Offshore Wind Turbine Tower Research Articles

Dynamic Analysis of Fixed Offshore Structures for Wind Turbines

Offshore wind power presents itself as an alternative for complementing and diversifying the Brazilian energy matrix. In this context, fixed jacket-type platforms, widely used by the oil industry, are alternatives for supporting offshore wind turbine towers. However, the unique characteristics of these structures, such as their large dimensions, high centers of mass, and eccentricities of assemblies, as well as the random nature of the loads acting simultaneously on the structure, such as ocean waves, winds, and currents, are challenging components for the engineering of structures built in the marine environment. This article presents some of the main computational models for dynamic structural analysis of fixed offshore wind turbines. In the applied methodology, the sea state is modeled based on second-order Stokes wave theory, where fluid kinematics are calculated from the analysis of random waves in the frequency domain, using the Pierson-Moskowitz spectrum. The aeroelastic-dynamic forces and interactions acting above the free surface were simplified through the adoption of values prescribed in the literature. Finally, structural analysis is carried out using the finite element method, with the jacket bars modeled using plane frame elements. The results obtained in terms of dynamic properties, as well as structural responses, were compared with those extracted from recent works, thus confirming the validity of the chosen methods and consolidating the results for the development of future work.

Assessment of typhoon-induced wind and wave effects on fatigue crack growth life in offshore wind turbines

ABSTRACT Fatigue and structural failures in OWT towers are common due to sustained aerodynamic and wave loads. This study predicts the remaining service life of 2.1MW jacket-type Offshore Wind Turbine (OWT) towers, focusing on fatigue crack growth life (FCGL). Using one-way fluid-structure interaction (FSI) simulations with Typhoon "Muifa" parameters, it analyzes stress under wind, wave, and current effects. FNK theory and linear elastic fracture mechanics are applied to calculate FCGL under various loads. The results indicate that the participation of waves and currents significantly affects the stress distribution in both the tower and the tower frame. During the crack propagation process, cracks initially propagate along the thickness direction and then extend along a straight path after penetrating the thickness. Under typhoon conditions, waves and currents cause a significant reduction in the FCGL of the tower, decreasing from 2.46 years to 1.48 years numerically.

Strain response prediction of offshore wind turbine tower under free vibration

Strain monitoring of critical locations in offshore wind turbine tower is essential for fatigue life prediction and safe operation of wind turbine. This paper theoretically analyses the feasibility of predicting tower strain under free vibration using the modal superposition method. A finite element numerical model of the tower is established, and the displacement mode and strain mode parameters of the tower are extracted. The initial displacement and strain of the tower at cut-out wind speed are analyzed, and the first three modal coordinate of the tower are calculated using test points of displacement or strain separately. Subsequently, the full field strain of the tower is predicted using the modal superposition method. Comparative results demonstrate higher accuracy in modal coordinate values calculated using test points of displacement, and the accuracy and errors of strain prediction using different numbers of test points are compared, emphasizing the crucial role of selecting optimal positions and numbers of test points in improving prediction accuracy.

A new shape reconstruction method for monitoring the large deformations of offshore wind turbine towers

Offshore wind turbine (OWT) upsizing has become an inevitable trend. Compared with small OWTs, large OWT rotors exert greater horizontal loads and bending moments on the tower. These factors make a large OWT tower more prone to geometric nonlinear deformations, which can affect the normal operation of a wind turbine and even lead to damage to the wind turbine tower. Therefore, monitoring the deformation of large OWT towers is necessary. Shape sensing is a technique that uses surface strains to reconstruct deformed shapes. Currently, there is a lack of effective methods for geometric nonlinearity deformation shape sensing. In addition, the tower of OWT is a variable cross-section structure. The influence of varying cross-sections further increases the difficulty of developing a large deformation reconstruction algorithm. To solve this problem, this paper proposes a new method called rotation angle approximation (RAA). This method establishes a least-squares error functional using analytic curvature and section curvature. The rotation angles of the tower axis are obtained via this function. The deformed shape is then predicted via the boundary conditions and the rotation angles along the tower axis. Numerical simulations demonstrated this method can accurately predict the large deformations of a tower under different load conditions.

