Optimized Design of Large-Body Structure of Pile Driver Based on Particle Swarm Optimization Improved BP Neural Network
Round 1
Reviewer 1 Report
In this article, the authors use BP NN and PSO to optimize parameters related to thickness of steel sheets used in the construction of the large body structure of the YZY400 hydraulic static pile driver. to do so they created a parametric model and used Finite Element Analysis.
The results indicate 22.1% reduction of mass.
I have a couple of minor comments:
1. related work part is very short
2. few English related issues one of them is line 354.
The concerning point is, I found that the authors have published another articles that has mush the same content as this one. the article is:
Optimization of Pile Driver Frame Based on Sensitivity Analysis
by Jinmei Wu *,Yanqing Yang * andJiameng Hu
the results of the published article seem to be better as the mass was reduced to 64,282.6 kg while it is 65064 KG here.
Diagrams and tables are similar. the paper is cited in this article.
I would like to see a proper justification on how the two articles are different and why would anyone use the results in this article while another article provided better results.
minor issues, needs to be reviewed.
Author Response
Dear Reviewer,
We feel great thanks for your professional review work on our article. As you are concerned, several problems need to be addressed. According to your nice suggestions, we have made extensive corrections to our previous draft. A point-by-point response to every comment put forward is provided as follows:
Point 1: The related work part is very short.
Response 1: We think this is an excellent suggestion. We have added a subsection to illustrate the application of the Particle Swarm Optimization algorithm and also to complement the optimization results of the Particle Swarm Optimization algorithm. It is in lines 335-357 and 409-421 of the manuscript, respectively; We have added the basis for constructing the BP neural network node data, added a description of the method, and added plots of the predicted versus actual values of the BP neural network in Figures 10, 11, and 12 to illustrate its effectiveness. They are reflected in lines 373-377, 383-384, and 389-400 of the manuscript, respectively.
Point 2: Few English related issues one of them is line 354.
Response 2: We appreciate the reviewer for raising this important point. We have corrected errors in line 354 of the original manuscript and lines 401-404 of the revised manuscript. We have checked and corrected the English expressions throughout the manuscript. Please see the highlighted sections of the revised manuscript and the revision notes.
Point 3: How the two articles are different and why would anyone use the results in this article while another article provided better results.
Response 3: We appreciate the reviewer for raising this important point. ​In this paper, we want to investigate the application of intelligent optimization algorithms to optimal structure design. The role of BP neural networks in structural optimization is explored by comparing the optimization results of the two algorithms. In the two articles we present two different sets of optimized design schemes. ​The optimized design scheme presented in this paper can be used not only for the optimized design of hydraulic static pile drivers, but also for similar mechanical products. ​We make a note of this in the manuscript, in lines 96-100, 444-449, and 455-456.
We have added some research background in the introduction section of the manuscript and in lines 77-87 of the revised manuscript. ​Several references have been added and corrected, see the references section of the revised manuscript. We have revised the conclusions, which are in lines 458-462 of the manuscript.
We tried our best to improve the manuscript and have made some changes marked in yellow in the revised manuscript. We sincerely appreciate the warm work of the editors/reviewers and hope that the correction will be approved. Again, thank you very much for your comments and suggestions.
Kind regards，
Ms. Hu
Author Response File: 
Author Response.docx
Reviewer 2 Report
· The paper (applsci-2407351 entitled ‘Optimized Design of Large Body Structure of Pile Driver Based on Particle Swarm Optimization Improved BP Neural Network’) covered the APDL parametric design language provided by ANSYS to build a large-body structural geometry model of a hydrostatic pile driver and perform a static analysis of its finite element model. All the terminology and variables defined and measured properly. The study methods are up-to-date valid and reliable, and data represented properly. The conclusions seem to have answered the aims of the study. The paper has potential to be published.
However, there are some points that needs to be taken into consideration as follows. Please:
· Writing should definitely be improved. Abstract has many problems I believe. Please do not start to paper with a inverted sentence. Instead abstract should be starting with ……. Is important ( a few of general sentences). In this paper, …. Was …ed. In the last sentence of the abstract, give the main results.
· Remove the dot in line 8 page 1 before in this paper.
