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Article
Peer-Review Record

Extended Hierarchical Kriging Method for Aerodynamic Model Generation Incorporating Multiple Low-Fidelity Datasets

by Vinh Pham 1, Maxim Tyan 1, Tuan Anh Nguyen 1 and Jae-Woo Lee 1,2,*
Reviewer 1: Anonymous
Reviewer 2:
Submission received: 8 November 2023 / Revised: 10 December 2023 / Accepted: 16 December 2023 / Published: 20 December 2023
(This article belongs to the Special Issue Aerodynamic and Multidisciplinary Design Optimization)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

All in all, it is a good job. Congratulations!

Detailed comments: in order not to confuse the symbol for the exponential exp, the logarithm ln and sin, it is proposed that they should always be written in roman type and not in italics. Revise expressions 15, 16, 19, 20, 24, 25, 26 and table 2 and B1.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In this manuscript, the authors proposed the Extended Hierarchical Kriging (EHK) method, which leverages a unique Bayesian-based MFSM framework, simultaneously combining non-level LF models using scaling factors to construct a global trend model. This research is interesting and has practical significance. Some of the suggestions and questions are listed in the attached file.

Comments for author File: Comments.pdf

Author Response

Please see the attachment

Author Response File: Author Response.pdf

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