dynamic stabilization, mid-level perception–action coordination, and high-level task planning and decision-making. The proposed hierarchy emphasizes the functional role and intervention depth of RL policies within the control architecture, further supporting a layer-wise analysis of sim-to-real challenges. This review aims to provide a structured understanding of the roles of reinforcement learning in hierarchical UAV control and to highlight future research directions toward robust real-world deployment. Full article

The surging need for public security risk mitigation has placed stricter demands on the modernization of emergency response capacities. Unmanned aircraft systems (UASs) offer a promising solution for liquid anti-riot agent dispersion, yet the complex interaction between rotor-induced downwash and droplet trajectories makes nozzle layout optimization a significant challenge. To address the prohibitive computational costs of traditional Computational Fluid Dynamics (CFD) and the limitations of single-objective optimization, this study proposes an integrated “simulation–modeling–optimization–decision” framework. First, a linear nozzle layout was identified as superior to the traditional circular arrangement, achieving a 44.8% increase in deposition rate. Subsequently, Optimal Latin Hypercube Sampling (OLHS) and CFD simulations were combined to construct high-precision Kriging surrogate models for three key indicators: deposition rate, uniformity, and coverage rate. The NSGA-II algorithm was then employed to solve the multi-objective trade-off, followed by the entropy-weighted TOPSIS method to identify the optimal engineering solution. Results indicate that nozzle count is the dominant system-level variable under the constant per-nozzle flow-rate condition, showing strong positive correlations with all performance indicators. The identified optimal configuration (6 nozzles with a 1.88 m boom length) achieved a 66.1% increase in deposition rate and an 18.7% increase in coverage rate compared to the original circular layout. Furthermore, the surrogate-based framework improved optimization efficiency to 296% compared to full factorial methods. This study provides a scientific theoretical basis and a highly efficient technical pathway for the structural design of high-performance UAV spray systems. Full article

One of the most critical challenges in maritime transport decarbonization, as part of the EU greenhouse gas (GHG) neutrality strategy, is the reduction in GHG and harmful emissions from the energy systems of existing vessels. Furthermore, the potential for implementing decarbonization technologies in operating vessels remains significantly more limited compared to newly constructed ships. Selecting appropriate decarbonization measures requires a comprehensive evaluation of technological feasibility, economic viability, and environmental performance, in accordance with the regulatory frameworks established by the IMO and the EU. A major limitation in such decision-making processes is ensuring the representativeness and reliability of expert judgments. In order to improve the reliability of results by expanding and structuring the information base, this study proposes and implements a method based on the integration of SWOT analysis with multi-criteria decision-making (MCDM) methods. The objective of this study was to examine the methodological aspects of testing the integrated application of comprehensive analysis and ranking methods for decarbonization technologies as applied to a prototype oil tanker. Based on the SWOT analysis method, technological solutions that are available for practical application were identified for the medium-term decarbonization period considered in the study, up to 2030–2035. Subsequent rating based on several applied multi-criteria (MCDM) analysis methods (TOPSIS, COPRAS, SAW) allowed us to examine the range, stability and sensitivity of the obtained solutions in relation to the methods themselves and scenarios with variations in the weighting factors of the evaluation criteria. The complete match of the ratings obtained using the TOPSIS and COPRAS methods confirms the stability of the multi-criteria decision-making process (priority-compromise order): CCS, kite, air lubrication, Flettner rotor. The performed sensitivity analysis showed that the technology rankings remain relatively stable when the weighting factor for the CO₂ reduction criterion varies within a range of approximately ±10%, while larger deviations result in an increasing difference between all three MCDM methods. For the TOPSIS method, the change limits for the critical values of the threshold indicators were ±20%, the COPRAS method showed intermediate results, and changing the weighting coefficients within a ±20% range did not alter the selection of the best technology. The results obtained allow for a positive assessment of the effectiveness of the proposed integrated methodology when applied as an alternative in the initial stage of ranking decarbonization methods for in-service ships. Full article