<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Leading edge erosion of wind turbine blades: Understanding, prevention and protection

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 May 2021Publisher:Elsevier BVJournal:Renewable Energy, volume 169, pages 953-969 (issn: 0960-1481,

Authors: Anna-Maria Tilg; Jakob Ilsted Bech; Charlotte Bay Hasager; Christian Bak; Saeed Doagou Rad; Søren Fæster; Leon Mishnaevsky;

doi: 10.1016/j.renene.2021.01.044

Leading edge erosion of wind turbine blades: Understanding, prevention and protection

- Summary
- Metrics

Abstract

Abstract Surface erosion of wind turbine blades is one of rather critical problems of the wind energy development. In this overview paper, recent studies in the mechanisms, modelling and possibilities of preventing the surface erosion of wind turbine blades are discussed. Latest research in the area of leading edge erosion (LEE) from different viewpoints, based on meteorology, aerodynamics, materials science, computational mechanics are summarized. Technologies of experimental testing of anti-erosion coatings, effect of leading edge erosion on aerodynamics of wind turbines, roughness and its evolution are discussed, as well as meteorological aspects, parameters and characteristics of precipitation, possibilities of prediction of rain and hail and regional differences. Further, computational models of LEE and directions of the development of anti-erosion coatings are presented.

Related Organizations

Technical University of Denmark
Denmark

Impact byBIP!

	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).	123
	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.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 0.1%