Computational Intelligence Approach for Optimising MHD Casson Ternary Hybrid Nanofluid over the Shrinking Sheet with the Effects of Radiation

Round 1

Reviewer 1 Report

The paper is interesting and can be accepted for publication after addressing the following points:

The title is to be revised; what do you mean by ‘’ Influence of Thermal Analysis’’

The authors considered the effect of radiation; it should be mentioned in the title.

Nanofluids are generally opaque; how can you consider the effect of radiation in such cas?

The main quantitative results are to be mentioned in the abstract.

The novelty of the paper is to be clearly stated.

The used AI technique (ANN) and related equations are to be described in detail.

It should be mentioned that the used nanoparticles have spherical shapes.

The following paper may be added to the literature review:

10.1016/j.csite.2023.103201

The paper is to be checked for misprints and grammatical mistakes.

The paper is to be checked for misprints and grammatical mistakes.

Author Response

please see the attached file

Author Response File: Author Response.pdf

Reviewer 2 Report

In this study, the LMS-BPNN approach is used to scrutinize the flow problem of ternary hybrid nanofluid over a porous shrinking sheet due to MHD effects and thermal radiation. the manuscript has novelty and is well-written, however the manuscript can be published after miner editing as follows:  

1- abstract section need to be rewritten to be more clarified in academic form.  kindly change the self-expression in the first phrase "   The author intends to present..." 

2- kindly if possible give a description (or abbreviation) for "bvp4c" in the abstract section or in another part of the manuscript, to facilitate reading 

3- the introduction is well written but can be enriched with other references. the following references would be beneficial 

https://www.mdpi.com/2079-4991/12/14/2390

https://www.mdpi.com/2079-4991/12/12/1974

4- the novelty of this work needs to be clarified (kindly rewrite the part that includes the novelty of this work based on the literature )

5- kindly provide a sharper version of Fig 1 and add more detail about this one in the captcha.

6-the conclusion gives a short description of the finding and the results of the study. the authors have to highlight their findings with further details also the conclusion must give some recommendations for future studies in the field.    

7- some typos and grammatical errors have been found, however, the manuscript must be checked. 

Author Response

please see attached file

Author Response File: Author Response.docx

Reviewer 3 Report

Tables 1, 2, and 3 show the written formulas of its reference. The quality of the photos is very low. The governing formulas are not referenced. How is the error analysis done? Explain. To improve, read the following articles and refer to the work if needed:

https://journals.sagepub.com/doi/abs/10.1177/09576509231158668

https://journals.sagepub.com/doi/abs/10.1177/09576509211058057

can be improved

Author Response

please see the attached file

Author Response File: Author Response.pdf

Reviewer 4 Report

 

The author resent a novel computational intelligence approach of AI-based Levenberg-Marquardt scheme under the influence of backpropagated neural network (LMS- BPNN) for optimizing MHD ternary hybrid nanofluid using Casson fluid over a porous shrinking sheet in the existence of thermal radiation effects. The manuscript can be accepted after following suggestions for improvement:

Suggestions for Improvement:

1. Begin the article with a clear and concise statement of the research objective. Explain the problem being addressed and the significance of using the AI-based Levenberg–Marquardt scheme with backpropagated neural network for optimizing the MHD ternary hybrid nanofluid. This will provide readers with a clear understanding of the study's focus.

2. Provide a more detailed explanation of the computational intelligence approach and the implementation of the AI-based Levenberg–Marquardt scheme with backpropagated neural network. Describe the steps involved in converting the governing PDEs into ODEs and how the LMS-BPNN is trained and utilized for the numerical analysis.

3. Present the results in a more comprehensive manner. Include tables or graphs showing the numerical data and trends for velocity, temperature, and other relevant parameters. Clearly label and caption the figures to aid readers in understanding the findings.

4. Discuss the implications of the observed trends and numerical results in more detail. Provide a physical interpretation of the velocity and temperature variations with respect to Casson fluid parameters, magnetic field, nanoparticle concentrations, and thermal radiation. Relate the findings to the problem being addressed and discuss their significance in the context of MHD ternary hybrid nanofluid optimization.

By addressing these suggestions, the article will provide a clearer and more informative study on the AI-based Levenberg–Marquardt scheme for optimizing the MHD ternary hybrid nanofluid. These improvements will enhance the clarity, depth, and overall quality of the research.

 

Author Response

Please find the attached file

Author Response File: Author Response.docx

Reviewer 5 Report

Review for Applied Science-2513128

This manuscript focuses on present a novel computational intelligence approach of AI-based Levenberg–Marquardt scheme under the influence of backpropagated neural network (LMS- BPNN) for optimizing MHD ternary hybrid nanofluid using Casson fluid over a porous shrinking sheet in the existence of thermal radiation (??) effects. Authors reported that velocity decreases as ? grows, whereas the magnetic field (?) reverses and ?(0) increases as concentrations of nanoparticles and thermal radiations increase.

The subject is very interesting, however, the substantial revision is needed before publication. My comments are below:

1-      Highlight the novelties of the present work with respect previously published papers?

2-      As nan-Newtonian fluids behavior is highly importance, authors need to mention and cite the following references in the introduction section [“Non-linear rheology of polymer melts: constitutive equations, rheological properties of polymer blends, shear flow, sliding plate rheometers, LAP Lambert Acad. Publ.2011.”, and https://doi.org/10.1007/s10965-012-9897-2].

3-      Application of Marquardt-Levenberg algorithm and neural network method in various fields (polymer, extraction, pharmaceutical, etc) must be mentioned and cited such as [Determination of the Discrete Relaxation Spectrum for Polybutadiene and Polystyrene by a Non-linear Regression Method, Iranian Polymer J. 11 (2002) 107-113., https://doi.org/10.1515/arh-2004-0010, A comprehensive comparison among four different approaches for predicting the solubility of pharmaceutical solid compounds in supercritical carbon dioxide, Korean Journal of Chemical Engineering,…, https://doi.org/10.1016/j.jtice.2015.11.003].

4-      References are few. They must be strengthening.

5-      This manuscript suffers from novel data. Also, sources of used data should be specified.

6-      Analysis of statistical must be comprehensively reported.

7-      A polishing for language edit is needed.

                

 

Comments for author File: Comments.pdf

A revision is needed.

Author Response

Please see the attached file

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

ACCEPTED

Reviewer 5 Report

Authors have addressed the most of my comments. Just they must cite this following book when proofreading. I recommend the manuscript for publication providing that the minor revision.

"Non-linear rheology of polymer melts: constitutive equations, rheological properties of polymer blends, shear flow, sliding plate rheometers, LAP Lambert Acad. Publ. 2011.”

Comments for author File: Comments.docx