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Passive flow control around airfoils, wind turbines, and submarines to enhance their aerodynamic properties is the subject of interest in several studies. Previous research provides different solutions, from basic changes in surface roughness and simple geometries to complex shapes and mechanical solutions. This article presents experimental research using the Particle Image Velocimetry (PIV) method on a NACA 0012 airfoil at a Reynolds number of 66,400. Initially, the airfoil was tested for three different angles of attack: 13°, 15°, 17°, and 19°. These tests revealed that angles of attack above 15° significantly increase boundary layer detachment, as shown in the normalized streamwise velocity fields U x . In the second stage of the research, a different-shaped microcylinder with a characteristic dimension (d/c) of 0.01 was added to the leading edge of the airfoil at a high angle of attack of 17°. Unlike traditional vortex generators placed at the rear of the airfoil, this configuration aimed to reduce boundary layer detachment. The experiment demonstrated that the microcylinder effectively reduced boundary layer detachment at this angle of attack. [ABSTRACT FROM AUTHOR]

Wind turbine blades are critical components of wind energy systems, and their structural health is essential for reliable operation and maintenance. Several studies have used time-domain and frequency-domain features alongside machine learning techniques to predict faults in wind turbine blades, such as erosion and cracks. However, a key gap remains in integrating these methods into a unified framework for fault prediction, which could offer a more comprehensive solution for diagnosing faults. This paper presents an approach to classify faults in wind turbine blades by leveraging well-known signals and analysis with machine learning techniques. The methodology involves a detailed feature engineering process that extracts and analyzes features from the time and frequency domains. Open-source vibration data collected from an experimental setup (where a small wind turbine with an artificially eroded and cracked blade was tested) were utilized. The time- and frequency-domain features were extracted and analyzed using various machine learning algorithms. It was found that erosion and crack faults have unique time- and frequency-domain features. The crack fault introduces an amplitude modulation in the vibration time wave, which produces sidebands around the fundamental frequency in the frequency domain. However, erosion fault introduces asymmetricity and flatness to the vibration time wave, which produces harmonics in the frequency-domain plot. The results also highlighted that utilizing both time- and frequency-fault features enhances the performance of the machine learning algorithms. This study further illustrates that even though some machine learning algorithms provide similar high classification accuracy, they might differ in quantifying error Types I, II, and, III, which is extremely important for maintenance engineers, as it might lead to undetected fault events and false alarm events. [ABSTRACT FROM AUTHOR]

Numerical simulation technology is a crucial tool for reducing costs and increasing efficiency in the wind power industry. However, with the development of large-scale wind turbines, the computational cost of numerical simulation has gradually increased. This paper uses the geometric similarity, structural similarity criterion, Reynolds similarity and boundary layer theory to establish a scaled model of the geometric three-dimensional shape, composite material, and finite element mesh of large wind turbine blades. The study analyzes the aerodynamic, gravitational, and centrifugal load variations within the scaled model. The proportional relationship between the scaled model's operating parameters, the numerical simulation's environmental parameters, and the mechanical response parameters is established. These parameters are coordinated to ensure the similarity of the blade structure and the fluid dynamics. For a geometric scale factor of 0.316, the relative difference in maximum deflection is 4.52%, with a reduction in calculation time by 48.1%. On the premise of ensuring the calculation accuracy of the aerodynamic and structural response of the blade, the calculation efficiency is effectively improved. [ABSTRACT FROM AUTHOR]

The wind energy sector is experiencing rapid growth, marked by the expansion of wind farms and the development of large-scale turbines. However, conventional manual methods for wind turbine operations and maintenance are struggling to keep pace with this development, encountering challenges related to quality, efficiency, and safety. In response, unmanned aerial vehicles (UAVs) have emerged as a promising technology offering capabilities to effectively and economically perform these tasks. This paper provides a review of state-of-the-art research and applications of UAVs in wind turbine blade damage detection, operations, and maintenance. It encompasses various topics, such as optical and thermal UAV image-based inspections, integration with robots or embedded systems for damage detection, and the design of autonomous UAV flight planning. By synthesizing existing knowledge and identifying key areas for future research, this review aims to contribute insights for advancing the digitalization and intelligence of wind energy operations. [ABSTRACT FROM AUTHOR]

