Probabilistic prediction of cavitation on rotor blades of tidal stream turbines. (December 2017)
- Record Type:
- Journal Article
- Title:
- Probabilistic prediction of cavitation on rotor blades of tidal stream turbines. (December 2017)
- Main Title:
- Probabilistic prediction of cavitation on rotor blades of tidal stream turbines
- Authors:
- Chernin, Leon
Val, Dimitri V. - Abstract:
- 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. Highlights: A probabilistic approach to predicting the cavitation on the rotor blades of a tidal stream turbine is proposed. Probabilistic models describing uncertainties associated with seawater velocities and depth above blades are introduced. A case study illustrating the application of new probabilistic approach and existing deterministic approach is presented. Probabilistic approach isAbstract: 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. Highlights: A probabilistic approach to predicting the cavitation on the rotor blades of a tidal stream turbine is proposed. Probabilistic models describing uncertainties associated with seawater velocities and depth above blades are introduced. A case study illustrating the application of new probabilistic approach and existing deterministic approach is presented. Probabilistic approach is found advantageous for rational and economically efficient cavitation design of blades. … (more)
- Is Part Of:
- Renewable energy. Volume 113(2017)
- Journal:
- Renewable energy
- Issue:
- Volume 113(2017)
- Issue Display:
- Volume 113, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 113
- Issue:
- 2017
- Issue Sort Value:
- 2017-0113-2017-0000
- Page Start:
- 688
- Page End:
- 696
- Publication Date:
- 2017-12
- Subjects:
- Tidal stream turbine -- Rotor blades -- Cavitation -- Turbulence -- Waves -- Probability
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2017.06.037 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17150.xml