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Article
Peer-Review Record

Experimental Determination of the Heat Transfer Coefficient of Real Cooled Geometry Using Linear Regression Method

Energies 2021, 14(1), 180; https://doi.org/10.3390/en14010180
by Asif Ali *, Lorenzo Cocchi, Alessio Picchi and Bruno Facchini
Reviewer 1:
Reviewer 2: Anonymous
Energies 2021, 14(1), 180; https://doi.org/10.3390/en14010180
Submission received: 12 November 2020 / Revised: 22 December 2020 / Accepted: 24 December 2020 / Published: 31 December 2020
(This article belongs to the Special Issue Gas Turbine Cooling Systems Design and Analysis)

Round 1

Reviewer 1 Report

Comments are attached

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

First of all, we would like to express our gratitude to you for the effectiveness and quality of your observation.

Based upon your comments the paper has been modified: various details and additional information have be added according to the different suggestions. Minor issues related to typos present in the draft have also been corrected.

To properly address the requests, specific answers to the various comments are reported in the attached reviewer_rebuttal file from page 1 to page 3.

The edited sections or lines are colored Red in the new draft paper (from page 4 to page 20 of reviewer_rebuttal file) for the visibility of the made changes.

Kind Regards

A. Ali, L. Cocchi, A. Picchi, and  B. Facchini

Author Response File: Author Response.pdf

Reviewer 2 Report

Overall

The paper describes the improvement of a literature approach to determine the internal heat transfer coefficient of cooled geometry using an external temperature distribution determined in an experiment and an iterative adjustment of the inner heat flux in a finite element simulation of the structure.

It is well written, the goal and methods are described clearly and completely and the figures complement the text well.

The approach itself is interesting and has great potential for use in application, if its robustness and accuracy can be proved. The latter is shown in this paper only in comparison to other models (the original model from ref [9] and correlations). For future work I would therefore like to suggest applying this method to a test case where a resolved distribution of HTC on the inside of the geometry (or maybe just a surface of the geometry that is hidden from the camera) is known from measurements. This would help identifying the "true" error range of the method (not the deviation to other models) and build confidence in this type of analysis. Also, a CFD simulation of the inner flow structures would help to justify the interpretation of the results.

Content

Some suggestions for making the paper more complete/easier to understand:

  • lines 44 - 51: The introduction lacks some references here. Consider mentioning/referencing some scaled/real hardware test rigs of the research community (OTRF,THTF/Oxford, NG-Turb Rig/Gottingen, Trisector Rig/Florence, LSTR/Darmstadt) or OEMS (https://www.dglr.de/publikationen/2017/450036.pdf) and the work of researchers investigating roughness effects (e.g. Karen Thole).
  • lines 137 - 140: Has the application of the black paint with a constant thickness on the 3D geometry been measured/assured in any way?
  • section 2.2: Has a sensitivity study been conducted to evaluate how the external HTC influences the results? If yes, consider including the results.
  • section 2.2: Has a systematic grid study been conducted? If yes, consider including the results.
  • section 2.2: What is the FEM boundary condition of the external surfaces where the geometry is fixed to the support?
  • line 181: Consider referring to a paper such as "Moffat, What's new in convective heat transfer?" that explains why the adiabatic wall temperature is a desirable reference (instead of the flow temperature).
  • line 181: In my opinion, the phrase "Tf is the adiabatic wall temperature" simplifies the matter a bit too much. Consider explaining the extrapolation to zero heat flux and distinguishing between flow temperature and adiabatic wall temperature better.
  • line 183: Consider referring to a paper such as "M. Gritsch, et al. The superposition approach to local heat transfer coefficients in high density ratio film cooling flows." in order to help understand this technique.
  • fig 2: I like this illustration. It provides a good overview on your approach!
  • fig 9: An additional illustration of the internal cooling geometry/core of the vane would help following your interpretation of the results.
  • tab 1: Where does the uncertainty for Tf come from? You cannot know that without knowing the actual flow distribution.
  • line 283: I suggest using a Monte-Carlo method for error estimation to challenge the results of the quadratic error propagation model. Your approach should be suitable for that.
  • overall approach: The greatest weakness of the approach (in terms of missing information or approximations) seems to be the distribution of Tf. Your error estimation says otherwise for the U-bend but I expect that for the highly 3D internal flow of the vane the uncertainty in bulk flow tmperature will be higher. Consider running 3D CFD to confirm the results of the flow model.

Language

  • line 25: Consider replacing "convective heat transfer" with "internal convective heat transfer".
  • line 34: Consider mentioning "manufacturing tolerances (e.g. of cooling holes)" as additional real hardware aspect.
  • line 83: The term "internal cooled geometry" might be misleading because (in case of film cooling) it is the inside of an externally cooled geometry.
  • line 83: Replace "principal" -> "principle".
  • line 85: Replace "phenomena" -> "phenomenon".
  • line 112: Replace "assemble" -> "assembly".
  • section 2.2: The initial temperature distribution should not be referred to as "boundary condition" but rather as "initial condition".
  • section 2.2: Replace "does not exceeds" -> "does not exceed".
  • section 2.2: Consider replacing "measure the internal heat transfer coefficient" with "compute the internal heat transfer coefficient".
  • section 2.3 (and following): Consider renaming "regression" and "baseline" with "our approach" and "approach by [9]" or similar, for more clarity.
  • line 293: Replace "is" -> "are".
  • line 306: Replace "mach" -> "Mach".
  • line 324: Replace "phenomena" -> "phenomenon".
  • line 324: Replace "form" -> "from".
  • line 327: Replace "compare" -> "compared".
  • line 380: Replace "mach" -> "Mach".
  • line 403: Replace "values always" -> "values are always".

Author Response

Dear Reviewer,

First of all, we would like to express our gratitude to you for the effectiveness and quality of your observation.

Based upon your comments the paper has been modified: various details and additional information have be added according to the different suggestions. Minor issues related to typos present in the draft have also been corrected.

To properly address the requests, specific answers to the various comments are reported in the attached reviewer_rebuttal file from page 1 to page 4.

The edited sections or lines are colored Red in the new draft paper (from page 5 to page 21 of reviewer_rebuttal file) for the visibility of the made changes.

Kind Regards

Author Response File: Author Response.pdf

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