With the trend towards larger and lighter designs of wind turbines, blades are progressively being developed to have longer and more flexible configurations. Under standstill conditions, the separated flow induced by a wide range of incident flow angles can cause complex aerodynamic elastic phenomena on blades. However, classical momentum blade element theory methods show limited applicability at high angles of attack, leading to significant inaccuracies in wind turbine performance prediction. In this paper, the geometrically accurate beam theory and high-fidelity CFD method are combined to establish a bidirectional fluid–structure coupling model, which can be used for the prediction of the aeroelastic response of wind turbine blades and the analysis of fluid–structure coupling. Aeroelastic calculations are carried out for a single blade under different working conditions to analyze the influence of turbulence, gravity and other parameters on the aeroelastic response of the blade. The results show that the dominant frequency of the vibration deformation response in the edgewise direction is always the same as the first-order edgewise frequency of the blade when the incoming flow condition is changed. The loading of gravity will make the aeroelastic destabilization of the blade more significant, which indicates that the influence of gravity should be taken into account in the design of the aeroelasticity of the wind turbine. Increasing the turbulence intensity will change the dominant frequency of the vibration response in the edgewise direction, and at the same time, it will be beneficial to the stabilization of the aeroelasticity response. [ABSTRACT FROM AUTHOR]

The wind energy sector faces a persistent challenge in developing sustainable solutions for decommissioned Wind Turbine Blades (WTB). This study utilises Lifecycle Assessment (LCA) to evaluate the gate-to-gate carbon footprint of high-profile disposal and recycling methods, aiming to determine optimal strategies for WTB waste treatment in the UK. While this article analyses the UK as a case study, the findings are applicable to, and intended to inform, recycling strategies for WTB waste globally. Long-term sustainability depends heavily on factors like evolving energy grids and changing WTB waste compositions and these must be considered for robust analysis and development strategy recommendations. In the short to medium term, mechanical recycling of mixed WTB waste is sufficient to minimise Global Warming Potential (GWP) due to the scarcity of carbon fibre in WTB waste streams. Beyond 2040, carbon fibre recycling becomes crucial to reduce GWP. The study emphasises the importance of matching WTB sub-structure material compositions with preferred waste treatment options for the lowest overall impact. Future development should focus on the extraction of carbon fibre reinforced polymer (CFRP) structures in WTB waste streams, commercialising large-scale CFRP structure recycling technologies, establishing supply chains, and validating market routes for secondary carbon fibre products. In parallel, scaling up low-impact options, like mechanical recycling, is vital to minimise WTB waste landfilling. Developing viable applications and cost-effective market routes for mechanical recyclates is necessary to displace virgin glass fibres, while optimising upstream recycling processes based on product requirements. [ABSTRACT FROM AUTHOR]

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs' Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions. [ABSTRACT FROM AUTHOR]

As wind turbine blade length increases, reconciling lightweight design with strength necessitates continuous advancements in process technology. The impact of three different process technologies–vacuum-assisted resin transfer moulding (VARTM), prepreg, and pultrusion–on the properties of wind turbine blade composite spar caps was investigated using scanning electron microscopy, dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, and static and fatigue testing. The results demonstrated that the fibre weight content and 0° tensile modulus of the VARTM and pultrusion composites increased as compared to those of the prepreg samples. Subsequently, the properties of a 94-m blade were analysed using the Ansys Composite PrepPost (ACP) and static structure modules in Ansys simulations, and the weights of the spar cap were compared with test data of materials under different process technologies. The results showed that the masses of the spar cap of a 94-m blade in the pultrusion, VARTM, and prepreg processes were 7965, 9170, and 9942 kg, respectively. The quantitative influence rules on the weight of the wind turbine blade spar cap prepared through different process technologies were formulated. The findings of this study are promising and are expected to aid the development of wind turbine blade process technologies. [ABSTRACT FROM AUTHOR]

