Search Results (933)

This study presents an approach to quantifying impact-induced damage severity in composites, focusing on synthetic carbon fibre-reinforced polymer (CFRP), natural flax fibre-reinforced polymer (FFRP) and hybrid fibre reinforced polymer (HFRP) composite of carbon and flax. The investigation aims to quantitatively characterise impact damage under energies ranging from 10 to 70 J through acousto–ultrasonics (AU) testing, proposing an efficient technique for evaluating the integrity of various FRP composites under in-service conditions. AU testing was performed at azimuthal angles of 0°, 30°, 45°, 60° and 90°, utilising acousto–ultrasonic waveform indices (AUWIs), such as wave velocity, peak amplitude, energy content, centroid frequency and skewness factor. The damage severity index is correlated with the damage mode. The findings establish that wave velocity is a reliable parameter for quantifying damage severity across all composite material types considered, with high adjusted R² values of 0.92 for CFRP, 0.89 for FFRP and 0.90 for HFRP. Peak amplitude also shows considerable sensitivity. Finally, this research highlights the limitations of traditional non-destructive evaluation (NDE) techniques and demonstrates the potential of combining multi-damage metrics with advanced imaging methods, such as X-ray micro-computed tomography (X-ray µCT) and scanning electron microscopy (SEM), to provide a comprehensive assessment of damage in various composite materials. The proposed methodology offers a promising approach for quantifying the impact damage severity in composite structures, as applicable to wind turbine blades, amongst other structural components. Full article

Offshore wind turbine blades in cold marine environments are exposed to low-temperature, high-humidity, and saline-droplet conditions, under which the melting behavior, interfacial sliding, and de-icing energy demand of saline ice differ from those of freshwater ice. Existing studies on combined phase-change coating–electrothermal de-icing have mainly focused on freshwater icing. Here, a glass-fiber-reinforced polymer (GFRP) NACA0018 airfoil was tested in a recirculating low-temperature icing wind tunnel to evaluate an n-tetradecane phase-change microcapsule/polyurethane (PCMS-PUR) coating combined with electrothermal heating at a salinity of 3%. Operating parameters, including heat flux density (8, 10, and 12 kW/m²), ambient temperature (−5, −10, and −15 °C), and incoming wind speed (3, 6, and 9 m/s), were systematically varied under a constant water flow rate (60 mL/min) and spray pressure (0.3 MPa) to characterize the evolution of ice morphology, temperature response, and de-icing energy consumption. During electrothermal de-icing, saline ice was more prone to interfacial softening and lubricating meltwater-layer formation, resulting in a dominant whole-block sliding detachment mode rather than gradual local melting. The PCMS-PUR coating further promoted interfacial melting and advanced ice destabilization through latent-heat release and thermal buffering. When the heat flux density increased from 8 to 12 kW/m², the de-icing energy consumption of the uncoated and coated blades decreased by 45.08% and 42.53%, respectively. The maximum energy-saving efficiency of the combined system reached 16.27% at 9 m/s. These findings clarify the de-icing behavior and energy-saving potential of combined phase-change coating–electrothermal systems under saline icing and provide guidance for the design of low-energy de-icing systems for offshore wind turbine blades. 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

The control of micro energy grids (MEGs) is characterized by volatility, uncertainty, and decentralization. Traditional power distribution algorithms, designed for centralized, dispatchable generators, are inadequate for MEG environments. Controllable load management provides peak shaving, load balancing, frequency regulation, and voltage stability, as well as fast balancing services for renewable energy grids in distributed power systems. A non-grid-tied inverter costs a fraction of its grid-tied counterpart for the same capacity. In the initial setting, one or more inverters are used. As the demand grows, more non-grid-tied inverters are added to the mix. Non-grid-tied inverters cannot be connected in parallel. There is no practical solution available in the market for the optimum utilization of this type of setting. Unlike a grid-tied microgrid, in non-grid-tied mode, a microgrid uses grid power only when needed, prioritizing renewable sources. This paper explores autonomous strategies for controlling and coordinating multiple renewable energy sources in MEG settings. It reviews and develops an algorithmic framework for optimal load distribution among multiple renewable sources, including solar photovoltaic (PV), wind turbines, and battery energy storage systems (BESSs). The proposed framework integrates resource forecasting, multi-objective optimization, and adaptive supervisory control to ensure stability, maximize renewable penetration, and minimize operational costs. Performance considerations, mathematical modelling, and potential implementation architectures are discussed. A hybrid approach, combining multiple algorithms, is therefore proposed. In this paper a real-life solution is proposed to a real-life problem. Full article

