The risks of extreme load extrapolation

van Eijk, Stefan F.; Bos, René; Bierbooms, Wim A. A. M.

doi:https://doi.org/10.5194/wes-2-377-2017

Articles | Volume 2, issue 2

https://doi.org/10.5194/wes-2-377-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/wes-2-377-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 2, issue 2

Research article

|

14 Jul 2017

Research article |

| 14 Jul 2017

The risks of extreme load extrapolation

Stefan F. van Eijk, René Bos, and Wim A. A. M. Bierbooms

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Final revised paper (published on 14 Jul 2017)
Preprint (discussion started on 14 Mar 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review comments: interesting study, but needs to be reworked significantly', Nikolay Dimitrov, 14 Apr 2017
- AC1: 'Thank you for the comments, please find our reply attached', René Bos, 03 May 2017
RC2: 'Review of "The risks of extreme load extrapolation"', Anonymous Referee #2, 26 Apr 2017
- AC2: 'Thank you for the comments, please find our reply attached', René Bos, 03 May 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (review by editor) (23 May 2017) by Michael Muskulus

AR by René Bos on behalf of the Authors (25 May 2017) Author's response Manuscript

ED: Publish as is (12 Jun 2017) by Michael Muskulus

ED: Publish as is (19 Jun 2017) by Joachim Peinke (Chief editor)

AR by René Bos on behalf of the Authors (19 Jun 2017)

Short summary

Predicting the 50-year extreme loads for wind turbines requires a tremendous computational effort. Therefore, designers often have to extrapolate from relatively small data sets and have to settle for some degree of uncertainty. We investigated the impact of this uncertainty on practical design problems by drawing subsets from a 96-year load data set and using a crude Monte Carlo method to find the 50-year load. The results show that designers have to be careful with selecting sample sizes.