Performance of non-intrusive uncertainty quantification in the aeroservoelastic simulation of wind turbines

Bortolotti, Pietro; Canet, Helena; Bottasso, Carlo L.; Loganathan, Jaikumar

doi:https://doi.org/10.5194/wes-4-397-2019

Articles | Volume 4, issue 3

https://doi.org/10.5194/wes-4-397-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-4-397-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 4, issue 3

Brief communication

|

11 Jul 2019

Brief communication |

| 11 Jul 2019

Performance of non-intrusive uncertainty quantification in the aeroservoelastic simulation of wind turbines

Pietro Bortolotti, Helena Canet, Carlo L. Bottasso, and Jaikumar Loganathan

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Final revised paper (published on 11 Jul 2019)
Preprint (discussion started on 15 Jan 2019)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review summary', Anonymous Referee #1, 17 Feb 2019
RC2: 'Review of WES-2018-75-R0 (please consider the attached pdf file)', Anonymous Referee #2, 20 Mar 2019
AC1: 'Reply to the reviewers' comments', Carlo L. Bottasso, 23 May 2019
AC2: 'Modified manuscript', Carlo L. Bottasso, 23 May 2019

Peer-review completion

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

AR by Carlo L. Bottasso on behalf of the Authors (23 May 2019) Manuscript

ED: Publish as is (28 May 2019) by Michael Muskulus

ED: Publish as is (05 Jun 2019) by Joachim Peinke (Chief editor)

AR by Carlo L. Bottasso on behalf of the Authors (12 Jun 2019) Manuscript

Short summary

The paper studies the effects of uncertainties in aeroservoelastic wind turbine models. Uncertainties are associated with the wind inflow characteristics and the blade surface state, and they are propagated by means of two non-intrusive methods throughout the aeroservoelastic model of a large conceptual offshore wind turbine. Results are compared with a brute-force extensive Monte Carlo sampling to assess the convergence characteristics of the non-intrusive approaches.