Probabilistic prediction of cavitation on rotor blades of tidal stream turbines

Leon Chernin and Dimitri V. Val

Renewable Energy, 2017, vol. 113, issue C, 688-696

Abstract: Power generation from tidal currents is currently a fast developing sector of the renewable energy industry. A number of technologies are under development within this sector, of which the most popular one is based on the use of horizontal axis turbines with propeller-type blades. When such a turbine is operating, the interaction of its rotating blades with seawater induces pressure fluctuations on the blade surface which may cause cavitation. Depending on its extent and severity, cavitation may damage the blades through erosion of their surface, while underwater noise caused by cavitation may be harmful to marine life. Hence, it is important to prevent cavitation or at least limit its harmful effects. The paper presents a method for predicting the probability of cavitation on blades of a horizontal axis tidal stream turbine. Uncertainties associated with the velocities of seawater and water depth above the turbine blades are taken into account. It is shown how using the probabilistic analysis the expected time of exposure of the blade surfaces to cavitation can be estimated.

Keywords: Tidal stream turbine; Rotor blades; Cavitation; Turbulence; Waves; Probability (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117305426
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:113:y:2017:i:c:p:688-696

DOI: 10.1016/j.renene.2017.06.037

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().