Showing papers on "Turbine blade published in 2023"

An Experimental Study on Adhesion Strength of Offshore Atmospheric Icing on a Wind Turbine Blade Airfoil

Abstract: When wind turbines work in a cold and humid environment, especially offshore condition, ice accretion on the blade surfaces has a negative effect on the aerodynamic performance. In order to remove the ice from the wind turbine blade, the adhesive characteristics of atmospheric icing on the blade surface should be mastered under various conditions. The objective of this study is to evaluate the effects of offshore atmospheric conditions, including wind speeds, ambient temperatures and, especially, the salt contents on ice adhesion strength for wind turbine blades. The experiments were conducted on a NACA0018 blade airfoil under conditions including an ambient temperature of −3 °C~−15 °C, wind speed of 6 m/s~15 m/s and salt content of 1~20 mg/m3. The results showed that salt content was the most important factor affecting the ice adhesion strength, followed by ambient temperature and wind speed. The interactive effect of wind speed and salt content, ambient temperature and salt content were extremely significant. The research can provide a reference for the anti-icing for offshore wind turbines.

Numerical simulations of ice accretion on wind turbine blades: are performance losses due to ice shape or surface roughness?

Abstract: Abstract. Ice accretion on wind turbine blades causes both a change in the shape of its sections and an increase in surface roughness. These lead to degraded aerodynamic performances and lower power output. Here, a high-fidelity multi-step method is presented and applied to simulate a 3 h rime icing event on the National Renewable Energy Laboratory 5 MW wind turbine blade. Five sections belonging to the outer half of the blade were considered. Independent time steps were applied to each blade section to obtain detailed ice shapes. The roughness effect on airfoil performance was included in computational fluid dynamics simulations using an equivalent sand-grain approach. The aerodynamic coefficients of the iced sections were computed considering two different roughness heights and extensions along the blade surface. The power curve before and after the icing event was computed according to the Design Load Case 1.1 of the International Electrotechnical Commission. In the icing event under analysis, the decrease in power output strongly depended on wind speed and, in fact, tip speed ratio. Regarding the different roughness heights and extensions along the blade, power losses were qualitatively similar but significantly different in magnitude despite the well-developed ice shapes. It was found that extended roughness regions in the chordwise direction of the blade can become as detrimental as the ice shape itself.

Investigation of the Mechanical Behavior of a New Generation Wind Turbine Blade Technology

Abstract: 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.

A multiaxial probabilistic fatigue life prediction method for nickel‐based single crystal turbine blade considering mean stress correction

Abstract: Gas turbine blades normally operate under high‐temperatures, extreme pressure, and high‐speed conditions, which leads to complex failure mechanisms and difficulties in fatigue life assessment. Moreover, due to the randomness of manufacturing errors, working loads, and material properties, the low cycle fatigue (LCF) life normally presents unavoidable stochastic behavior. Therefore, accurate and efficient fatigue life prediction is critical for the design of gas turbine blades. Accordingly, this paper analyzes the effects of mean stress, anisotropy, and uncertainties on the LCF life of nickel‐based single‐crystal turbine blades. The modified Hill yield criterion is employed to deal with the anisotropic damage characteristics of nickel‐based single‐crystal superalloy (NSCS) under a multiaxial stress state. Meanwhile, the effects of the temperature and crystal orientation are introduced into the walker mean stress correction term. A multiaxial LCF life prediction model is developed based on the energy criterion‐based fatigue life estimation method. Moreover, multi‐source uncertainties originating from rotation speeds, material properties, and temperature are analyzed and quantified. Comparison between the predicted and tested life indicates that the proposed method produces good accuracy and robustness, which can provide a reference for the reliability design of NSCS turbine blades.