Blade icing seriously affects wind turbines' aerodynamic performance and output power. Timely and accurately predicting blade icing status is crucial to improving the economy and safety of wind farms. However, existing blade icing prediction methods cannot effectively solve the problems of unbalanced icing/non-icing data and low prediction accuracy. In order to solve the above problems, this paper proposes a wind turbine blade icing prediction method based on the focal loss function and CNN-Attention-GRU. First, the recursive feature elimination method combined with the physical mechanism of icing is used to extract features highly correlated with blade icing, and a new feature subset is formed through a sliding window algorithm. Then, the focal loss function is utilized to assign more weight to the ice samples with a lower proportion, addressing the significant class imbalance between the ice and non-ice categories. Finally, based on the CNN-Attention-GRU algorithm, a blade icing prediction model is established using continuous 24-h historical data as the input and the icing status of the next 24 h as the output. The model is compared with advanced neural network models. The results show that the proposed method improves the prediction accuracy and F1 score by an average of 6.41% and 4.27%, respectively, demonstrating the accuracy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Aspects concerning resonance and global stability of a wind turbine blade must be carefully considered in its optimal design. In this paper, a composite wind turbine blade with an external geometry based on the NREL 5 MW model was subjected to multi-objective structural optimization considering these aspects. Four multi-objective structural optimization problems are formulated considering the blade mass, the maximum blade tip displacement, the natural frequencies of vibration, and the critical load factor as objective functions. The design variables are the number of plies, material, and fiber orientation. The design constraints are the materials' margin of safety, the blade's allowable tip displacement, and the minimum load factor. The blade model is submitted to the loads determined by the actuator lines theory and discretized in a finite element parameterized model using the Femap software according to geometric design variables. Among many multi-objective evolutionary algorithms available in the literature concerning evolutionary computation, the NSGA-II is the adopted evolutionary algorithm to solve the multi-objective optimization problems. Pareto fronts are obtained and performance indicators are used to evaluate the distribution of the non-dominated solutions. Multi-criteria decision-making is used to extract the solutions from the Pareto fronts according to the decision-maker's preferences. The values of the objective functions, design variables, and constraints are presented for each extracted solution. The proposed study is expected to contribute to the multi-objective optimization and the structural design of wind turbine blades. [ABSTRACT FROM AUTHOR]

This work aims to propose a method enabling the evaluation of wind turbine blade damage and fatigue related to a 1 Hz wind speed signal applied to a large period and based on standard 10-min SCADA data. Previous studies emphasize the need for sampling with a 1 Hz frequency when carrying out blade damage computation. However, such methods cannot be applied to evaluate the damage for a long period of time due to the complexity of computation and data availability. Moreover, 1 Hz SCADA data are not commonly used in the wind farm industry because they require a large data storage capacity. Applying such an approach, which is based on a 1 Hz wind speed signal, to current wind farms is not a trivial pursuit. The present work investigates the possibility of overcoming the preceding issues by estimating the equivalent 1 Hz wind speed damage over a 10-min period characterized by SCADA data in terms of measured mean wind speed and turbulence intensity. Then, a discussion is carried out regarding a method to estimate the uncertainty of the simulation, in a bid to come up with a tool facilitating decision-making by the operator. A statistical analysis of the damage assessed for different wind turbines is thus proposed to determine which one has sustained the most damage. Finally, the probability of reaching a critical damage level over time is then proposed, allowing the operator to optimize the operating and maintenance schedule. [ABSTRACT FROM AUTHOR]

This paper examines the potential for reducing the cost of energy for super-scale wind turbines through the use of a downwind configuration. Using nonlinear aeroelastic modeling, the responses of 10 MW upwind and downwind wind turbine blades are simulated and compared under shear wind conditions. The study evaluates the impact of both nonlinear and linear aeroelastic models on the dynamic response of different blade sizes, highlighting the need for a nonlinear approach. Results indicate that the linear model overestimates blade deformations (18.14%) and the nonlinear model is more accurate for predicting the aeroelastic response of ultra-long blades of 86.35 m. The study also finds that the downwind turbine blade experiences smaller flapwise moment (17.53%), and blade tip flapwise deformation (33.97%) than the upwind turbine blade, with increased load and deformation fluctuation as wind shear increases. [ABSTRACT FROM AUTHOR]

Wind turbine blades are one of the largest parts of wind power systems. It is a handicap that these large parts of numerous wind turbines will become scrap in the near future. To prevent this handicap, newly produced blades should be recyclable. In this study, a turbine blade, known as the new generation of turbine blade, was manufactured with reinforced carbon beams and recycled, low-density polyethylene materials. The manufacturing addressed in this study reveals two novelties: (1) it produces a heterogeneous turbine blade; and (2) it produces a recyclable blade. In addition, this study also covers mechanical tests using a digital image correlation (DIC) system and modeling investigations of the new generation blade. For the mechanical tests, displacement and strain data of both new generation and conventional commercial blades were measured by the DIC method. Instead of dealing with the modeling difficulty of the new generation blade's heterogeneity we modeled the blade structural system as a whole using the moment–curvature method as part of the finite element method. Then, the behavior of both the new generation and commercial blades at varying wind speeds and different angles of attack were compared. Consequently, the data reveal that the new generation blades performed sufficiently well compared with commercial blades regarding their stiffness. [ABSTRACT FROM AUTHOR]

