Local Scour Mechanisms and Prediction Methods Around Offshore Wind Turbine Foundations:Insights and Future Directions

Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability,driven by hydrodynamic forces.While research has made strides in comprehending scouring mechanisms,notable complexities persist,specifically with newer foundation types.Addressing these limitations is vital for advancing our understanding of scour mechanisms and for improving mitigation strategies in offshore wind energy development.This review synthesizes current findings on local scour across various offshore foundations,encompassing field observations,data-driven approaches,turbulence-sediment interactions,scour evolution processes,influencing factors,and numerical model advancements.The objective is to enrich our understanding of local scour mechanisms.In addition,future research directions are outlined,including the development of robust arti-ficial intelligence models for accurate predictions,the exploration of vortex structure characteristics,and the refinement of numerical models to strengthen prediction capabilities while minimizing computational efforts.

Aero-Hydro-Elastic-Servo Modeling and Dynamic Response Analysis of A Monopile Offshore Wind Turbine Under Different Operating Scenarios

This paper constructs a coupled aero-hydro-elastic-servo simulation framework for a monopile offshore wind turbine(OWT).In this framework,a detailed multi-body dynamics model of the monopile OWT including the gearbox,blades,tower and other components(nacelle,hub,bedplate,etc.)has been explicitly established.The effects of pile−soil interaction,controller and operational conditions on the turbine dynamic responses are studied systematically in time domain and frequency domain.The results show that(1)a comprehensive drivetrain model has the capability to provide a more precise representation of the complex dynamic characteristics exhibited by drivetrain components,which can be used as the basis for further study on the dynamic characteristics of the drivetrain.(2)The pile−soil interaction can influence the wind turbine dynamic responses,particularly under the parked condition.(3)The effect of the pile−soil interaction on tower responses is more significant than that on blade responses.(4)The use of the controller can substantially affect the rotor characteristics,which in turn influences the turbine dynamic responses.(5)The tower and blade displacements under the operational condition are much larger than those under the parked condition.The model and methodology presented in this study demonstrate potential for examining complex dynamic behaviors of the monopile OWTs.To ensure accuracy and precision,it is imperative to construct a detailed model of the wind turbine system,while also taking into account simulation efficiency.

Vibration attenuation performance of wind turbine tower using a prestressed tuned mass damper under seismic excitation

With the rapid development of large megawatt wind turbines,the operation environment of wind turbine towers(WTTs)has become increasingly complex.In particular,seismic excitation can create a resonance response and cause excessive vibration of the WTT.To investigate the vibration attenuation performance of the WTT under seismic excitations,a novel passive vibration control device,called a prestressed tuned mass damper(PS-TMD),is presented in this study.First,a mathematical model is established based on structural dynamics under seismic excitation.Then,the mathematical analytical expression of the dynamic coefficient is deduced,and the parameter design method is obtained by system tuning optimization.Next,based on a theoretical analysis and parameter design,the numerical results showed that the PS-TMD was able to effectively mitigate the resonance under the harmonic basal acceleration.Finally,the time-history analysis method is used to verify the effectiveness of the traditional pendulum tuned mass damper(PTMD)and the novel PS-TMD device,and the results indicate that the vibration attenuation performance of the PS-TMD is better than the PTMD.In addition,the PS-TMD avoids the nonlinear effect due to the large oscillation angle,and has the potential to dissipate hysteretic energy under seismic excitation.

Comparisons of Wave Force Model Effects on the Structural Responses and Fatigue Loads of a Semi-Submersible Floating Wind Turbine

The selection of wave force models will significantly impact the structural responses of floating wind turbines.In this study,comparisons of wave force model effects on the structural responses and fatigue loads of a semi-submersible floating wind turbine(SFWT)were conducted.Simulations were performed by employing the Morison equation(ME)with linear or second-order wave kinematics and potential flow theory(PFT)with first-or second-order wave forces.A comparison of regular waves,irregular waves,and coupled wind/waves analyses with the experimental data showed that many of the simulation results and experimental data are relatively consistent.However,notable discrepancies are found in the response amplitude operators for platform heave,tower base bending moment,and tension in mooring lines.PFT models give more satisfactory results of heave but more significant discrepan-cies in tower base bending moment than the ME models.In irregular wave analyses,low-frequency resonances were captured by PFT models with second-order difference-frequency terms,and high-frequency resonances were captured by the ME models or PFT models with second-order sum-frequency terms.These force models capture the response frequencies but do not reasonably predict the response amplitudes.The coupled wind/waves analyses showed more satisfactory results than the wave-only analyses.However,an important detail to note is that this satisfactory result is based on the overprediction of wind-induced responses.