An Improved U-Net Model for Infrared Image Segmentation of Wind Turbine Blade

Abstract: Infrared image segmentation of the wind turbine blade is an important link of wind turbine condition monitoring. Nevertheless, there remain plenty of challenges when the traditional semantic segmentation networks are applied directly to the infrared image segmentation of wind turbine blade, including the blurred boundaries caused by similar thermal radiation of background and blade, the irregularity of edge identification caused by uneven heating, and the hub misidentified as blade. To address these issues, a semantic segmentation neural network based on the basic U-Net is improved for infrared image segmentation of the wind turbine blade. The hierarchical-split depthwise separable convolution block is integrated into the constructed network to have a higher segmentation accuracy. Also, the fusion of convolution layer and batch normalization layer is performed in inference to get a better speed–accuracy tradeoff. The experimental results show that the proposed approach outperforms all the comparing methods, which further demonstrates that the trained network can achieve superior runtime performance and accurate segmentation with excellent anti-interference performance.

Experimental Investigation on Hardware and Triggering Effect in Tip-Timing Measurement Uncertainty

Abstract: Non-destructive testing for structural health monitoring is becoming progressively important for gas turbine manufacturers. As several techniques for diagnostics and condition-based maintenance have been developed over the years, the tip-timing approach is one of the preferred approaches for characterizing the dynamic behavior of turbine blades using non-contact probes. This experimental work investigates the uncertainty of the time-of-arrival of a Blade Tip-Timing measurement system, a fundamental requirement for numerical and aeromechanical modeling validation. The study is applied to both the measurement setup and the data processing procedure of a generic commercial measurement system. The influence of electronic components and signal processing on the tip-timing uncertainty is determined under different operating conditions.

A multiscale model integrating artificial neural networks for failure prediction in turbine blade coatings

Abstract: The failure prediction of turbine blade coatings remains a significant challenge due to complex microstructure and multiphysics failure mechanisms. A multiscale life prediction model integrating artificial neural networks was developed, which considers the failure mechanism of oxidation, creep and thermal mismatch in microscale, and the combined effect of gas and coolant conditions, film cooling and TBCs in macroscale. The model exhibits better prediction accuracy on interface oxidation, damage evolution and failure region of TBCs on turbine vane. Based on the model, the coupled effect of thermal, oxide growth and thermal mismatch on TBCs failure of turbine vane is discovered.

Power Production and Blade Fatigue of a Wind-Turbine Array Subjected to Active Yaw Control

Abstract: This study investigates the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of two-way coupled large-eddy simulation (LES) and aeroelastic blade simulation is applied to simulate the atmospheric boundary-layer (ABL) flow through the turbine array and the structural responses of the turbine blades. Mean power outputs and blade fatigue loads are extracted from the simulation results. By exploring the feasible AYC decision space, we find that (a) in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy; (b) in the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces the blade fatigue from the non-yawed benchmark. Through a theoretical analysis based on the blade element momentum theory, we reveal that the aforementioned differences in flapwise blade fatigue between the positively and negatively yawed turbine are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the combined effects of vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocity and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Computational fluid dynamics (CFD) modeling of actual eroded wind turbine blades

Abstract: Abstract. Leading edge erosion (LEE) is one of the most critical degradation mechanisms that occur with wind turbine blades (WTBs), generally starting from the tip section of the blade. A detailed understanding of the LEE process and the impact on aerodynamic performance due to the damaged leading edge (LE) is required to select the most appropriate leading edge protection (LEP) system and optimize blade maintenance. Providing accurate modeling tools is therefore essential. This paper presents a two-part study investigating computational fluid dynamics (CFD) modeling approaches for different orders of magnitudes in erosion damage. The first part details the flow transition modeling for eroded surfaces with roughness on the order of 0.1–0.2 mm, while the second part focuses on a novel study modeling high-resolution scanned LE surfaces from an actual blade with LEE damage on the order of 10–20 mm (approx. 1 % chord); 2D and 3D surface-resolved Reynolds-averaged Navier–Stokes (RANS) CFD models have been applied to investigate wind turbine blade sections in the Reynolds number (Re) range of 3–6 million. From the first part, the calibrated CFD model for modeling flow transition accounting for roughness shows good agreement of the aerodynamic forces for airfoils with leading-edge roughness heights on the order of 140–200 µm while showing poor agreement for smaller roughness heights on the order of 100 µm. Results from the second part of the study indicate that up to a 3.3 % reduction in annual energy production (AEP) can be expected when the LE shape is degraded by 0.8 % of the chord, based on the NREL5MW turbine. The results also suggest that under fully turbulent conditions, the degree of eroded LE shapes studied in this work show the minimal effect on the aerodynamic performances, which results in a negligible difference to AEP.