Wind energy is considered a clean energy source and is predicted to be one of the primary sources of electricity. However, leading-edge erosion of wind turbine blades due to impacts from rain drops, solid particles, hailstones, bird fouling, ice, etc., is a major concern for the wind energy sector that reduces annual energy production. Therefore, leading-edge protection of turbine blades has been an important topic of research and development in the last 20 years. Further, there are critical issues related to the amount of waste produced, including glass fiber, carbon fiber, and various harmful volatile organic compounds in turbine fabrication and their end-of-life phases. Hence, it is vital to use eco-friendly, solvent-free materials and to extend blade life to make wind energy a perfect clean energy source. In this study, cellulose microparticles (CMP) and cellulose microfibers (CMF) have been used as fillers to reinforce water-based polyurethane (PU) coatings developed on glass fiber reinforced polymer (GFRP) substrates by a simple spray method for the first time. Field emission scanning electron microscopy images show the agglomerated particles of CMP and fiber-like morphology of CMF. Fourier transform infrared spectra of CMP, CMF, and related coatings exhibit associated C–H, C=O, and N–H absorption bands of cellulose and polyurethane. Thermal gravimetric analysis shows that CMP is stable up to 285 °C, whereas CMF degradation is observed at 243 °C. X-ray photoelectron spectroscopy of C 1s and O 1s core levels of CMP, CMF and related coatings show C–C/C–H, C–O, C–OH, and O–C=O bonds associated with cellulose structure. The solid particle erosion resistance properties of the coatings have been evaluated with different concentrations of CMP and CMF at impact angles of 30° and 90°, and all of the coatings are observed to outperform the PU and bare GFRP substrates. Three-dimensional (3D) profiles of erosion scans confirm the shape of erosion scars, and 2D profiles have been used to calculate volume loss due to erosion. CMP-reinforced PU coating with 5 wt.% filler concentration and CMF-reinforced PU coating with 2 wt.% concentration are found to be the best-performing coatings against solid particle erosion. Nanoindentation studies have been performed to establish a relation between H3/E2 and the average erosion rate of the coatings. [ABSTRACT FROM AUTHOR]

With global warming and the depletion of fossil energy sources, renewable energy is gradually replacing non-renewable energy as the main energy in the future. As one of the fastest growing renewable energy sources, the safety and reliability of wind energy have been paid more and more attention. The size of modern wind turbines is becoming larger and larger. As the main component of wind turbines to capture energy, the blade is often damaged by various complex environments and irregular loads. Therefore, the health monitoring and damage identification of wind turbine blades have become a main research focus. At present, in addition to the overview of various detection methods of wind turbine blades, there is a lack of comprehensive classifications and overviews of the main damage types, damage-generation mechanisms, and basic principles of the damage-detection technology of wind turbine blades. In this paper, firstly, the common fault types of wind turbine blades, such as trailing edge cracking, lightning strike, leading edge corrosion pollution, icing, and delamination, as well as their generation mechanism, are comprehensively analyzed. Then, the basic principles and the latest research progress of the current main detection technologies, such as vision, ultrasonic, thermal imaging, vibration, acoustic emission, and so on, are comprehensively reviewed. The advantages and limitations of the various detection technologies for practical application are summarized. Finally, through a comparative analysis of the various damage-detection technologies, we try to find potential future research directions, and draw conclusions. This paper will provide a reference for understanding the mechanism behind the main damage types and the damage-detection methods of wind turbine blades. It has important reference value for further promoting practical research of wind turbine blade damage-detection technology and grasping this research direction. [ABSTRACT FROM AUTHOR]

Delamination in Wind Turbine Blades (WTB) is a common structural problem that can generate large costs. Delamination is the separation of layers of a composite material, which produces points of stress concentration. These points suffer greater traction and compression forces in working conditions, and they can trigger cracks, and partial or total breakage of the blade. Early detection of delamination is crucial for the prevention of breakages and downtime. The main novelty presented in this paper has been to apply an approach for detecting and diagnosing the delamination WTB. The approach is based on signal processing of guided waves, and multiclass pattern recognition using machine learning. Delamination was induced in the WTB to check the accuracy of the approach. The signal is denoised by wavelet transform. The autoregressive Yule–Walker model is employed for feature extraction, and Akaike’s information criterion method for feature selection. The classifiers are quadratic discriminant analysis, k-nearest neighbors, decision trees, and neural network multilayer perceptron. The confusion matrix is employed to evaluate the classification, especially the receiver operating characteristic analysis by: recall, specificity, precision, and F-score. [ABSTRACT FROM AUTHOR]