Semi-supervised surface defect detection of wind turbine blades with YOLOv4

Timely inspection of defects on the surfaces of wind turbine blades can effectively prevent unpredictable accidents.To this end,this study proposes a semi-supervised object-detection network based on You Only Looking Once version 4(YOLOv4).A semi-supervised structure comprising a generative adversarial network(GAN)was designed to overcome the difficulty in obtaining sufficient samples and sample labeling.In a GAN,the generator is realized by an encoder-decoder network,where the backbone of the encoder is YOLOv4 and the decoder comprises inverse convolutional layers.Partial features from the generator are passed to the defect detection network.Deploying several unlabeled images can significantly improve the generalization and recognition capabilities of defect-detection models.The small-scale object detection capacity of the network can be improved by enhancing essential features in the feature map by adding the concurrent spatial and channel squeeze and excitation(scSE)attention module to the three parts of the YOLOv4 network.A balancing improvement was made to the loss function of YOLOv4 to overcome the imbalance problem of the defective species.The results for both the single-and multi-category defect datasets show that the improved model can make good use of the features of the unlabeled images.The accuracy of wind turbine blade defect detection also has a significant advantage over classical object detection algorithms,including faster R-CNN and DETR.

Experimental Study on the Sinking and Leveling of A Large-Capacity Offshore Wind Turbine Five-Bucket Foundation in Sand

As offshore wind farms expand into deeper and farther ocean regions and the unit capacity of offshore wind turbines(OWTs)increases,there is a pressing need for a new foundation structure that can accommodate deep-sea conditions and support large capacities while maintaining economical and safe.To meet this goal of integrated transportation and one-step installation,a novel five-bucket jacket foundation(FBJF),with its suction installation and leveling methods in sand,has been proposed,analyzed and experimentally studied.First,seepage failure experiments of the FBJF at various depths were conducted,and a formula for calculating the critical suction of seepage failure suitable for the FBJF in sand was chosen and recommended for use with a range of values for the permeability coefficient ratio.Second,through leveling experiments of the FBJF at different depths,the maximum adjustable leveling angle during the sinking process was defined using seepage failure and the adjustable leveling angle of the foundation as control criteria.Various leveling control strategies were proposed and verified.Finally,an automatic sinking and leveling control system for the FBJF was developed and experimentally verified for feasibility.

Research on Leading Edge Erosion and Aerodynamic Characteristics of Wind Turbine Blade Airfoil

The effects of the erosion present on the leading edge of a wind turbine airfoil(DU 96-W-180)on its aerodynamic performances have been investigated numerically in the framework of a SST k–ωturbulence model based on the Reynolds Averaged Navier-Stokes equations(RANS).The results indicate that when sand-induced holes and small pits are involved as leading edge wear features,they have a minimal influence on the lift and drag coefficients of the airfoil.However,if delamination occurs in the same airfoil region,it significantly impacts the lift and resistance characteristics of the airfoil.Specifically,as the angle of attack grows,there is a significant decrease in the lift coefficient accompanied by a sharp increase in the drag coefficient.As wear intensifies,these effects gradually increase.Moreover,the leading edge wear can exacerbate flow separation near the trailing edge suction surface of the airfoil and cause forward displacement of the separation point.

Dynamic Analysis of a 10 MW Floating Offshore Wind Turbine Considering the Tower and Platform Flexibility

Recently,semisubmersible floating offshore wind turbine technologies have received considerable attention.For the coupled simulation of semisubmersible floating offshore wind energy,the platform is usually considered a rigid model,which could affect the calculation accuracy of the dynamic responses.The dynamic responses of a TripleSpar floating offshore wind turbine equipped with a 10 MW offshore wind turbine are discussed herein.The simulation of a floating offshore wind turbine under regular waves,white noise waves,and combined wind-wave conditions is conducted.The effects of the tower and platform flexibility on the motion and force responses of the TripleSpar semisubmersible floating offshore wind turbine are investigated.The results show that the flexibility of the tower and platform can influence the dynamic responses of a TripleSpar semisubmersible floating offshore wind turbine.Considering the flexibility of the tower and platform,the tower and platform pitch motions markedly increased compared with the fully rigid model.Moreover,the force responses,particularly for tower base loads,are considerably influenced by the flexibility of the tower and platform.Thus,the flexibility of the tower and platform for the coupled simulation of floating offshore wind turbines must be appropriately examined.

