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Article
Peer-Review Record

Simulation of Light Scattering in Automotive Paints: Role of Particle Size

Mathematics 2023, 11(11), 2429; https://doi.org/10.3390/math11112429
by Sergey Ershov, Alexey Voloboy * and Vladimir Galaktionov
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3:
Mathematics 2023, 11(11), 2429; https://doi.org/10.3390/math11112429
Submission received: 29 April 2023 / Revised: 18 May 2023 / Accepted: 22 May 2023 / Published: 24 May 2023
(This article belongs to the Special Issue Modeling and Simulation in Engineering, 2nd Edition)

Round 1

Reviewer 1 Report

In the introduction, the authors did not provide a strong motivation for the paper and the obtained results. In addition, they should discuss the main contributions of their work in detail after the motivation part. Then they should summarize the main structure of their paper in brief at the end of the introduction. In addition, the Introduction should contain answers to the following questions: What problem is studied and why it is important? Which methods are used? What is the importance of the results? What conclusions can be drawn from the results?

Minor editing of English language required.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Please find the attached file for a detailed review report

Comments for author File: Comments.pdf

Minor editing of the English language required

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study propose an analysis on the effect of particle size for paired surface luminance on the simulation of light scattering in material. The study is properly formulated, mathematics justification are provided with numerical benchmarks. The authors dig in the deviation of light scattering phenomenon in media and point out the role of correlations between particles. I have a few questions for the authors to response:

 

 

 

  1. Forward problems show good application of the method, I am wondering if it could handle inverse problem? For example, given the observation, could you identify the particle size bases on it?
  2. Wonder if it could be a problem scale up the dimensionality of this study to 3D cases? Could the authors make it a bit clear?
  3. Could a recent work  “Solving Optical Tomography with Deep Learning” be useful to improve the current work? The work uses deep learning approach to study the PDE of optical phenomenon in 2D material. 

Overall the manuscript is well written. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Accept it

Reviewer 3 Report

I appreciate the authors for addressing the questions!

 

I recommend for publishing.

 

Overall English is descent.

 

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