The increasing demand for higher efficiency and lower emissions in aircraft gas turbines motivates investigation of alternative thermodynamic cycle architectures. This study assesses the performance and nitrogen oxides (NOx) emission behavior of a triple-spool, separate-exhaust turbofan engine equipped with an interstage turbine burner (ITB). A baseline engine representative of the RB211 Trent 892 is first modeled at maximum takeoff, sea-level static conditions and verified against publicly available takeoff reference data. The cycle is then modified by introducing an isobaric secondary combustion process between the high-pressure and intermediate-pressure turbines. The effects of fan pressure ratio, bypass ratio, overall pressure ratio, high-pressure turbine inlet temperature, and ITB exit temperature are examined using two-parameter response surface sweeps. Main combustor NOx is estimated using an RQL-type cycle correlation, while the ITB contribution is represented using an engineering source–sink model accounting for new NOx formation and partial reburning of upstream NOx. The baseline model predicts specific thrust, thrust-specific fuel consumption (TSFC), and NOx emission index (EINOx) within ±8% of reference values. At a selected ITB operating point, specific thrust increases by 1.98%, TSFC increases by 9.84%, thermal efficiency decreases by 2.56%, and the adopted engineering source–sink model predicts a 20.03% reduction in fuel flow-weighted EINOx. The corresponding takeoff-mode NOx-per-thrust indicator decreases by approximately 12.1%. These results indicate that ITB integration introduces a coupled performance–emissions trade-off and should not be evaluated solely as a thrust augmentation method. Full article

The rapid expansion of wind energy as a key pillar of sustainable electricity generation has intensified the need for reliable and efficient wind turbine operation, particularly in minimizing failures of critical components such as gearboxes, which significantly impact maintenance costs, downtime, and overall lifecycle sustainability. This study proposes a vibration-based fault diagnosis framework integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and a Multiscale Convolutional Neural Network (MSCNN) for wind turbine gearbox condition monitoring. The approach decomposes non-stationary vibration signals into Intrinsic Mode Functions (IMFs) to capture meaningful oscillatory characteristics, which are then processed through parallel multiscale convolutional branches to learn both transient and long-term signal patterns. Experimental validation using the NREL Gearbox Reliability Collaborative dataset demonstrates that the proposed CEEMDAN-MSCNN model demonstrates strong performance compared to conventional machine learning methods and single-scale CNN architectures, achieving 99.50% accuracy on an unseen holdout dataset. The proposed framework supports predictive maintenance strategies by enabling reliable fault diagnosis, reducing unplanned downtime, and improving the operational efficiency and long-term sustainability of wind energy systems. Full article

This paper presents an in-depth investigation into the loss-of-excitation (LOE) protection for variable-speed pumped storage units with full-size converters (FSC-VSPSUs). It elucidates the dynamic interaction between electromagnetic transients and converter control loops under various machine-side converter (MSC) control strategies. The study reveals that units employing voltage-oriented control face a fundamental risk of phase-locked loop (PLL) instability following an LOE event. Given the inadequacy of traditional impedance-based protection for FSC-VSPSUs, a novel LOE protection scheme is proposed. This scheme integrates a dynamically tuned main impedance criterion with an acceleration criterion based on the rate of change of the impedance’s real part, incorporating a speed compensation coefficient to accommodate variable-speed operations. Experimental validation on an RTDS platform demonstrates that the proposed strategy accurately identifies LOE faults across various turbine and pumping modes, offering superior response speeds compared to traditional methods and other techniques reported in the existing literature. Full article

