On the influence of airfoil deviations on the aerodynamic performance of wind turbine rotors

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Winstroth, J.; Seume, J.R.: On the influence of airfoil deviations on the aerodynamic performance of wind turbine rotors. In: Journal of Physics: Conference Series 753 (2016), Nr. 2, 22058. DOI: https://doi.org/10.1088/1742-6596/753/2/022058

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/2628

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Sum total of downloads: 178




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Abstract: 
The manufacture of large wind turbine rotor blades is a difficult task that still involves a certain degree of manual labor. Due to the complexity, airfoil deviations between the design airfoils and the manufactured blade are certain to arise. Presently, the understanding of the impact of manufacturing uncertainties on the aerodynamic performance is still incomplete. The present work analyzes the influence of a series of airfoil deviations likely to occur during manufacturing by means of Computational Fluid Dynamics and the aeroelastic code FAST. The average power production of the NREL 5MW wind turbine is used to evaluate the different airfoil deviations. Analyzed deviations include: Mold tilt towards the leading and trailing edge, thick bond lines, thick bond lines with cantilever correction, backward facing steps and airfoil waviness. The most severe influences are observed for mold tilt towards the leading and thick bond lines. By applying the cantilever correction, the influence of thick bond lines is almost compensated. Airfoil waviness is very dependent on amplitude height and the location along the surface of the airfoil. Increased influence is observed for backward facing steps, once they are high enough to trigger boundary layer transition close to the leading edge.
License of this version: CC BY 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2016
Appears in Collections:Fakultät für Maschinenbau

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 99 55.62%
2 image of flag of United States United States 20 11.24%
3 image of flag of China China 17 9.55%
4 image of flag of Tanzania, United Republic of Tanzania, United Republic of 5 2.81%
5 image of flag of Russian Federation Russian Federation 5 2.81%
6 image of flag of Czech Republic Czech Republic 5 2.81%
7 image of flag of Philippines Philippines 2 1.12%
8 image of flag of United Kingdom United Kingdom 2 1.12%
9 image of flag of Spain Spain 2 1.12%
10 image of flag of Canada Canada 2 1.12%
    other countries 19 10.67%

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