Full-Scale Serrated Wind Turbine Trailing Edge Noise Certification Analysis Based on the Lattice-Boltzmann Method

Abstract: This work presents a multi-fidelity framework for wind-turbine aeroacoustic simulations developed at Dassault Systemes. The framework is based on concurrent semi-analytical aerodynamic/aeroacoustic calculations and scale-resolving Computational Fluid Dynamic (CFD) simulations, the latter performed by considering two-dimensional extruded blade profile calculations and three-dimensional full wind-turbine calculations, respectively. Flow simulations are performed by using the high-fidelity multi-propose CFD software SIMULIA PowerFLOW. The benchmark wind-turbine NM80 configuration is considered initially for the assessment of the methodology, while the focus of current paper is on the prediction of wind-turbine serrated blade trailing-edge noise from 2.5D blade section CFD simulations. A step-by-step engineering approach is applied, leading to the analysis and optimization of serrated trailing-edges at different radial positions. Results between airfoil trailing-edge noise prediction in wind-tunnel quasi two-dimensional conditions and the full three-dimensional rotating turbine are compared, confirming lower level of far-field noise reduction for the latter compared to the former, and thus revealing the importance of the proposed methodology in the framework of digital noise reduction prediction of full-scale serrated wind turbine blades.

A fatigue reliability assessment approach for wind turbine blades based on continuous time Bayesian network and FEA

Abstract: Wind turbine blades made by composite materials (CWTBs), encounter fatigue failures, such as cracks, fractures, delamination, etc. Finite Element Analysis (FEA) is applied for fatigue performance simulations of CWTBs as the full‐scale testing is costly. To consider correlated failures and uncertainties in load and material parameters, this paper proposes a fatigue reliability assessment method based on continuous time Bayesian network and FEA. Specifically, the dangerous regions of each component of CWTBs are determined by finite element fatigue simulation. The failure probability distributions of components are then computed by quantifying the uncertainties of several factors including the load and material parameters. A continuous time Bayesian network model is constructed for the fatigue reliability of CWTBs. The performance of the proposed method is verified by a comprehensive analysis with the results of discrete time Bayesian networks.

Enhancement of horizontal wind turbine blade performance using multiple airfoils sections and fences

Abstract: This study addresses performances and behaviors of the multi-cross-section HAWT blade design with and without fences. The FX66-S-196 V, FX63-137 S and SG6043, supercritical airfoils were used and distributed along the blade radius; further, the NACA4412 single-cross-section HAWT blade having the same dimensions was used to compare the behaviors and overall performances of all the blades. Analyses were then performed numerically using blade elements momentum BEM theory with a self-code (F.90) and CFD as well as experimentally with three multi-cross-section blades designed using SOLIDWORKS and 3D- printed with polylactic acid. the multi-cross-section HAWT blades show good performance compared with the single- cross-section blade, with an approximately 8% increase in power coefficient, i.e., 40 W, for a miniature wind turbine (127 cm diameter 500 W output power) and greater improvements for wind turbines with large diameters. The fences were designed using boundary layer theory and installed on multi-cross-section blades in experimentally determined positions. The fences showed high performance, with a 16% increase in total power coefficient and high flutter stability.