Influence of Surface Ice Roughness on the Aerodynamic Performance of Wind Turbines

The focus of this research was on the equivalent particle roughness height correction required to account for the presence of ice when determining the performances of wind turbines.In particular,two icing processes(frost ice and clear ice)were examined by combining the FENSAP-ICE and FLUENT analysis tools.The ice type on the blade surfaces was predicted by using a multi-time step method.Accordingly,the influence of variations in icing shape and ice surface roughness on the aerodynamic performance of blades during frost ice formation or clear ice formation was investigated.The results indicate that differences in blade surface roughness and heat flux lead to disparities in both ice formation rate and shape between frost ice and clear ice.Clear ice has a greater impact on aerodynamics compared to frost ice,while frost ice is significantly influenced by the roughness of its icy surface.

Influence of Trailing-Edge Wear on the Vibrational Behavior of Wind Turbine Blades

To study the impact of the trailing-edge wear on the vibrational behavior of wind-turbine blades,unworn blades and trailing-edge worn blades have been assessed through relevant modal tests.According to these experiments,the natural frequencies of trailing-edge worn blades-1,-2,and-3 increase the most in the second to fourth order,thefifth order increases in the middle,and thefirst order increases the least.The damping ratio data indi-cate that,in general,thefirstfive-order damping ratios of trailing-edge worn blades-1 and trailing-edge worn blades-2 are reduced,and thefirstfive-order damping ratios of trailing-edge worn blades-3 are slightly improved.The mode shape diagram shows that the trailing-edge worn blades-1 and-2 have a large swing in the tip and the blade,whereas the second-and third-order vibration shapes of the trailing edge-worn blade-3 tend to be improved.Overall,all these results reveal that the blade’s mass and the wear area are the main fac-tors affecting the vibration characteristics of wind turbine blades.

Optimized Design of Bio-Inspired Wind Turbine Blades

To enhance the aerodynamic performance of wind turbine blades,this study proposes the adoption of a bionic airfoil inspired by the aerodynamic shape of an eagle.Based on the blade element theory,a non-uniform extraction method of blade elements is employed for the optimization design of the considered wind turbine blades.Moreover,Computational Fluid Dynamics(CFD)is used to determine the aerodynamic performances of the eagle airfoil and a NACA2412 airfoil,thereby demonstrating the superior aerodynamic performance of the former.Finally,a mathematical model for optimizing the design of wind turbine blades is introduced and a comparative analysis is conducted with respect to the aerodynamic performances of blades designed using a uniform extraction approach.It is found that the blades designed using non-uniform extraction exhibit better aerodynamic performance.

Zonal Coupling Analysis Method of Seismic Response of Offshore Monopile Wind Turbine

The seismic safety of offshore wind turbines is an important issue that needs to be solved urgently.Based on a unified computing framework,this paper develops a set of seawater-seabed-wind turbine zoning coupling analysis methods.A 5 MW wind turbine and a site analysis model are established,and a seismic wave is selected to analyze the changes in the seismic response of offshore monopile wind turbines under the change of seawater depth,seabed wave velocity and seismic wave incidence angle.The analysis results show that when the seawater increases to a certain depth,the seismic response of the wind turbine increases.The shear wave velocity of the seabed affects the bending moment and displacement at the bottom of the tower.When the angle of incidence increases,the vertical displacement and the acceleration of the top of the tower increase in varying degrees.

Research on the Icing Diagnosis ofWind Turbine Blades Based on FS–XGBoost–EWMA

In winter,wind turbines are susceptible to blade icing,which results in a series of energy losses and safe operation problems.Therefore,blade icing detection has become a top priority.Conventional methods primarily rely on sensor monitoring,which is expensive and has limited applications.Data-driven blade icing detection methods have become feasible with the development of artificial intelligence.However,the data-driven method is plagued by limited training samples and icing samples;therefore,this paper proposes an icing warning strategy based on the combination of feature selection(FS),eXtreme Gradient Boosting(XGBoost)algorithm,and exponentially weighted moving average(EWMA)analysis.In the training phase,FS is performed using correlation analysis to eliminate redundant features,and the XGBoost algorithm is applied to learn the hidden effective information in supervisory control and data acquisition analysis(SCADA)data to build a normal behavior model.In the online monitoring phase,an EWMA analysis is introduced to monitor the abnormal changes in features.A blade icing warning is issued when themonitored features continuously exceed the control limit,and the ambient temperature is below 0℃.This study uses data fromthree icing-affected wind turbines and one normally operating wind turbine for validation.The experimental results reveal that the strategy can promptly predict the icing trend among wind turbines and stably monitor the normally operating wind turbines.

