Full-field 3D displacements and surfaces strains of a small-scale wind turbine blade during static testing

2014 ◽  
pp. 327-332
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Full Field ◽  
Static Testing

An Investigation of the Aerodynamic Response of a Wind Turbine Blade to Tower Shadow

2004 ◽  
Vol 126 (4) ◽  
pp. 1034-1040 ◽  
Author(s):  
Xabier Munduate ◽  
Frank N. Coton ◽  
Roderick A.McD. Galbraith
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Careful Consideration ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Force Coefficient ◽  
Velocity Deficit ◽  
Pressure Transducers ◽  
Aerodynamic Model ◽  
Tower Shadow

This paper presents results from a wind tunnel based examination of the response of a wind turbine blade to tower shadow in head-on flow. In the experiment, one of the blades of a small-scale, two-bladed, downwind turbine was instrumented with miniature pressure transducers to allow recording of the blade surface pressure response through tower shadow. The surface pressures were then integrated to provide the normal force coefficient responses presented in this paper. It is shown that it is possible to reproduce the measured responses using an indicially formulated unsteady aerodynamic model applied to a cosine wake velocity deficit. It is also shown that agreement between the model and the measured data can be improved by careful consideration of the velocity deficit geometry.

scholarly journals Design and Development of a New Small-Scale Wind Turbine Blade

2015 ◽  
Author(s):  
Ulan Dakeev ◽  
Quamrul Mazumder ◽  
Faruk Yildiz ◽  
Kenan Baltaci
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Design And Development

scholarly journals Non-Destructive Evaluation of Damage Mechanisms in Composite Sandwich Structure

2008 ◽  
Vol 13-14 ◽  
pp. 105-114
Author(s):  
Amit Puri ◽  
Alexander D. Fergusson ◽  
I. Palmer ◽  
Andrew Morris ◽  
F. Jensen ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Structural Integrity ◽  
Wind Turbine Blade ◽  
Image Correlation ◽  
Box Girder ◽  
Full Field ◽  
Composite Sandwich ◽  
Non Destructive ◽  
Dic Technique

This paper presents the experimental results obtained of flexurally loaded wind turbine blade cross section material. All material was extracted from a wind turbine blade box girder and testing was conducted in four point configuration. The aim was to gain an understanding of the structural integrity of this lightweight material as it deforms in flexure. To allow for thorough analysis, digital image correlation (DIC) was used to produce full field strain maps of the deforming specimens. Results highlight the capability of the DIC technique to identify regions of failure, as well as the aspects responsible for them. Overall, the results present a foundation for tests on larger substructure, and eventually integration into manufacturing and maintenance aspects of the industry.

Monitoring Multi-Site Damage Growth During Quasi-Static Testing of a Wind Turbine Blade using a Structural Neural System

2008 ◽  
Vol 7 (2) ◽  
pp. 157-173 ◽  
Author(s):  
Goutham R. Kirikera ◽  
Vishal Shinde ◽  
Mark J. Schulz ◽  
Mannur J. Sundaresan ◽  
Scott Hughes ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Neural System ◽  
Wind Turbine Blade ◽  
Damage Growth ◽  
Static Testing

Cable Reinforced Small Scale Horizontal Axial Wind Turbine

2013 ◽  
Vol 394 ◽  
pp. 309-313
Author(s):  
Yuan Ma ◽  
Pan Zeng ◽  
Hong Ya Lu ◽  
Yue Jie Xu
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbines ◽  
Noise Level ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Optimum Location ◽  
Reinforcement Structure ◽  
First Order ◽  
Vibration Tests

In this paper, a cable reinforcement structure for small scale horizontal axial wind turbines is proposed. Shock-vibration tests were performed on the cable reinforced structure with different parameters of cable installation. The first order frequency of the blade was chosen to represent the stiffness of the blade rotor. According to the results, an optimum location of cable reinforcement exists at around 1/3 length of the wind turbine blade, and the first order frequency of the blade rotor will rise with the tension of the cable in a certain range. Further analysis showed that besides improving the reliability of the wind turbine rotors, the cable reinforcement structure also provides a possibility to use cheaper materials for blade manufacturing and also control the noise level of small scale horizontal axial wind turbines.

scholarly journals Airfoil types effect on geometry and performance of a small-scale wind turbine blade design

2020 ◽  
Vol 18 (1) ◽  
pp. 132-139
Author(s):  
Sigit Iswahyudi ◽  
S Sutrisno ◽  
P Prajitno ◽  
Setyawan Wibowo
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Blade Design ◽  
And Performance ◽  
Turbine Blade Design

scholarly journals PSO-BP Neural Network-Based Strain Prediction of Wind Turbine Blades

