Lifetime reassessment of offshore wind turbines considering different operating conditions using Kriging meta-models

Schmidt, Franziska; Hübler, Clemens; Rolfes, Raimund

doi:10.5194/wes-2026-38

Preprints

https://doi.org/10.5194/wes-2026-38

Preprints

23 Feb 2026

| 23 Feb 2026

Status: a revised version of this preprint was accepted for the journal WES.

Lifetime reassessment of offshore wind turbines considering different operating conditions using Kriging meta-models

Franziska Schmidt, Clemens Hübler, and Raimund Rolfes

Abstract. To extend the lifetime of an offshore wind turbine, a lifetime reassessment is required to determine the remaining lifetime. In this case, the lifetime is recalculated using the combinations of environmental parameters (wind and wave effects) that actually occurred during the lifetime and which normally differ from the assumed conditions during design. The computational effort of such a lifetime reassessment is significant, as a very large number of aeroelastic simulations has to be carried out. Therefore, according to the state of the art, the number of considered combinations of environmental parameters is reduced similar to the design procedure. In this work, an alternative approach for the lifetime reassessment is investigated in detail. It keeps the full set of combinations of environmental parameters and also considers normal operation as well as idling. The challenge of the high computational effort is resolved by using Kriging meta-models instead of aeroelastic simulations. The meta-model-based approach is compared to two other methods for lifetime reassessment: First, the reference method, i.e., a full lifetime reassessment using aeroelastic simulations where all actually occurred combinations of environmental parameters are considered. And second, the approach according to IEC 61400-3. The results show that it is possible to use meta-models instead of the original simulation model for the lifetime reassessment. The computing time can be significantly reduced compared to the other two methods, while maintaining a high approximation quality in the prediction of the lifetime fatigue loads.

Received: 06 Feb 2026 – Discussion started: 23 Feb 2026

Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Franziska Schmidt, Clemens Hübler, and Raimund Rolfes

Status: final response (author comments only)

RC1:
'Comment on wes-2026-38', Anonymous Referee #1, 03 Mar 2026
As reviewer of the Manuscript wes-2026-38 entitled " Lifetime reassessment of offshore wind turbines considering different operating conditions using Kriging meta-models", I have thoroughly reviewed the manuscript, and I would recommend in accept the manuscript based on my review.
In the abstract, lifetime reassessment is performed using three different models. It is worth adding in the abstract itself, the quantitative comparison among the three different methods.

In the abstract, the author can add their insights on high level takeaways and choices among three different methods.

In the literature review, there are significant number of references are mentioned in the manuscript, but there is no clear description on the gap in the existing literature and how it is addressing in the current manuscript. It is value added to clearly bring this into the manuscript.

I would suggest adding table of comparison with pro’s and con’s among three different methods to easily understand from the manuscript.

There is typo error in 1^st paragraph of conclusions ….which served as a reference soluation and a lifetime calculation

General comment: whether the proposed simulation methods are also applicable for onshore wind turbines? Any justifications/comments on the validity might be worth to add as important note in the manuscript.

I hope my critique helps the authors to improve their work and find useful in this review. Best of luck in developing this study further. Thank you!
Citation: https://doi.org/10.5194/wes-2026-38-RC1
RC2:
'Comment on wes-2026-38', Anonymous Referee #2, 20 May 2026
This paper investigates the use of Kriging/Gaussian-process meta-models for offshore wind turbine lifetime reassessment, considering both normal operation and idling conditions. The authors compare three approaches: a full aeroelastic simulation-based reference calculation, a reduced load-case approach based on IEC 61400-3, and a Kriging meta-model-based approach. The study uses the NREL 5 MW reference turbine on the OC3 monopile, environmental distributions based on FINO 3, and evaluates lifetime damage equivalent loads at the monopile and blade root.
Overall, the paper is well structured, clearly written, and logically developed. The choice of surrogate model is technically sound and supported by established literature. This work represents a valuable contribution to the wind energy community. However, several methodological clarifications and additional validation details are needed before publication. I therefore recommend publication after the authors address the following comments.
Specific Comments

In Section 2.3, the authors use a Monte Carlo step-by-step sizing approach to determine where the lifetime DEL converges, thereby avoiding the need to run the full set of 1,314,900 simulations. However, the manuscript does not clearly define the criterion used to determine convergence. What criterion was used to decide that the lifetime DEL had converged? This should be clearly defined.

In Lines 324–330,: I believe the inclusion of idling conditions is one of the key selling points of this paper. Therefore, a deviation of this magnitude should not be dismissed without further explanation. At the very least, some reasoning or investigation should be provided. For example, if idling conditions were excluded, would the deviation remain similarly large? This issue is particularly important if the proposed method is intended to be applied to cases where idling loads are more influential.

In Section 3.3, the authors note that using the mean Kriging prediction is not conservative and then state that using the 65th percentile for normal operation and the 70th percentile for idling leads to conservative lifetime DEL estimates. This is an interesting and useful correction, but the choice of these percentiles appears empirical and case-specific. The manuscript should explain how these percentiles were selected and discuss whether they are expected to generalize to other turbines or sites.

Minor Comments
Line 83 contains a typo: “The paper ist structured as follows.” This should be corrected to “The paper is structured as follows.”

Line 158 contains a double period: “...for the in-plane and out-of-plane bending moments.. For idling...”.

In Table 2, the range of TpTp is listed as “0.25–30.25 m.” This should likely be in seconds rather than meters.
Citation: https://doi.org/10.5194/wes-2026-38-RC2
AC1: 'Comment on wes-2026-38', Franziska Schmidt, 09 Jun 2026

We want to thank both reviewers for their time and effort in reviewing our article and their constructive feedback that helped us to improve the quality of our paper.
In the attached pdf document, you can find our answers to the comments. Here, the line numbers in the reviewers’ comments refer to the first preprint version (initial submission) whereas the line numbers in our answers refer to the revised version of the paper. The edits in the manuscript are highlighted in magenta for Reviewer 1 and in blue for Reviewer 2.
For your information, in the period between submission and review, the paper was professionally proofread. As a result, some words and, in some cases, sentence structures have changed, but the content has remained unchanged.

Citation: https://doi.org/10.5194/wes-2026-38-AC1

Franziska Schmidt, Clemens Hübler, and Raimund Rolfes

Data sets

Simulation data for lifetime reassessment of an offshore wind turbine Franziska Schmidt et al. https://doi.org/10.25835/ubouf7p2

Franziska Schmidt, Clemens Hübler, and Raimund Rolfes

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Short summary

A lifetime reassessment of an offshore wind turbine using Kriging meta-models is performed. This method is compared to a full lifetime reassessment using aeroelastic simulations considering all actually occurred combinations of environmental parameters and to the approach according to IEC 61400-3. By using the meta-models, the computing time can be significantly reduced compared to the other two methods, while ensuring a high approximation quality in the prediction of the lifetime fatigue loads.


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