To meet the increasing demands of aircraft engines for high thrust-to-weight ratios and elevated turbine inlet temperatures, turbine blades have been progressively designed with thin-walled structures. It has been demonstrated that the mechanical properties of Ni₃Al-based single-crystal alloys (SXs) are highly sensitive to specimen thickness. In this study, the high-cycle fatigue behavior of [111]-oriented Ni₃Al-based SXs with wall thicknesses of 0.3, 0.5, and 0.8 mm was systematically investigated under tensile–tensile loading conditions at 1000 °C. The results revealed that, as the wall thickness decreased, the fatigue life of the alloy significantly deteriorated, while the crack initiation site gradually shifted from the specimen interior toward the surface and near-surface regions. Furthermore, the fatigue failure mode transitioned from being dominated by internal defects to being controlled primarily by near-surface damage. Near-surface damage induced by high-temperature oxidation and geometric constraints was identified as the primary factor responsible for the degradation of the high-cycle fatigue performance of the SXs. In addition, the cyclic deformation behavior at 1000 °C was governed by the synergistic effects of dislocation climb, cross-slip, and γ′-phase shearing. This study provides both theoretical guidance and experimental evidence for the structural optimization of next-generation single-crystal turbine blades for advanced aircraft engines. Full article

Reversible pump turbines (RPTs) play a key role in pumped hydro energy storage systems, where increasing grid flexibility requires frequent operation under off-design conditions. In turbine mode, deep partial load and no-load operation are often associated with severe flow instabilities, rotating stall, and strong rotor–stator interactions, which can limit operational flexibility and increase mechanical stress. Previous studies have shown that blade lean can influence hydrodynamic stability; however, its effect under no-load conditions remains insufficiently understood. In this work, the influence of runner blade lean on flow instabilities and rotor–stator interaction in a reversible pump turbine is numerically investigated. Two runner configurations, featuring a 0° and a $-15°$ blade lean angle, are analyzed through unsteady CFD simulations during the transition from deep partial load to no-load operation. The analysis focuses on flow field characteristics, blade loading, and the spectral content of pressure, torque, and radial forces. The results show that the negatively leaned runner significantly mitigates flow recirculation near the hub, reduces pressure and torque fluctuations, and strongly suppresses higher-order harmonic components associated with rotor–stator interaction. In particular, radial force amplitudes at blade-passing harmonics are substantially reduced under no-load conditions. These findings demonstrate that a negative blade lean improves hydrodynamic stability and reduces vibratory loads, contributing to the enhanced operational reliability of reversible pump turbines. Full article

This paper presents detailed small-signal modeling and modal analysis of a 1.5 MW grid-connected doubly fed induction generator (DFIG) wind turbine. A full nonlinear model capturing stator, rotor, and grid-side converter dynamics, DC-link voltage behavior, and the wind-turbine electromechanical subsystem is developed in the synchronously rotating d-q frame and linearized around a realistic steady-state operating point. The resulting state-space representation is utilized to investigate the intrinsic dynamic characteristics of the DFIG through eigenvalue analysis, modal classification, and participation factor evaluation. The results show that the open-loop DFIG contains a weakly damped electrical mode, a slowly growing unstable mode, and a near-integrator mode linked to the DC-link voltage, all of which strongly influence system behavior under disturbances. Parameter-sensitivity studies reveal how rotor speed, stator voltage, and rotor resistance affect the dominant modes, highlighting significant deterioration under low-voltage and low-speed operating conditions. Time-domain small-signal responses to temporary voltage sags further expose the vulnerability of DC-link voltage and power outputs when no coordinated control is applied. Overall, the study establishes a rigorous dynamic baseline for DFIG systems and provides the foundational insight needed for a follow-up paper focused on advanced damping and robustness-enhancing controllers. Full article

Turbine engine discs operate at high speeds with heavy loads. Any failure may result in the engine stopping or being destroyed. Therefore, it is necessary to check the normal modes and determine the rotational speeds at which they may occur. The aim of this article is to present a method of non-contact measurement of normal modes using the single and three-dimensional modes. The test element is the isolated first compressor stage of the DGEN-380 miniature jet engine (minijet). The disc has the shape of a hollow truncated cone with large blades. Vibration measurements were carried out in a non-contact manner using a scanning Doppler vibrometer. The measurement was made in 1D and 3D mode. The 1D mode is simpler and easier to prepare. In 3D mode, the calibration of three scanning heads significantly complicates the measurement preparation, but allows researchers to obtain the deformation in three-dimensional space The summary shows the measured frequencies using both modes. The shapes of deformation are also summarized. It is described how close the 1D measurement is to the 3D mode and in what frequency range. Finally, it is shown to what extent it is possible to describe the nature of structural oscillations in the 1D measurement mode. Full article