Structural Design and Research of Offshore Wind Turbine Towers

The structural design and research of offshore wind turbine tower need to involve knowledge and technology in many fields, such as mechanical engineering, material science, fluid mechanics and so on. Through the research and optimization of tower structure, it can promote the development of related industries and improve the technical level and competitiveness of the whole industrial chain. The structural design and research of offshore wind turbine tower has important practical significance and application value. Through in-depth research and optimization of design, the performance and reliability of offshore wind turbines can be improved, and the rapid development of offshore wind power technology can be promoted.

Effects of carbon nanotubes and carbon fibers on the properties of ultra-high performance concrete for offshore wind power generation

Ultra-high performance concrete (UHPC), as one of the most eye-catching building materials, has been the subject of extensive research by scholars. On this basis, to expand the application of UHPC for offshore wind turbine towers in complex marine environments, three different fiber materials - copper-plated microfibre steel fibers, carbon fibers, and carbon nanotubes (CNTs) - have been selected for the study of the possibilities of further improving the mechanical properties of UHPC. This study focused on understanding the impact of various fiber combinations and dosages on the flowability, compressive strength, flexural strength, and tensile strength of UHPC. Our findings indicate that carbon fiber, when present at a concentration of up to 0.5%, the effect on the fluidity of UHPC is only about 1.05%. However, the addition of CNTs significantly diminishes the flowability of UHPC, with a consistent decrease observed as the CNT content increases. Notably, when carbon fiber and CNTs are used in combination, the maximum reduction in flowability reaches 7.8%. Furthermore, as the dosage of these fibers increases, the compressive strength, flexural strength, and tensile strength of UHPC all demonstrate a positive trend of improvement. It is observed that the optimal performance is achieved when both carbon fiber and CNTs are present. In particular, carbon fiber exhibits a more profound impact on enhancing compressive strength and flexural strength, when carbon fibers were doped by volume at 0.5%, the compressive and flexural strengths were increased by 6.7% and 11.7%, respectively, compared to the control group, while carbon nanotubes increased the tensile strength by 7.4% at lower dosage. These findings highlight the potential of fiber combinations to optimize UHPC’s mechanical properties for various engineering applications..

Multi-objective parameter optimization of large-scale offshore wind Turbine's tower based on data-driven model with deep learning and machine learning methods

The tower plays a crucial role in wind turbine systems. However, the design and optimization of configuration parameters have traditionally been lacking in intelligent methods. This study proposes a multi-objective parameter optimization framework that incorporates artificial intelligence models. Specifically, the diameters and thicknesses of the tower are the design parameters that strongly influence two conflicting optimization objectives: mass and top deflection. The nonlinear relationship between these parameters is predicted using surrogate models, such as the Convolutional Neural Network (CNN), Back-propagation Neural Network (BPNN), and Support Vector Machine (SVM), which serve as optimization functions. Additionally, the solutions must meet the requirements for frequency, stress, and buckling. In this study, two reference wind turbines, namely, IEA-15-240 and IEA-22-280, are selected as case studies, and the open-source software WISDEM is utilized to construct the training and testing datasets. Bayesian optimization is used to fine-tune the hyperparameters. Results show that the CNN model outperforms others with larger datasets. Leveraging Deep Learning in the design of offshore wind turbines can significantly reduce mass and deflection while maintaining integrity and performance.

Vibration-based FE-model updating for strain history estimation of a 3MW offshore wind turbine tower

Vibration-based FE-model updating for strain history estimation of a 3MW offshore wind turbine tower

Improved fatigue life of floating offshore wind turbine towers with tuned mass damper inerters (TMDIs)

Improved fatigue life of floating offshore wind turbine towers with tuned mass damper inerters (TMDIs)

Data driven damping separation method for the Mega-offshore wind turbine tower

This study proposes a novel damping separation method based on operating state-measured data collected from a 6.7 MW offshore wind turbine tower to provide various damping ratios caused by different loads. First, the operating frequencies and total damping ratios for various operating states are identified using the dynamic responses under normal operating conditions. Subsequently, the natural and harmonic frequencies caused by the rotation of the blades are distinguished using rotor speed data and the Campbell diagram. Finally, to determine the various damping ratios of different modal orders of offshore wind turbines under multiple load conditions using only actual response data, a new damping equation based on different damping sources is proposed. Filtering strategies for total damping ratios corresponding to different damping sources with varying vibration amplitudes and wind speed thresholds were proposed. The outlier elimination method was introduced to remove error-scattered points, and the average value calculation was used to identify various damping ratios. The actual measured data of a 6.7 MW offshore wind turbine tower was studied, and the results show that the proposed method can effectively separate various damping ratios.