Wind turbine blades are easily struck by lightning, a phenomenon that has attracted more and more attention in recent years. On this subject a large current experiment was conducted on three typical blade sandwich structures to simulate the natural lightning-induced arc effects. The resulting damage to different composite materials has been compared: polyvinyl chloride (PVC) and polyethylene terephthalate (PET) suffered pyrolysis and cracks inside, while the damage to balsa wood was fibers breaking off and large delamination between it and the resin layer, and only a little chemical pyrolysis. To analyze the damage mechanism on sandwich structures of different materials, a finite element method (FEM) model to calculate the temperature and pressure distribution was built, taking into consideration heat transfer and flow expansion due to impulse currents. According to the simulation results, PVC had the most severe temperature and pressure distribution, while PET and balsa wood were in the better condition after the experiments. The temperature distribution results explained clearly why balsa wood suffered much less chemical pyrolysis than PVC. Since balsa wood had better thermal stability than PET, the pyrolysis area of PET was obviously larger than that of balsa wood too. Increasing the volume fraction of solid components of porous materials can efficiently decrease the heat transfer velocity in porous materials. Permeability didn't influence that much. The findings provide support for optimum material selection and design in blade manufacturing. [ABSTRACT FROM AUTHOR]

This paper describes the feasibility analysis of an innovative, extensible blade technology. The blade aims to significantly improve the energy production of a wind turbine, particularly at locations with unfavorable wind conditions. The innovative 'smart' blade will be extended at low wind speed to harvest more wind energy; on the other hand, it will be retracted to its original shape when the wind speed is above the rated wind speed to protect the blade from damages by high wind loads. An established aerodynamic model is implemented in this paper to evaluate and compare the power output of extensible blades versus a baseline conventional blade. The model was first validated with a monitored power production curve based on the wind energy production data of a conventional turbine blade, which is subsequently used to estimate the power production curve of extended blades. The load-on-blade structures are incorporated as the mechanical criteria to design the extension strategies. Wind speed monitoring data at three different onshore and offshore sites around Lake Erie are used to predict the annual wind energy output with different blades. The effects of extension on the dynamic characteristics of blade are analyzed. The results show that the extensive blade significantly increases the annual wind energy production (up to 20% to 30%) with different blade extension strategies. It, therefore, has the potential to significantly boost wind energy production for utility-scale wind turbines located at sites with low-class wind resource. [ABSTRACT FROM AUTHOR]

This paper presents the effect of the tip shape of a wind turbine blade on aerodynamic forces, including the effects of separation, transition and stall. A National Renewable Energy Laboratory (NREL) Phase-VI wind turbine blade was used, in which the shape of the tip was modified to a pointed tip. Computational fluid dynamics (CFD) simulations were employed for the analysis and the results were compared with the original NREL blade CFD and experimental data using ANSYS CFX (Ansys Inc., Delaware, PA, USA). To predict the separation and separation-induced transition on both near wall and far away, the shear-stress-transport (SST) Gamma-Theta turbulent model was used. The stall onset of a 20° angle of attack and its effects were also analyzed and presented. The value of torque with the pointed tip blade was found to be 3%-8% higher than the original NREL blade showing the benefit of the pointed tip. Normal force coefficient is lower at the tip for the pointed tip blade, which results in lower deformation of the blade. It was found that the pointed-tip blade is more efficient in terms of generating torque than the original NREL Phase-VI blade in the dynamic stall region of 10-15 m/s wind speeds. [ABSTRACT FROM AUTHOR]

Wind turbines installed in cold climate sites accumulate ice on their structures. Icing of the rotor blades reduces turbine power output and increases loads, vibrations, noise, and safety risks due to the potential ice throw. Ice accumulation increases the mass distribution of the blade, while changes in the aerofoil shapes affect its aerodynamic behavior. Thus, the structural and aerodynamic changes due to icing affect the modal behavior of wind turbine blades. In this study, aeroelastic equations of the wind turbine blade vibrations are derived to analyze modal behavior of the Tjaereborg 2 MW wind turbine blade with ice. Structural vibrations of the blade are coupled with a Beddoes-Leishman unsteady attached flow aerodynamics model and the resulting aeroelastic equations are analyzed using the finite element method (FEM). A linearly increasing ice mass distribution is considered from the blade root to half-length and thereafter constant ice mass distribution to the blade tip, as defined by Germanischer Lloyd (GL) for the certification of wind turbines. Both structural and aerodynamic properties of the iced blades are evaluated and used to determine their influence on aeroelastic natural frequencies and damping factors. Blade natural frequencies reduce with ice mass and the amount of reduction in frequencies depends on how the ice mass is distributed along the blade length; but the reduction in damping factors depends on the ice shape. The variations in the natural frequencies of the iced blades with wind velocities are negligible; however, the damping factors change with wind velocity and become negative at some wind velocities. This study shows that the aerodynamic changes in the iced blade can cause violent vibrations within the operating wind velocity range of this turbine. [ABSTRACT FROM AUTHOR]

