Behavioral Investigation of Single Wall and Double Wall CNT Mixed Asphalt Adhesion Force Using Chemical Force Microscopy and Artificial Neural Networks

Round 1

Reviewer 1 Report

In the Reviewer opinion the research paper entitled “BEHAVIORAL INVESTIGATION OF SINGLE WALL AND DOUBLE WALL CNT MIXED ASPHALT ADHESION FORCE USING CHEMICAL FORCE MICROSCOPY (CFM) SUPPORTED NANOTECHNOLOGY AND RBF ARTIFICIAL NEURAL NETWORKS” is good.

This study aims at determining a better approach for modeling asphalt adhesion damage using Artificial Neural Network (ANNs). Atomic Force Microscopy (AFM) test was deployed to determine the adhesion and cohesion forces of asphalt samples with varying contents of polymer and Antistripping Agents (ASAs). Two types of ANN models namely: Multilayer Perceptions (MLPs) and radial basis function neural network (RBFNN) were used in this effort. The analysis found that RBFNN was better suited for hierarchical models than MLP. The results of the study will be helpful for researchers and practitioners, working on pavement materials, for developing prediction models to prepare better mix design of polymer modified asphalt.

Some comments which greatly enhance the understanding of the paper and its value are presented below. Specific issues that require further consideration are:

1. The title of the manuscript is matched to its content but it is too long.
2. The Introduction generally covers the cases.
3. The methodology was clearly presented.
4. In the Reviewer’s opinion, the current state of knowledge relating to the manuscript topic has been presented, but the author's contribution and novelty are not enough emphasized.
5. Experimental program and results looks interesting and was clearly presented.
6. Please corrected  all drawings – the quality.
7. In the Reviewer’s opinion, the bibliography, comprising 36 references is representative.
8. An analysis of the manuscript content and the References shows that the manuscript under review constitutes a summary of the Author(s) achievements in the field.

In the Reviewer’s opinion the manuscript is well written, and it should be published in the journal after minor revision.

Author Response

Please see attachments.

Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript “BEHAVIORAL INVESTIGATION OF SINGLE WALL AND DOUBLE WALL CNT MIXED ASPHALT ADHESION FORCE USING CHEMICAL FORCE MICROSCOPY (CFM) SUPPORTED NANOTECHNOLOGY AND RBF ARTIFICIAL NEURAL NETWORKS” offers novel and interesting theme. Artificial neural network approach is actual and welcome in the experiments. Title and key words adequately describe the research presented in the manuscript. Abstract is brief, informative and covers all of the main information.

Introduction is also informative, well written and it covers all of the main researches in this area. Materials and methods are described in detail. Results and discussion chapter is logical and well described. Conclusions cover all of the main findings in the investigation. References are up to date. All of the tables and figures are necessary and cannot be omitted.

Overall manuscript is well written. Text should be reread on more time in order to remove all potential typing and formatting mistakes.

Author Response

Please see attachments. Thanks!

Author Response File: Author Response.pdf

Reviewer 3 Report

In this article, machine learning algorithms are used in an interesting topic. However, the manuscript contains several problems:

1. What is the new contribution of the present study? All machine learning methods used are existing methods. What is your purpose in comparing these algorithms with each other? Please explain them in more detail.
2. The quality of the figures and tables is low. To increase the quality of figures 3-8 and 9-11, it is recommended to use different colors and increase the size of the numbers.
3. Please add a paragraph in the introduction by relying on and citing important articles on the importance and benefits of machine learning algorithms. Important articles are as follows:

https://doi.org/10.1007/s11269-021-02913-4

https://doi.org/10.1007/S11600-020-00446-9

https://doi.org/10.3390/hydrology8010025

4.         Please add graphical abstract to the manuscript.

Author Response

Please have a look on attachments!

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Dear authors

Thank you for the response. Please check the manuscript one more time in order to remove all potential typing and formatting mistakes. Also, check the tables formats like Fig. 4.

Best regards

Author Response

Dear Reviewer,

Lots of thanks for your constructive review suggestions. We have incorporated all the comments and suggestion in the revised version of our paper (as attached). The language have been throughly revised to check possible typos and formatting issues. The figures and tables are now as per MDPI standards. All the changes are highlighted with Review Track Change options. Thanks again!

 

Author Response File: Author Response.doc