Development of a second-order dynamic stall model

<p>Dynamic stall phenomena carry the risk of negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue and extreme) loads. Some of the inaccuracies in current dynamic stall models may...

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Main Authors: N. Adema, M. Kloosterman, G. Schepers
Format: Article
Language:English
Published: Copernicus Publications 2020-05-01
Series:Wind Energy Science
Online Access:https://www.wind-energ-sci.net/5/577/2020/wes-5-577-2020.pdf
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spelling doaj-fd16e3199d7a42f98ae912a2477105f32020-11-25T02:03:44ZengCopernicus PublicationsWind Energy Science2366-74432366-74512020-05-01557759010.5194/wes-5-577-2020Development of a second-order dynamic stall modelN. Adema0M. Kloosterman1G. Schepers2EUREC European Master in Renewable Energy, Hanze University of Applied Sciences, Groningen, 9747 AS, the NetherlandsDNV GL, Groningen, 9743 AN, the NetherlandsEUREC European Master in Renewable Energy, Hanze University of Applied Sciences, Groningen, 9747 AS, the Netherlands<p>Dynamic stall phenomena carry the risk of negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue and extreme) loads. Some of the inaccuracies in current dynamic stall models may be due to the fact that they are not properly designed for high angles of attack and that they do not specifically describe vortex shedding behaviour. The Snel second-order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to a turbine design software such as Bladed. In this paper the model has been validated with oscillating aerofoil experiments, and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small-scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicted and measured (fatigue and extreme) loading, leading to possible lower safety factors for design and more cost-efficient designs for future wind turbines.</p>https://www.wind-energ-sci.net/5/577/2020/wes-5-577-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author N. Adema
M. Kloosterman
G. Schepers
spellingShingle N. Adema
M. Kloosterman
G. Schepers
Development of a second-order dynamic stall model
Wind Energy Science
author_facet N. Adema
M. Kloosterman
G. Schepers
author_sort N. Adema
title Development of a second-order dynamic stall model
title_short Development of a second-order dynamic stall model
title_full Development of a second-order dynamic stall model
title_fullStr Development of a second-order dynamic stall model
title_full_unstemmed Development of a second-order dynamic stall model
title_sort development of a second-order dynamic stall model
publisher Copernicus Publications
series Wind Energy Science
issn 2366-7443
2366-7451
publishDate 2020-05-01
description <p>Dynamic stall phenomena carry the risk of negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue and extreme) loads. Some of the inaccuracies in current dynamic stall models may be due to the fact that they are not properly designed for high angles of attack and that they do not specifically describe vortex shedding behaviour. The Snel second-order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to a turbine design software such as Bladed. In this paper the model has been validated with oscillating aerofoil experiments, and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small-scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicted and measured (fatigue and extreme) loading, leading to possible lower safety factors for design and more cost-efficient designs for future wind turbines.</p>
url https://www.wind-energ-sci.net/5/577/2020/wes-5-577-2020.pdf
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AT mkloosterman developmentofasecondorderdynamicstallmodel
AT gschepers developmentofasecondorderdynamicstallmodel
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