Study on the Relationship between Structural Aspects and Aerodynamic Characteristics of Archimedes Spiral Wind Turbines

A combined experimental and numerical research study is conducted to investigate the complex relationship between the structure and the aerodynamic performances of an Archimedes spiral wind turbine(ASWT).Two ASWTs are considered,a prototypical version and an improved version.It is shown that the latter achieves the best aerodynamic performance when the spread angles at the three sets of blades areα_(1)=30°,α_(2)=55°,α3=60°,respectively and the blade thickness is 4 mm.For a velocity V=10 m/s,a tip speed ratio(TSR)=1.58 and 2,the maximum CP values are 0.223 and 0.263 for the prototypical ASWT and improved ASWT,respectively,and the maximum C_(P) enhancement is 17.93%.For V=10 m/s and TSR=2,the CP values of the prototypical ASWT and improved ASWT are 0.225 and 0.263,respectively,with an aerodynamic performance enhancement of 16.88%.Through mutual verification of the test outcomes and numerical results,it is concluded that the proposed approach can effectively lead to aerodynamic performance improvement.

Impact of Blade-Flapping Vibration on Aerodynamic Characteristics of Wind Turbines under Yaw Conditions

Although the aerodynamic loading of wind turbine blades under various conditions has been widely studied,the radial distribution of load along the blade under various yaw conditions and with blade flapping phenomena is poorly understood.This study aims to investigate the effects of second-order flapwise vibration on the mean and fluctuation characteristics of the torque and axial thrust of wind turbines under yaw conditions using computational fluid dynamics(CFD).In the CFD model,the blades are segmented radially to comprehensively analyze the distribution patterns of torque,axial load,and tangential load.The following results are obtained.(i)After applying flapwise vibration,the torque and axial thrust of wind turbines decrease in relation to those of the rigid model,with significantly increased fluctuations.(ii)Flapwise vibration causes the blades to reciprocate along the axial direction,altering the local angle of attack and velocity of the blades relative to the incoming wind flow.This results in the contraction of the torque region from a circular shape to a complex“gear”shape,which is accompanied by evident oscillations.(iii)Compared to the tangential load,the axial load on the blades is more sensitive to flapwise vibration although both exhibit significantly enhanced fluctuations.This study not only reveals the impact of flapwise vibration on wind turbine blade performance,including the reduction of torque and axial thrust and increased operational fluctuations,but also clarifies the radial distribution patterns of blade aerodynamic characteristics,which is of great significance for optimizing wind turbine blade design and reducing fatigue risks.

Data-Driven Modeling for Wind Turbine Blade Loads Based on Deep Neural Network

Blades are essential components of wind turbines.Reducing their fatigue loads during operation helps to extend their lifespan,but it is difficult to quickly and accurately calculate the fatigue loads of blades.To solve this problem,this paper innovatively designs a data-driven blade load modeling method based on a deep learning framework through mechanism analysis,feature selection,and model construction.In the mechanism analysis part,the generation mechanism of blade loads and the load theoretical calculationmethod based on material damage theory are analyzed,and four measurable operating state parameters related to blade loads are screened;in the feature extraction part,15 characteristic indicators of each screened parameter are extracted in the time and frequency domain,and feature selection is completed through correlation analysis with blade loads to determine the input parameters of data-driven modeling;in the model construction part,a deep neural network based on feedforward and feedback propagation is designed to construct the nonlinear coupling relationship between the unit operating parameter characteristics and blade loads.The results show that the proposed method mines the wind turbine operating state characteristics highly correlated with the blade load,such as the standard deviation of wind speed.The model built using these characteristics has reasonable calculation and fitting capabilities for the blade load and shows a better fitting level for untrained out-of-sample data than the traditional scheme.Based on the mean absolute percentage error calculation,the modeling accuracy of the two blade loads can reach more than 90%and 80%,respectively,providing a good foundation for the subsequent optimization control to suppress the blade load.