Study on Dynamic Response Characteristics of Offshore Floating Wind Turbine Pitch System

Due to its special working conditions, offshore wind turbine will bear large direct and indirect loads under the combined action of air flow and wave flow. In this paper, a variable pitch system composed of variablepitch motorand variable pitch bearing is improved, and the characteristics of system's bending moment, torque, vibration and other physical quantities under the action of multiple physical loads are verified, and the mechanical response characteristics of floating wind turbine under the control of unified variable pitch and independent variable pitch are studied under the running conditions at sea. The results show that mechanical structure of uniform pitch is compared with that of independent pitch, the independent variable pitch structure can effectively reduce the mean oscillation value of wind turbine tower in the parallel direction of air flow by optimizing control strategy, and reduce the thrust at the hub of wind turbine and the bending moment at the root of tower, but increase the vibration frequency and fatigue load of offshore wind turbine tower along parallel direction of air flow. Reduce the fatigue life of equipment. The research results can be used as a reference to reduce the variable pitch control and vibration suppression of offshore wind turbines and improve the reliability of wind turbines.

Effect of gap size on flange face corrosion

AbstractBolted flanged joints play a critical role in offshore wind turbine tower structures, serving as integral components that connect various sections of the tower. This research study employs electrochemical techniques to investigate the effect of gap dimensions, which determine the crevice gap thickness and crevice depth, on corrosion behavior of 321 stainless steel flange sample plates in a 3.5 wt% NaCl solution at 50°C. Gaskets are used in this study to create gaps between two flange surfaces. A novel fixture is utilized to simulate the applied stress on the gasket, fluid flow within the fixture, and the geometric aspects of the gasket and flange. The findings reveal that increasing the gap thickness from 1.58 to 6.35 mm results in a rise in the general corrosion rate of the flange surface from 0.09 to 1.03 mm y−1, and crevice corrosion initiation time increases from 0.23 to 3.12 h. Furthermore, reducing the crevice depth (d) from 7.49 to 0 mm leads to a decrease in the general corrosion rate from 0.09 mm y−1 to 0.04 µm y−1, and cases with d = 3.81 and d = 0 mm show no observable crevice corrosion after potentiostatic tests.

Vibration Mitigation Using 3D-PSTMD for the Offshore Wind Turbine Considering Self-Excitation Behaviors

The self-excitation behaviors can be triggered by the blade rotation of the wind turbine. To mitigate the excessive vibration of offshore wind turbine (OWT) tower under this self-excitation addition with wind–wave loadings, a three-dimensional prestressed TMD (3D-PSTMD) is extended in this study. First, based on the Lagrange equation, the analytical formulations of 1P (rotor rotational speed) and 3P (blade passing frequency) loads from self-excitations are deduced, and more factors under real operational conditions of the OWT are further analyzed using theoretical derivation and numerical simulation. Then, structural aero-hydrodynamic loadings are modelled, and self-resonance phenomenon of the uncontrolled OWT and resonance dissipation capability of 3D-PSTMD are discussed at startup–operation–shutdown state. Finally, the energy harvesting competence of 3D-PSTMD is quantitatively calculated via the classical Wilson-[Formula: see text] algorithm under self-excitations with wind–wave loadings. Results indicate that this dashpot is remarkably able to mitigate the structural resonance responses over 61.3% and 40.5% respectively when under the 1P and 3P loadings, and it can also effectively reduce the bi-directionally horizontal vibrations of OWT under aero-hydrodynamic loadings.