Blades in strong wind conditions are prone to various failures and damage that is due to the action of random variable amplitude loads. In this study, we analyze the failure of 1.5 MW horizontal axis wind turbine blades. The computational fluid dynamics unsteady calculation method is used to simulate the aerodynamic load distribution on the blade. Fluid–structure coupling methods are applied to calculate the blade stress. The results show that the equivalent stress of the blade is the largest when the azimuth angle is 30°, and the maximum equivalent stress is 20.60 MPa. There are obvious stress peaks in six sections, such as r/R = 0.10 (the span length of blade/the full length of the blade = 0.10). The frequency of damage that is caused by the stress in each area of the blade is determined based on the blade damage. The frequency of gel coat cracking in the blade tips and leaves is 77.78% and 22.22%, respectively, and the frequency of crack occurrence is 87.75%, 10.20% and 2.05%, respectively. By combining the stress concentration area and the damage results, the cause of blade damage is determined, which can replace the traditional inspection methods and improve the inspection efficiency. [ABSTRACT FROM AUTHOR]

Making full use of wind energy can effectively alleviate the global energy shortage and environment contamination problems. Nevertheless, how to significantly improve the performance of the wind turbine airfoil and blade is a crucial issue. As the novel flow control method, the co-flow jet (CFJ) technology is one of the most potential methods to solve this problem. Thus, the effects of the CFJ technology on the performance enhancement of the S809 airfoil and Phase VI wind turbine blade are explored in this study. Furthermore, the effects of the injection location and jet momentum coefficient are studied, and an adaptive jet momentum coefficient strategy of the CFJ technology is proposed. Results demonstrate that the CFJ technology can significantly improve the maximum lift coefficient and maximum corrected lift-to-drag ratio of the S809 airfoil. Moreover, the power coefficient of the Phase VI wind turbine blade at the low tip speed ratio is greatly enhanced as well. In particular, the maximum lift coefficient and maximum corrected lift-to-drag ratio of the typical S809 CFJ airfoil with adaptive Cμ are improved by 119.7% and 36.2%, respectively. The maximum power coefficient of CFJ blade can be increased by 4.5%, and the power coefficient of CFJ blade can be boosted by 226.7% when the tip speed ratio is 1.52. [ABSTRACT FROM AUTHOR]

Leading edge erosion is becoming increasingly important as wind turbine size and rainfall are predicted to increase. Understanding environmental conditions is key for laboratory testing, maintenance schedules and lifetime estimations to be improved, which in turn could reduce costs. This paper uses weather data in conjunction with a rain texture model and wind turbine RPM curve to predict and characterise rain erosion conditions across Ireland during rainfall events in terms of droplet size, temperature, humidity and chemical composition, as well as the relative erosivity, in terms of number of annual impacts and kinetic energy, as well as seasonal variations in these properties. Using a linear regression, the total annual kinetic energy, mean temperature and the mean humidity during impact are mapped geospatially. The results indicate that the west coast of Ireland and elevated regions are more erosive with higher kinetic energy. During rain events, northern regions tend to have lower temperatures and lower humidities and mountainous regions have lower temperatures and higher humidities. Irish rain has high levels of sea salt, and in recent years, only a slightly acidic pH. Most erosion likely occurs during winters with frequent rain infused with salt due to increased winds. After this analysis, it is concluded that Ireland's largest wind park (Galway) is placed in a moderate-highly erosive environment and that RET protocols should be revisited. [ABSTRACT FROM AUTHOR]

In the projects Smartblades and Smartblades 2 a full-scale 20 m rotor blade for the NREL CART3 wind turbine was designed, built and tested. The rotor blade was intended to have a strong bending–torsion coupling. By means of the experiments, the proof for the technology in question was supposed to be provided. The experimental work was accompanied by simulations. The aim of the paper was to describe and publish a reference finite element model for the 20 m rotor blade. The validation procedure is presented, as are the modelling strategy and the limitations of the model. The finite element model is created using quadratic finite shell elements and quadratic solid elements. Different data sets were used for the validation. First, the data of static test bench experiments were used. The validation comprised the comparison of global displacement and local strain measurements for various flap and edge bending tests and for torsion unit loading tests. Second, the blades' eigenfrequencies and eigenvectors in clamped and free–free scenarios were used for validation. Third, the mass distributions of the finite element and real blade were investigated. The paper provides the evaluated experimental data, and all analysed scenarios and the corresponding finite element models in Abaqus, Ansys and Nastran and formats as a reference dataset. Dataset: 10.5281/zenodo.3628356 Dataset License: CC-BY [ABSTRACT FROM AUTHOR]

