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Constructing Fast and Representative Analytical Models of Wind Turbine Main-Bearings

Authors: James Stirling; Edward Hart; Abbas Kazemi Amiri;

Constructing Fast and Representative Analytical Models of Wind Turbine Main-Bearings

Abstract

Abstract. This paper considers the modelling of wind turbine main bearings using analytical models. The validity of simplified analytical representations used in existing work is explored by comparing main bearing force reactions with those obtained from higher fidelity 3D finite element models. Results indicate that there is good agreement between the analytical and 3D models in the case of a non moment-reacting case (such as for a spherical roller bearing), but, the same does not hold in the moment reacting case (such as for tapered roller bearings). Therefore, a new analytical model is developed in which moment reactions at the main bearing are captured through the addition of torsional springs. This latter model is shown to improve the agreement between analytical and 3D models in the moment reacting case. The new analytical model is then used to investigate load characteristics, in terms of forces and moments, for this type of main bearing across different operating points and wind conditions.

Country
United Kingdom
Keywords

690, Electrical engineering. Electronics Nuclear engineering, TK, TJ807-830, Renewable energy sources, 620

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
gold