Effect of Rigid Pitch Motion on Flexible Vibration Characteristics of a Wind Turbine Blade

Adynamic pitch strategy is usually adopted to improve the aerodynamic performance of the blade of awind turbine.The dynamic pitch motion will affect the linear vibration characteristics of the blade.However,these influences have not been studied in previous research.In this paper,the influences of the rigid pitch motion on the linear vibration characteristics of a wind turbine blade are studied.The blade is described as a rotating cantilever beam with an inherent coupled rigid-flexible vibration,where the rigid pitch motion introduces a parametrically excited vibration to the beam.Partial differential equations governing the nonlinear coupled pitch-bend vibration are proposed using the generalized Hamiltonian principle.Natural vibration characteristics of the inherent coupled rigid-flexible system are analyzed based on the combination of the assumed modes method and the multi-scales method.Effects of static pitch angle,rotating speed,and characteristics of harmonic pitch motion on flexible natural frequencies andmode shapes are discussed.It shows that the pitch amplitude has a dramatic influence on the natural frequencies of the blade,while the effects of pitch frequency and pith phase on natural frequencies are little.

Nonlinear Flap-Wise Vibration Characteristics ofWind Turbine Blades Based onMulti-Scale AnalysisMethod

This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle.We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory(NREL),to research the effects of the nonlinear flap-wise vibration characteristics.The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam,and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first.Then,the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force.Lastly,it is truncated by the Galerkin method and analyzed semi-analytically using the multi-scale analysis method,and numerical simulations are carried out to compare the simulation results of finite elements with the numerical simulation results using Campbell diagram analysis of blade vibration.The results indicated that the rotational speed of the impeller has a significant impact on blade vibration.When the wheel speed of 12.1 rpm and excitation amplitude of 1.23 the maximum displacement amplitude of the blade has increased from 0.72 to 3.16.From the amplitude-frequency curve,it can be seen that the multi-peak characteristic of blade amplitude frequency is under centrifugal nonlinearity.Closed phase trajectories in blade nonlinear vibration,exhibiting periodic motion characteristics,are found through phase diagrams and Poincare section diagrams.

Research on Fatigue Damage Behavior of Main Beam Sub-Structure of Composite Wind Turbine Blade

Given the difficulty in accurately evaluating the fatigue performance of large composite wind turbine blades(referred to as blades),this paper takes the main beam structure of the blade with a rectangular cross-sectionas the simulation object and establishes a composite laminate rectangular beam structure that simultaneouslyincludes the flange,web,and adhesive layer,referred to as the blade main beam sub-structure specimen,throughthe definition of blade sub-structures.This paper examines the progressive damage evolution law of the compositelaminate rectangular beam utilizing an improved 3D Hashin failure criterion,cohesive zone model,B-K failurecriterion,and computer simulation technology.Under static loading,the layup angle of the anti-shear web hasa close relationship with the static load-carrying capacity of the composite laminate rectangular beam;under fatigueloading,the fatigue damage will first occur in the lower flange adhesive area of the whole composite laminaterectangular beam and ultimately result in the fracture failure of the entire structure.These results provide a theoreticalreference and foundation for evaluating and predicting the fatigue performance of the blade main beamstructure and even the full-size blade.

Review of Artificial Neural Networks for Wind Turbine Fatigue Prediction

Wind turbines have emerged as a prominent renewable energy source globally.Efficient monitoring and detection methods are crucial to enhance their operational effectiveness,particularly in identifying fatigue-related issues.This review focuses on leveraging artificial neural networks(ANNs)for wind turbine monitoring and fatigue detection,aiming to provide a valuable reference for researchers in this domain and related areas.Employing various ANN techniques,including General Regression Neural Network(GRNN),Support Vector Machine(SVM),Cuckoo Search Neural Network(CSNN),Backpropagation Neural Network(BPNN),Particle Swarm Optimization Artificial Neural Network(PSO-ANN),Convolutional Neural Network(CNN),and nonlinear autoregressive networks with exogenous inputs(NARX),we investigate the impact of average wind speed on stress transfer function and fatigue damage in wind turbine structures.Our findings indicate significant precision levels exhibited by GRNN and SVM,making them suitable for practical implementation.CSNN demonstrates superiority over BPNN and PSO-ANN in predicting blade fatigue life,showcasing enhanced accuracy,computational speed,precision,and convergence rate towards the global minimum.Furthermore,CNN and NARX models display exceptional accuracy in classification tasks.These results underscore the potential of ANNs in addressing challenges in wind turbine monitoring and fatigue detection.However,it’s important to acknowledge limitations such as data availability and model complexity.Future research should explore integrating real-time data and advanced optimization techniques to improve prediction accuracy and applicability in real-world scenarios.In summary,this review contributes to advancing the understanding of ANNs’efficacy in wind turbine monitoring and fatigue detection,offering insights and methodologies that can inform future research and practical applications in renewable energy systems.