Leading-edge erosion at wind turbine blades cause a loss in profit for wind farm owners, in particular offshore. The characterization of the rain erosion environmental load at wind turbine blades is based on the long-term rain rate and wind speed observations at 10-minute resolutions at coastal stations around the North Sea, Baltic Sea, and inland. It is assumed that an IEA Wind 15 MW turbine is installed at each station. The leading-edge lifetime is found to increase from the South to the North along the German and Danish North Sea coastline from 1.4 to 2.8 years. In the Danish and German Baltic Sea, the lifetime in the West is shorter (~2 years) than further East (~3 to 4 years). It is recommended to use a time series of 10 years or longer because shorter time series most likely will cause an overestimation of the lifetime. The loss in profit due to leading-edge erosion can potentially be reduced by ~70% using the erosion-safe mode, i.e., reduce the tip speed during heavy rain events, to reduce blade erosion, aerodynamic loss, repair costs, and downtime during repair. The aerodynamic loss for the 18 stations is on average 0.46% of the annual energy production. [ABSTRACT FROM AUTHOR]

Interior and exterior wind turbine blade inspections are necessary to extend the lifetime of wind turbine generators. The use of unmanned vehicles is an alternative to exterior wind turbine blade inspections performed by technicians that require the use of cranes and ropes. Interior wind turbine blade inspections are even more challenging due to the confined spaces, lack of illumination, and the presence of potentially harmful internal structural components. Additionally, the cost of manned interior wind turbine blade inspections is a major limiting factor. This paper analyses all aspects of the viability of using manually controlled or autonomous aerial vehicles for interior wind turbine blade inspections. We discuss why the size, weight, and flight time of a vehicle, in addition to the structure of the wind turbine blade, are the main limiting factors in performing internal blade inspections. We also describe the design issues that must be considered to provide autonomy to unmanned vehicles and the control system, the sensors that can be used, and introduce some of the algorithms for localization, obstacle avoidance and path planning that are best suited for the task. Lastly, we briefly describe which non-destructive test instrumentation can be used for the purpose. [ABSTRACT FROM AUTHOR]

For a wind turbine to extract as much energy as possible from the wind, blade geometry optimization to maximize the aerodynamic performance is important. Blade design optimization includes linearizing the blade chord and twist distribution for practical manufacturing. As blade linearization changes the blade geometry, it also affects the aerodynamic performance and load characteristics of the wind turbine rotor. Therefore, it is necessary to understand the effects of the design parameters used in linearization. In this study, the effects of these parameters on the aerodynamic performance of a wind turbine blade were examined. In addition, an optimization algorithm for linearization and an objective function that applies multiple tip speed ratios to optimize the aerodynamic efficiency were developed. The analysis revealed that increasing the chord length and chord profile slope improves the aerodynamic efficiency at low wind speeds but lowers it at high wind speeds, and that the twist profile mainly affects the behaviour at low wind speeds, while its effect on the aerodynamic performance at high wind speeds is not significant. When the blade geometry was optimized by applying the linearization parameter ranges obtained from the analysis, blade geometry with improved aerodynamic efficiency at all wind speeds below the rated wind speed was derived. [ABSTRACT FROM AUTHOR]

The flow control over the blades of a small horizontal-axis wind turbine (HAWT) model using a dielectric barrier discharge plasma actuator (DBD-PA) was studied based on large-eddy simulations. The numerical simulations were performed with a high-resolution computational method, and the effects of the DBD-PA on the flow fields around the blades were modeled as a spatial body force distribution. The DBD-PA was installed at the leading edge of the blades, and its impacts on the flow fields and axial torque generation were discussed. The increase in the ratios of the computed, cycle-averaged axial torque reasonably agreed with that of the available experimental data. In addition, the computed results presented a maximum of 19% increase in the cycle-averaged axial torque generation by modulating the operating parameters of the DBD-PA because of the suppression of the leading edge separation when the blade's effective angles of attack were relatively high. Thus, the suppression of the leading edge separation by flow control can lead to a delay in the breakdown of the tip vortex as a secondary effect. [ABSTRACT FROM AUTHOR]