· Do not use ‘ in the paper.
· So many in this paper, we used. Just use one in the end of abstract, that would be more than enough. If you use we use it would be simple present tense, you used a methodology that is why it should b ewe used or …. Was used.
· Writing should be improved greatly.
· Modify Figure 4. Nothing is readable in the figure as the texts are too small to read.
· Figure 5 and 6. Remove the frames in figures.
· Keep tables 1 and 4 in the same page.
· Conclusion. …. Was used, …. Was solved. Abstract has many problems I believe. Please do not start to paper with a inverted sentence. Instead abstract should be starting with ……. Is important ( a few of general sentences). In this paper, …. Was …ed. In the last sentence of the abstract, give the main results.
· Remove the dot in line 8 page 1 before in this paper.
· Do not use ‘ in the paper.
· So many in this paper, we used. Just use one in the end of abstract, that would be more than enough. If you use we use it would be simple present tense, you used a methodology that is why it should b ewe used or …. Was used.
· Writing should be improved greatly.
· Modify Figure 4. Nothing is readable in the figure as the texts are too small to read.
· Figure 5 and 6. Remove the frames in figures.
· Keep tables 1 and 4 in the same page.
· Conclusion. …. Was used, …. Was solved.
Writing should definitely be improved.
Author Response
Dear Reviewer,
We feel great thanks for your professional review work on our article. As you are concerned, several problems need to be addressed. According to your nice suggestions, we have made extensive corrections to our previous draft. A point-by-point response to every comment put forward is provided as follows：
Point 1: Writing should definitely be improved. Abstract has many problems; the abstract should be starting with ……. Is important (a few of general sentences); in the last sentence of the abstract, give the main results.
Response 1: We think this is an excellent suggestion. We have revised the beginning of the abstract and given the main conclusions at the end of the abstract, see lines 8-19 of the revised manuscript; ​We have checked and corrected grammatical issues throughout the paper. Please check the revision log.
Point 2: Remove the dot in line 8 page 1 before in this paper.
Response 2: ​Thank you for raising this issue. We have fixed this error, see lines 8-9 of the revised manuscript.
Point 3: Do not use ‘in the paper’.
Response 3: We think this is an excellent suggestion. ​We have corrected 'in the paper' throughout, see the manuscript for details.
Point 4: Just use one ‘was used’ in the end of abstract, ​the 'use' should be changed to 'used’.
Response 4: We appreciate the reviewer for raising this important point. We checked the English tense issue and made corrections and reduced the use of 'we used', see the abstract of the revised manuscript (lines 8-19).
Point 5: Writing should be improved greatly.
Response 5: Thank you for this very important advice. We have made careful corrections to English grammatical issues throughout the text. Please see the revision log for the revised manuscript.
Point 6: Modify Figure 4. Nothing is readable in the figure as the texts are too small to read.
Response 6: We appreciate the reviewer for raising this important point. We have replaced the figures with clearer ones, please see Figure 4 in the revised manuscript.
Point 7: Figure 5 and 6. Remove the frames in figures.
Response 7: ​Thank you so much for this suggestion. ​We remove the boundaries of Figs. 5, 6, and 3. Please see the figures in the revised manuscript.
Point 8: Keep tables 1 and 4 in the same page.
Response 8: We have placed Tables 1 and 4 on the same page. Please check the tables of the revised manuscript.
Point 9: Conclusion. …. Was used, …. Was solved.
Response 9: We appreciate the reviewer for raising this important point. ​We have fixed grammatical issues in the conclusions, see lines 451-466 of the revised manuscript.
We have added some research background in the introduction section of the manuscript and lines 77-87 of the revised manuscript. ​Several references have been added and corrected, see the references section of the revised manuscript. We have added the basis for constructing the BP neural network node data, added a description of the method, and added plots of the predicted versus actual values of the BP neural network in Figures 10, 11, and 12 to illustrate its effectiveness. They are reflected in lines 373-377, 383-384, and 389-400 of the manuscript, respectively. In addition, we have added a subsection to illustrate the application of the Particle Swarm Optimization algorithm and also to complement the optimization results of the Particle Swarm Optimization algorithm. It is in lines 335-357 and 409-421 of the manuscript, respectively.