Extreme load extrapolation and long-term fatigue assessment of offshore wind turbine tower based on monitoring data

Extreme load and fatigue damage are important parameters in the structural design of offshore wind turbines (OWTs). The purpose of this study is to obtain extreme loads and long-term fatigue damage assessment of OWT structures based on measured data. In the present study, a utility-scale OWT was monitored with a dynamic response monitoring system and long-term strains of the OWT tower were collected. Based on the monitoring strain and the operational conditions of the OWT, the load and fatigue characteristics of the OWT tower were discussed. Furthermore, statistical extrapolation of the extreme load of the OWT tower was performed and the applicability of different statistical extrapolation methods was studied. The results indicate that the same probability distribution model does not apply to all wind speeds. The maximum extreme load is extrapolated in the vicinity of the rated wind speed. Finally, the relationship between short-term fatigue damage and long-term fatigue damage of the OWT structure was discussed. Superimposing fatigue from a short calculation period underestimates the long-term fatigue of OWT structures due to significant calculation period impact. Therefore, an evaluation method for OWT structures' long-term fatigue was established to improve the accuracy of long-term fatigue calculation by superimposing short calculation periods.

An Overview on Structural Health Monitoring and Fault Diagnosis of Offshore Wind Turbine Support Structures

The service environment of offshore wind turbine (OWT) support structures is harsh, and it is extremely difficult to replace these structures during their operational lifespan, making their failure a catastrophic event. The structural health monitoring (SHM) of OWT support structures is a crucial aspect of operational maintenance for OWT support structures, aiming to mitigate significant financial losses. This paper systematically summarizes the current monitoring methods and technologies for OWT support structures, including towers and foundations. Through the review of monitoring content and the evolution of monitoring techniques for supporting structures, it delves deeper into the challenges faced by wind turbine monitoring and highlights potential avenues for future development. Then, the current damage identification techniques for OWT towers and foundations are analyzed, exploring various methods including model-based, vibration-based, artificial intelligence and hybrid fault diagnosis methods. The article also examines the advantages and disadvantages of each approach and outlines potential future directions for research and development in this field. Furthermore, it delves into the current damage identification techniques for OWT towers and foundations, discussing prevalent challenges and future directions in this domain. This status review can provide reference and guidance for the monitoring design of OWT support structures, and provide support for the fault diagnosis of OWT support structures.

Optimizing mechanical properties and corrosion resistance in core‐shell nanofiber epoxy self‐healing coatings: Impact of shell material variation

AbstractShell materials play significant impact on corrosion resistance and mechanical properties on self‐healing coating of composite with core‐shell nanofiber. In this paper, three promising shell materials were investigated to optimize the performance of self‐healing coating. Self‐healing core‐shell nanofibers with different shell materials were prepared with coaxial electrospinning. The resulting nanofibers were used to prepare self‐healing corrosion resistance coating. The tensile test revealed a notable enhancement in the tensile strength of PA6 core‐shell nanofiber epoxy composite coatings compared with the epoxy coating, demonstrating increase of 26.92%. Friction and wear test indicated reductions in the friction coefficients of PAN, PVDF, and PA6 core‐shell nanofibers by 13.82%, 12.44%, and 26.27%, respectively. The self‐healing and anti‐corrosion abilities were evaluated through electrochemical impedance spectroscopy (EIS) test. All three coatings exhibited exceptional self‐healing efficiencies exceeding 90%, highlighting the substantial potential of the chosen shell materials as nanocontainers for self‐healing agent. Results indicate that the nanofibers with PA6 as shell material can achieve the best enhancement performance, which has a greater potential for the corrosion protection and long‐lasting use of offshore wind turbine tower coatings.Highlights Optimizing coating performance by screening coaxial nanofibers for shell materials Shell material can improve the tensile strength of coating up to 26.92% Friction coefficient of PA6 nanofiber coating was about 15% lower than PAN and PVDF All three coatings exhibited exceptional self‐healing efficiencies exceeding 90%

Coupling multi-physics models to corrosion fatigue prognosis of high-strength bolts in floating offshore wind turbine towers

