## Abstract

Tidal stream turbines are a new technology for extracting kinetic energy from tidal currents. A number of different concepts of such devices have been proposed up to now and the most popular of them is a horizontal-axis turbine with propeller-type blades. Although the concept looks similar to a typical wind turbine, guidelines for the design and reliability assessment of wind turbine blades are not applicable for those of tidal stream turbines due to a number of reasons, in particular much higher loads on the blades of tidal turbines since seawater is about 830 times denser than air. The paper concentrates on the reliability of tidal turbine blades in the context of bending failure. Uncertainties associated with tidal current speeds, the blade resistance and the model used to calculate bending moments in the blades are taken into account in reliability analysis. The paper shows how results of the reliability analysis can be applied to set values of the partial factors for the design of tidal turbine rotor blades with respect to failure in bending

Original language | English |
---|---|

Title of host publication | Applications of statistics and probability in civil engineering - |

Subtitle of host publication | Proceedings of the 11th international conference on applications of statistics and probability in civil engineering |

Editors | Michael Faber, Jochen Koehler, Kazuyoshi Nishijima |

Publisher | Taylor & Francis |

Pages | 1817-1822 |

Number of pages | 6 |

Edition | 1st |

ISBN (Print) | 9780415669863, 0415669863 |

DOIs | |

Publication status | Published - 15 Jul 2011 |

Event | 11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP - Zurich, Switzerland Duration: 1 Aug 2011 → 4 Aug 2011 |

### Conference

Conference | 11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP |
---|---|

Country/Territory | Switzerland |

City | Zurich |

Period | 1/08/11 → 4/08/11 |

## ASJC Scopus subject areas

- Civil and Structural Engineering
- Statistics and Probability