Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines

Müller, Kolja; Cheng, Po Wen

doi:https://doi.org/10.5194/wes-3-149-2018

Articles | Volume 3, issue 1

https://doi.org/10.5194/wes-3-149-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-3-149-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 3, issue 1

Research article

|

26 Mar 2018

Research article |

| 26 Mar 2018

Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines

Kolja Müller and Po Wen Cheng

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Final revised paper (published on 26 Mar 2018)
Preprint (discussion started on 26 Oct 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review', Anonymous Referee #1, 27 Nov 2017
- AC1: 'reply', Kolja Müller, 31 Jan 2018
SC1: 'Application of a Monte Carlo Procedure for Probabilistic Fatigue Design of Floating Offshore Wind Turbines', Clemens Hübler, 01 Dec 2017
- AC1: 'reply', Kolja Müller, 31 Jan 2018
RC2: 'Comments following review WES-2017-41', Anonymous Referee #2, 17 Dec 2017
- AC1: 'reply', Kolja Müller, 31 Jan 2018

Peer-review completion

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

AR by Kolja Müller on behalf of the Authors (31 Jan 2018) Manuscript

ED: Publish as is (16 Feb 2018) by Michael Muskulus

ED: Publish as is (16 Feb 2018) by Jakob Mann (Chief editor)

AR by Kolja Müller on behalf of the Authors (20 Feb 2018)

Short summary

An efficient and accurate Monte Carlo approach is presented to assess the lifetime fatigue loading on a floating offshore wind turbine accurately. This is typically challenging in simulation effort due to the many different combinations of relevant environmental conditions which need to be considered. The applied method uses quasi-random Sobol sequences and shows promising performance with respect to convergence and accuracy.