Floating wind offshore turbines (FOWTs) tap into the immense Aeolian resource in deep-water oceans. The turbine structure, especially in ring-flange (RF) connections, are highly prone to corrosion fatigue (C-F) deterioration due to the combination of strong wind-wave loads, structural flexibility, and high corrosivity. This study provides innovative insights into the C-F deterioration of FOWT towers by integrating site-specific data, material test results, multi-physics simulations, and deterioration models. A probabilistic C-F (PCF) evolution model is tailored for bolts in RF connections, accounting for multiple failure modes. Concurrently, the corrosion test data are adopted to estimate the corrosion rate from the site-specific ambient conditions, including the temperature, humidity and airborne salinity. The result indicates a strong correlation between wind-wave spatial distribution and C-F damage, for which the critical bolt aligns with high-velocity winds. Meanwhile, the bolt deterioration is accelerated under high corrosivity, risking premature failures. Moreover, compared with the traditional fixed-bottom foundation, the floating platform amplifies the tower dynamics in both mean value and variation, which in turns escalate stress ranges in bolts. The findings underscore the importance of monitoring C-F deterioration in FOWT structures and highlight the potential of condition-based maintenance.

Vibration-based health monitoring of the offshore wind turbine tower using machine learning with Bayesian optimisation

Structural health monitoring of towers for offshore wind turbines (OWTs) is critical because they serve as support structures. Although the modal parameters of the tower can be identified through operational modal analysis, evaluating the realistic characteristics of structures is challenging, and the modal parameters are susceptible to fluctuations owing to shifting environmental and operational conditions (EOCs). In this study, we aim to improve the vibration-based structural health monitoring strategy for monitoring OWT towers. Remote-sensing products from ERA5, which provide information regarding the marine state, are used to extend the data source. Machine learning (ML) with Bayesian optimisation is utilised to minimise the effects of EOCs on modal parameters. We demonstrate that the modal parameters of the tower are significantly influenced by the EOCs by applying the developed approach to an offshore wind turbine. Moreover, the effects of the EOCs on the modal parameters are minimised by applying ML models with Bayesian optimisation. A comparison between the monitoring divided into different operating conditions and the monitoring of all operating conditions indicate that there is minimal room for performance improvement of ML models with thorough condition segmentation. Consequently, employing global models directly is preferred in the present application environment.

On controlling, Vibration Performance and Energy Transfer of an Offshore Wind Turbine Tower System via PPF Controller

In this paper, we focus on the control, energy transfer, and vibration performance under multi mixed excitations for the offshore wind turbine tower (OWTT) system. For reducing the controlled system oscillations, the positive position feedback (PPF) controller is applied. The energy transfers occur in the system of wind turbine by adding the PPF controller to the system equations. With the help of the phase plane approach, frequency response equations, and Poincare maps, the bifurcation and stability at worst resonance cases are sought and investigated. The vibration behaviors are studied numerically at different parameters values for the wind turbine system. Additionally, the response and numerical outcomes are examined, also, the approach of multiple scales is used to establish the approximate solutions of the wind turbine-controlled system. Besides that, MAPLE and MATLAB algorithms are used to implement the numerical results and compare analytical solutions with numerical behavior. The results also be compared to previous research that has been published.

Sustainability of corrosion protection for offshore wind turbine towers

When coatings industries have ambitions to develop more sustainable products it is important to know what path to follow. Quantitative evaluations in the form of Life Cycle Assessment (LCA) offers guidance for sustainability directions. The direction will depend on the type of coating. This work analyses sustainability performance of protective coatings, using the coating of an offshore wind turbine tower as a case. All steps in the manufacturing are assessed and the relevant environmental impacts are evaluated along the life cycle of the turbine tower. The assessment shows that the vast majority of the impacts, including climate change, originate from manufacturing of the steel. Therefore the durability of the coating system to protect the steel and prolong the lifetime, minimizing the need for repair, etc. should be the main priority for a sustainable direction. The coating system must keep the steel structures corrosion free for at least as long as the designed lifetime, as it is much more costly in terms of environmental impacts to repair or replace steel than to protect it properly from the start. When the protection is secured, the sustainable development path from the present situation where thermal sprayed metal (TSM) is used for galvanic protection of the wind turbine tower, will be to develop:-Coating systems where toxic substances are substituted by less toxic or non-toxic substances.-Coating systems where the thermal sprayed metal (TSM) layer is substituted by zinc-rich epoxy or Zinc silicate coatings.-Coating systems where the organic solvents are substituted by water.-Coating systems which would make it possible to reduce the amount of steel used.-Coating systems where the organic binder material is substituted with alternatives with lower carbon footprint-Ease of recycling the structure material for reuse in new structures.