We tried our best to improve the manuscript and have made some changes marked in yellow in the revised manuscript. We sincerely appreciate the warm work of the editors/reviewers and hope that the correction will be approved. Again, thank you very much for your comments and suggestions.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
Reviewer 3 Report
The authors present the study of the large-body structure of the YZY400 hydrostatic pile driver. The applied model and optimization procedure allowed to reduce the weight of the structure by 21%.
I do not fully understand what the authors wanted to convey in this work. Why is this particular research object interesting? I miss the reference to the results from work [12], where exactly the same mass reduction result was obtained.
The authors consider only static loads. And what about the resistance of the structure to cyclic changes and material fatigue?
Economic effects are to be an argument for successful optimization. Will the resulting model actually be cheaper to produce? Reducing weight does not necessarily go hand in hand with facilitating the manufacturing process. Especially since the pile driver already in use is being studied, which should already be optimized in terms of durability and production.
The descriptions in the figures are illegible.
Therefore, I cannot give a positive opinion of this work for publication.
Author Response
Dear Reviewer,
We feel great thanks for your professional review work on our article.
We added a subsection to study the application of particle swarm optimization algorithm in the optimization process of pile driver, and also added the optimization results of particle swarm optimization algorithm to compare with the optimization results of BP neural network based on particle swarm improvement, in order to study the role of BP neural network in the optimization design of mechanical structures. In lines 335-357 and 409-421 of the revised manuscript, respectively.
We have responded to your query as follows:
1. What the authors wanted to convey in this work? Why is this particular research object interesting?
We appreciate the reviewer for raising this important point. As a machine commonly used in construction, we believe that the hydraulic static pile driver needs to be continuously optimized to meet not only the changing working conditions, but also the evolving needs of the machinery industry. The focus of this paper is not only on the lightweight design of pile drivers, but also, and importantly, we would like to further investigate the application of BP neural networks in the optimization of mechanical structures by comparing the optimization results of the two algorithms. In this paper, we propose an optimization scheme not only for the optimal design of pile presses but also for different mechanical products. This we explain in lines 93-98, 444-449, 458-462, and 465-466 of the revised manuscript.
2. What about the resistance of the structure to cyclic changes and material fatigue?
We appreciate the reviewer for raising this important point. ​The focus of our study in this paper is more on the comparison of the two optimization algorithms applied to the optimal design of the structure and the BP neural network application, and we next analyze the dynamic harmonic response of the structure.
3. Economic effects are to be an argument for successful optimization. Will the resulting model actually be cheaper to produce? Reducing weight does not necessarily go hand in hand with facilitating the manufacturing process. Especially since the pile driver already in use is being studied, which should already be optimized in terms of durability and production.
​We believe that the lightweight design of the structure can reduce the cost of production to a certain extent by reducing the use of materials, thus allowing the machinery manufacturer to save some costs for more profit. ​The pile driver already in use definitely meets the design requirements, but as the machinery industry changes, additional optimization of it becomes a possibility, and only continuous improvements can adapt to industry and economic requirements.
4. The descriptions in the figures are illegible.
We think this suggestion is spot-on. We have replaced the figure with a clearer one, so please check the revised manuscript.
We have added some research background in the introduction section of the manuscript and in lines 77-87 of the revised manuscript. ​Several references have been added and corrected, see the references section of the revised manuscript. We have revised the conclusions, which are in lines 458-462 of the manuscript. We have added the basis for constructing the BP neural network node data, added a description of the method, and added plots of the predicted versus actual values of the BP neural network in Figures 10, 11, and 12 to illustrate its effectiveness. They are reflected in lines 373-377, 383-384, and 389-400 of the manuscript, respectively.
We tried our best to improve the manuscript and have made some changes marked in yellow in the revised manuscript. We sincerely appreciate the warm work of the editors/reviewers and hope that the correction will be approved. Again, thank you very much for your comments and suggestions.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
Reviewer 4 Report
This manuscript was written well. The results can be valuable for the design of large body structure of pile driver. I support publication with only minor revisions:
1. In figure 4, the font size needs to be enlarged to increase the readability.
2. Figures 9-11, a magnification of the plot showing the initial number of iterations will be helpful to the readers.
Author Response
Dear Reviewer,
We feel great thanks for your professional review work on our article. ​Many thanks for your recognition of our work. According to your nice suggestions, we have made extensive corrections to our previous draft. A point-by-point response to every comment put forward is provided as follows:
Point 1: In figure 4, the font size needs to be enlarged to increase the readability.
