Status: final response (author comments only)
This paper deals with PCE for surrogate modelling and sensitivity analysis for use in the Bayesian calibration of (1) airfoil polars and (2) yaw correction model of wind turbines. Data from the DanAero and New MEXICO experiments were deployed in the Bayesian updating process. This paper is well written, to the point, concise, and all assumptions underpinning the presented method and its limitations were clearly explained throughout the paper.
- Under steady conditions, Bayesian udpating the static airfoil polars is correct as described in the paper. The moment unsteady dynamics (large blade deflections) and turbulent inflow are accounted for, one needs then to also think about updating BOTH the Dynamic stall model AND input static airfoil polars. I suggest that the authors spend a bit of time discussion this issue in the paper.
- Once the static airfoil polars are updated conditional on the measurements, there is no garantee that the new/update polars are actually correct. One possibility would be to verify the posterior predicted power outpout (if available) or the blade bending moment (if available) with the new/updated polars. I suggest that the authors spend a bit of time discussion this issue in the paper, and if possible compare the power output (for instance) before and after the updating of the polars.
The authors present a framework to perform model calibration and apply it to two proof of concepts of increasing complexity, highly relevant to the field of wind energy. The others stress at several occasions that these are proofs of concept, and that some steps are "manual" and could need extra care for more advanced applications. I think the level of "discussion"/"moderation", theory, and setup description is well balanced and flows well. I welcome the use of these simple, but relevant, applications.
The work is thourough and well written, so I only have limited comments.
Some of the recurring theme in my comments are: - It would seem relevant to add the evaluation from the polynomial model to the plots on top of the results from the calibrated and uncalibrated Aero-Module. - When describing the "ingredients" of the model, it could be nice to precise which parts are obtained using library calls to UQLab (mentioning the function name of this library could also be interesting to some readers), and which part were implemented in this study.
I enclose some specific comments in the pdf attached to this review, I hope that addressing these in the text could help other readers.
I congratulate the authors for this very interesting work. I'll be looking forward to review a revised version of this paper.
The authors appreciate the valuable comments from the reviewers in order to improve the quality of the work. In response to that, the following are the author's (on behalf of all co-author) comments.
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