Accurate short-term wind power forecasting is crucial for maintaining the stability of modern power grid dispatching systems; however, the high nonstationarity and volatility of wind power data pose challenges for traditional forecasting models. To address these issues, a hybrid forecasting framework, variational mode decomposition (VMD)–improved sparrow search algorithm (ISSA)–support vector regression (SVR), is proposed herein. First, VMD is employed to decompose raw wind power data into multiple stable mode components. Then, the ISSA is introduced to optimize the hyperparameters of SVR, thereby alleviating the tendency of conventional SVR hyperparameter tuning methods to become trapped in local optima. Independent SVR forecasting models are then established for each decomposed mode component, and the final forecasting output is obtained via signal reconstruction. Experiments conducted on real-world datasets collected from five wind turbines demonstrate that the proposed framework consistently outperforms several baseline models. Compared with the VMD–SSA–SVR model, the proposed VMD–ISSA–SVR framework reduces the average root mean square error by 8.03% (from 124.28 to 114.19 kW) and improves the average coefficient of determination to 0.9024, with a maximum value of 0.9115. These results verify the effectiveness of the proposed framework in modeling complex nonlinear wind power data and highlight the superior optimization capability of the proposed ISSA. Full article

The identification of natural vibration modes in turbomachinery components is essential to ensure safe and reliable operation, particularly with respect to resonance avoidance. In lightweight structures such as bladed disks, conventional contact-based measurement techniques may alter the dynamic response of the system. This study presents an experimental comparison of one-dimensional (1D) and three-dimensional (3D) laser Doppler vibrometry for non-contact modal analysis of a miniature turbofan engine rotor. The investigation focuses on measurement accuracy, experimental complexity, and the practical applicability of both approaches. Experimental tests were conducted on an isolated rotor of the DGEN-380 engine using a scanning laser vibrometer system. The obtained natural frequencies and mode shapes were compared for both techniques. The results indicate that, for vibration modes dominated by axial motion, the differences between 1D and 3D measurements are typically below 1%. At the same time, the 1D approach significantly simplifies the experimental setup and reduces measurement time. These findings suggest that 1D vibrometry can be effectively used in selected engineering applications, while 3D measurements remain necessary for the full spatial characterization of complex vibration modes. Full article

Pump-as-turbine (PAT) units have been widely used for energy recovery in water-supply networks, petrochemical systems, and small hydropower applications; however, their turbine-mode performance is often limited because most commercial pumps are originally designed for pumping conditions. To improve the hydraulic performance of a low-specific-speed PAT, this study developed a surrogate-assisted multi-objective optimization framework combining three-dimensional computational fluid dynamics (CFD), design of experiments, a Kriging surrogate model, and a multi-objective genetic algorithm. Five key impeller geometric parameters, including blade inlet angles, blade wrap angles, and impeller outlet diameter, were selected as design variables, and turbine-mode efficiency was maximized under a head constraint of H ≥ 24 m at the rated condition of 1450 r/min. The results showed that the optimized design increased efficiency from 72.34% to 84.42% while satisfying the head requirement. Comparative analyses of pressure and velocity fields in the impeller and volute further revealed that the performance improvement was mainly associated with enhanced flow-field uniformity and reduced local hydraulic losses. A dedicated PAT test rig was finally established to experimentally validate the optimized design. Full article

This study introduces an innovative approach to enhance the lifetime of power converters linked in a back-to-back configuration for Type-4 wind turbines. The proposed method involves periodically changing both the connection points and functions of the machine-side converter (MSC) and grid-side converter (GSC) at ultra-low frequencies. This adjustment enables shared usage of power semiconductor switch lifetime, specifically of the IGBTs in power modules and their diodes, across the inverter and rectifier modes. In addition, the method incorporates simulation-based tests to assess aging effects on semiconductors as part of the evaluation process. To validate this proposed strategy, simulations were carried out using PSCAD for modeling the wind turbine and converter systems, alongside MATLAB for developing thermal models, calculating losses, and determining expected lifetimes. The impedance parameters employed in the thermal network were obtained through manufacturer-led experimental data; furthermore, the estimated junction temperatures align with the results obtained from the manufacturer’s tool. The findings illustrate that the proposed approach can significantly improve the lifetime of wind turbine converter systems, by values of 85% or more, even if the swapping operation is implemented during maintenance work. Full article