Response 1: We appreciate the reviewer for raising this important point. We have replaced the figures with clearer ones, please see Figure 4 in the revised manuscript.
Point 2: Figure 9-11 should show a magnified view of the initial number of iterations.
Response2: ​Thank you for raising this issue. ​We have changed the sizes of the original Figures 9-11, see Figures 14-16 of the revised manuscript.
We have added some research background in the introduction section of the manuscript and in lines 77-87 of the revised manuscript. ​Several references have been added and corrected, see the references section of the revised manuscript. We have revised the conclusions, which are in lines 451-466 of the manuscript. We have added the basis for constructing the BP neural network node data, added a description of the method, and added plots of the predicted versus actual values of the BP neural network in Figures 10, 11, and 12 to illustrate its effectiveness. They are reflected in lines 373-377, 383-384, and 389-400 of the manuscript, respectively.
We tried our best to improve the manuscript and have made some changes marked in yellow in the revised manuscript. We sincerely appreciate the warm work of the editors/reviewers and hope that the correction will be approved. Again, thank you very much for your comments and suggestions.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
Thank you for the update.
Numerous words and sentences have been altered in the latest version. I believe the paper requires thorough reading and careful editing. In several instances, the previous version was preferable, such as when "high-rise" was changed to "tall-rise".
Numerous words and sentences have been altered in the latest version. I believe the paper requires thorough reading and careful editing. In several instances, the previous version was preferable, such as when "high-rise" was changed to "tall-rise".
Author Response
Dear Reviewer,
Thank you very much for your time in reviewing the manuscript and your encouraging comments on the merits.
Based on your suggestions, we read the article and carefully edited the complete text, and "tall-rise" was changed to "high-rise". Please check the revised latest manuscript.
We have changed references that are not entirely related to the article, so please check the references of the latest manuscript.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
Reviewer 2 Report
Thank you for following my recommendations. The writing of the paper has been improved many thanks. I am glad that the text size in the subfigures of Figure 4 have been increased, which makes the cations and the figure clearer. Page 8, line 205: please combine the very short paragraph with other paragraphs as an academic paragraphs should normally have max 500 words, while min 250 words. Table 7 clarifies the differences after the optimisation, well done for adding this table. Please combine the two paragraphs following Table 7 together. Conclusion is a lot clearer now.
I personally think that the manuscript quality increased remarkably after the previous review. For this reason, I recommend accepting the manuscript as it is and no further changes should be required.
Author Response
Dear Reviewer,
Thank you very much for your time reviewing the manuscript and encouraging comments on the merits. A point-by-point response to every comment put forward is provided as follows：
Point 1: Page 8, line 205: combine the very short paragraph with other paragraphs.
Response 1: We really appreciate the advice you gave. We have merged the shorter paragraph of line 205 into its previous paragraph. See lines 195-197 of the latest manuscript.
Point 2: Combine the two paragraphs following Table 7 together.
Response 2: ​We think this advice of yours is essential. We have combined the two paragraphs below Table 7 into one paragraph. See lines 405-412 of the latest manuscript.
To better respond to the valuable comments made by the reviewers, we have read the manuscript throughout and made some corrections in addition to the changes mentioned above, which do not affect the overall effect of the article.
Thank you again for your recognition of our work. Your encouragement and affirmation are our motivation to continue our research.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
Reviewer 3 Report
The authors introduced the necessary corrections to the manuscript, so I see no objections to publication.
Author Response
Dear Reviewer,
Thank you for your recognition of our work. Your encouragement and affirmation are our motivation to continue our research.
To better respond to the valuable comments made by the reviewers, we have read the manuscript throughout and made some corrections, which do not affect the overall effect of the article. Please check the latest manuscript.
Kind regards，
Ms. Hu
Author Response File: Author Response.docx