Wind turbine blades are constantly submitted to different types of particles such as dirt, ice, etc., as well as all the different environmental parameters that affect the behaviour and efficiency of the energy generation system. These parameters can cause faults to the wind turbine blades, modifying their behaviour due, for example, to the turbulence. A new method is presented in this paper based on cross-correlations to determine the presence of delamination in the blades. The experiments were conducted in two real wind turbine blades to analyse the fault and non-fault blades using ultrasonic guided waves. Finally, the energy analysis of the signal based on wavelet transforms allowed to determine energies abrupt changes in the correlation of the signals and to locate the faults. [ABSTRACT FROM AUTHOR]

In order to solve the problem of icing on the surface of wind turbine blade, a heating system that includes a carbon fiber net (CFN) and power cables is proposed recently. When lightning strikes at the blade with a de-icing heating system, the blade and its heating system are more easily damaged due to the overvoltage between the lightning protection system (LPS) of the blade and the heating system. In this paper, the models of a wind turbine blade with the de-icing heating system are established by Alternative Transients Program/Electromagnetic Transients Program (ATP–EMTP) and the accuracy of models is verified through an experiment. With these models, the influence of lightning current, surge protective devices (SPDs) and earthing resistance of wind turbine are analyzed by calculating the voltage between the down-conductor of the LPS and the heating system. The results show that the voltage is positively correlated with lightning current amplitude and negatively correlated with the front time of lightning current. SPDs are quite useful to reduce the voltage, and an optimal installation scheme of SPDs is obtained by simulation. It is noted that voltage decreases slightly with the increasing earthing resistance with the optimal installation scheme of SPDs. [ABSTRACT FROM AUTHOR]

The present study scrutinized the impacts of terrain-induced turbulence on wind turbine blades, examining measurement data regarding wind conditions and the strains of wind turbine blades. Furthermore, we performed a high-resolution large-eddy simulation (LES) and identified the three-dimensional airflow structures of terrain-induced turbulence. Based on the LES results, we defined the Uchida-Kawashima Scale_1 (the U-K scale_1), which is a turbulence evaluation index, and clarified the existence of the terrain-induced turbulence quantitatively. The threshold value of the U-K scale_1 was determined as 0.2, and this index was confirmed to not be dependent on the inflow profile, the influence of the horizontal grid resolution, and the influence of the computed azimuth. In addition, we defined the Uchida-Kawashima Scale_2 (the U-K scale_2), which is a fatigue damage evaluation index based on the measurement data and the design value obtained by DNV GL's Bladed. DNV GL (Det Norske Veritas Germanischer Lloyed) is a third party certification body in Norway, and Bladed has been the industry standard aero-elastic wind turbine modeling software. Using the U-K scale_2, the following results were revealed: the U-K scale_2 was 0.86 < 1.0 (within the designed value) in the case of northerly wind, and the U-K scale_2 was 1.60 > 1.0 (exceeding the designed value) in the case of easterly wind. As a result, it was revealed that the blades of the target wind turbine were directly and strongly affected by terrain-induced turbulence when easterly winds occurred. [ABSTRACT FROM AUTHOR]

This paper proposes a strain prediction method for wind turbine blades using genetic algorithm back propagation neural networks (GA-BPNNs) with applied loads, loading positions, and displacement as inputs, and the study can be used to provide more data for the wind turbine blades' health assessment and life prediction. Among all parameters to be tested in full-scale static testing of wind turbine blades, strain is very important. The correlation between the blade strain and the applied loads, loading position, displacement, etc., is non-linear, and the number of input variables is too much, thus the calculation and prediction of the blade strain are very complex and difficult. Moreover, the number of measuring points on the blade is limited, so the full-scale blade static test cannot usually provide enough data and information for the improvement of the blade design. As a result of these concerns, this paper studies strain prediction methods for full-scale blade static testing by introducing GA-BPNN. The accuracy and usability of the GA-BPNN prediction model was verified by the comparison with BPNN model and the FEA results. The results show that BPNN can be effectively used to predict the strain of unmeasured points of wind turbine blades. [ABSTRACT FROM AUTHOR]

A commercial 43 m wind turbine blade was tested under static loads. During these tests, loads, displacements, and local strains were recorded. In this work, the blade was modeled using the finite element method. Both a segment of the spar structure and the full-scale blade were modeled. In both cases, conventional outer mold layer shell and layered solid models were created by means of an in-house developed software tool. First, the boundary conditions and settings for modeling the tests were explored. Next, the behavior of a spar segment under different modeling methods was investigated. Finally, the full-scale blade tests were conducted. The resulting displacements and longitudinal and transverse strains were investigated. It was found that for the considered load case, the differences between the shell and solid models are limited. Thus, it is concluded that the shell representation is sufficiently accurate. [ABSTRACT FROM AUTHOR]