Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
Journal topic
Volume 3, issue 1
Wind Energ. Sci., 3, 107-120, 2018
https://doi.org/10.5194/wes-3-107-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Wind Energ. Sci., 3, 107-120, 2018
https://doi.org/10.5194/wes-3-107-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research articles 14 Mar 2018

Research articles | 14 Mar 2018

Effects of defects in composite wind turbine blades – Part 3: A framework for treating defects as uncertainty variables for blade analysis

Trey W. Riddle1, Jared W. Nelson2, and Douglas S. Cairns3 Trey W. Riddle et al.
  • 1Sunstrand, LLC, 1401 Locust Street, Louisville, KY 40206, USA
  • 2SUNY New Paltz, Division of Engineering Programs, New Paltz, NY, USA
  • 3Montana State University, Dept. of Mechanical and Industrial Engineering, Bozeman, MT, USA

Abstract. Given that wind turbine blades are large structures, the use of low-cost composite manufacturing processes and materials has been necessary for the industry to be cost competitive. Since these manufacturing methods can lead to the inclusion of unwanted defects, potentially reducing blade life, the Blade Reliability Collaborative tasked the Montana State University Composites Group with assessing the effects of these defects. Utilizing the results of characterization and mechanical testing studies, probabilistic models were developed to assess the reliability of a wind blade with known defects. As such, defects were found to be best assessed as design parameters in a parametric probabilistic analysis allowing for establishment of a consistent framework to validate categorization and analysis. Monte Carlo simulations were found to adequately describe the probability of failure of composite blades with included defects. By treating defects as random variables, the approaches utilized indicate the level of conservation used in blade design may be reduced when considering fatigue. In turn, safety factors may be reduced as some of the uncertainty surrounding blade failure is reduced when analyzed with application specific data. Overall, the results indicate that characterization of defects and reduction of design uncertainty is possible for wind turbine blades.

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The Department of Energy sponsored, Sandia National Laboratory led Blade Reliability Collaborative was formed to address wind turbine blade reliability. Utilizing the results of characterization and mechanical testing studies, probabilistic models were developed to assess the reliability of a wind blade with known defects. By treating defects as random variables, the results indicate that characterization of defects and reduction of design uncertainty is possible for wind turbine blades.
The Department of Energy sponsored, Sandia National Laboratory led Blade Reliability...
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