Materials ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 1889 ◽  
Author(s):  
Xin Liu ◽  
Zheng Liu ◽  
Zhongwei Liang ◽  
Shun-Peng Zhu ◽  
José A. F. O. Correia ◽  
...  
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Full Scale ◽  
Wind Turbine Blade ◽  
Blade Design ◽  
Wind Turbine Blades ◽  
Static Testing ◽  
Bpnn Model

The full-scale static testing of wind turbine blades is an effective means to verify the accuracy and rationality of the blade design, and it is an indispensable part in the blade certification process. In the full-scale static experiments, the strain of the wind turbine blade is related to the applied loads, loading positions, stiffness, deflection, and other factors. At present, researches focus on the analysis of blade failure causes, blade load-bearing capacity, and parameter measurement methods in addition to the correlation analysis between the strain and the applied loads primarily. However, they neglect the loading positions and blade displacements. The correlation among the strain and applied loads, loading positions, displacements, etc. is nonlinear; besides that, the number of design variables is numerous, and thus the calculation and prediction of the blade strain are quite complicated and difficult using traditional numerical methods. Moreover, in full-scale static testing, the number of measuring points and strain gauges are limited, so the test data have insufficient significance to the calibration of the blade design. This paper has performed a study on the new strain prediction method by introducing intelligent algorithms. Back propagation neural network (BPNN) improved by Particle Swarm Optimization (PSO) has significant advantages in dealing with non-linear fitting and multi-input parameters. Models based on BPNN improved by PSO (PSO-BPNN) have better robustness and accuracy. Based on the advantages of the neural network in dealing with complex problems, a strain-predictive PSO-BPNN model for full-scale static experiment of a certain wind turbine blade was established. In addition, the strain values for the unmeasured points were predicted. The accuracy of the PSO-BPNN prediction model was verified by comparing with the BPNN model and the simulation test. Both the applicability and usability of strain-predictive neural network models were verified by comparing the prediction results with simulation outcomes. The comparison results show that PSO-BPNN can be utilized to predict the strain of unmeasured points of wind turbine blades during static testing, and this provides more data for characteristic structural parameters calculation.

In-situ damage localization for a wind turbine blade through outlier analysis of stochastic dynamic damage location vector-induced stress resultants

2016 ◽  
Vol 16 (6) ◽  
pp. 745-761 ◽  
Author(s):  
Martin Dalgaard Ulriksen ◽  
Dmitri Tcherniak ◽  
Lasse M Hansen ◽  
Rasmus Johan Johansen ◽  
Lars Damkilde ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Small Scale ◽  
Stochastic Dynamic ◽  
Damage Localization ◽  
Outlier Analysis ◽  
Damage Location ◽  
Dynamic Damage ◽  
Characteristic Stress

Today, structural integrity inspections of wind turbine blades are typically carried out by the use of rope or platform access. Since these inspection approaches are both tedious and extremely costly, a need for a method facilitating reliable, remote monitoring of the blades has been identified. In this article, it is examined whether a vibration-based damage localization approach proposed by the authors can provide such reliable monitoring of the location of a structural damage in a wind turbine blade. The blade, which is analyzed in idle condition, is subjected to unmeasured hits from a mounted actuator, yielding vibrations that are measured with a total of 12 accelerometers; of which 11 are used for damage localization. The employed damage localization method is an extended version of the stochastic dynamic damage location vector method, which, in its origin, is a model-based method that interrogates damage-induced changes in a surrogate of the transfer matrix. The surrogate’s quasi-null vector associated with the lowest singular value is converted into a pseudo-load vector and applied to a numerical model of the healthy structure in question, hereby, theoretically, yielding characteristic stress resultants approaching zero in the damaged elements. The proposed extension is based on outlier analysis of the characteristic stress resultants to discriminate between damaged elements and healthy ones; a procedure that previously, in the context of experiments with a small-scale blade, has proved to mitigate noise-induced anomalies and systematic, non-damage-associated adverse effects.

Full-field inspection of a wind turbine blade using three-dimensional digital image correlation

2011 ◽  
Author(s):  
Bruce LeBlanc ◽  
Christopher Niezrecki ◽  
Peter Avitabile ◽  
Julie Chen ◽  
James Sherwood ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Digital Image ◽  
Three Dimensional ◽  
Wind Turbine Blade ◽  
Image Correlation ◽  
Full Field ◽  
Field Inspection
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