Sequential Design-Space Reduction and Its Application to Hull-Form Optimization

Round 1

Reviewer 1 Report

It is an interesting paper. The authors use existing decision theory of rough sets to carry out reduction of th design space necessary n ship optimization, especially when the evaluation is carried out using CFD.

They should just add some infoabout the parameters used in their CFD evaluation of the two tst cases referring to hull forms.

No comments. Minor editing errors.

Author Response

It is an interesting paper. The authors use existing decision theory of rough sets to carry out reduction of th design space necessary n ship optimization, especially when the evaluation is carried out using CFD.

They should just add some infoabout the parameters used in their CFD evaluation of the two tst cases referring to hull forms.

Reply: Thanks for your careful work and thoughtful suggestions that have helped improve this paper substantially. The computational domain is 1 time the length (Lpp) in width，0.5 times the length in height forward of the bow and 1.2 times the length in height behind the stern. There are a total of 7783 surface elements in the mesh of the free surface and hull surface. Figure 12 shows the hull surface and free flow surface element mesh. It is modified in the article.

 

Figure 12 Hull surface and free flow surface element mesh

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

The title of the paper deals with ship optimization but in fact the examples only deal with hull shape optimization. So at least the title needs to be adjusted.

The reference list is too limited and does not contain important referenced. Even limiting only to the hull, there are aspects of hull compartmentation hat affect hull shape:

https://doi.org/10.1016/j.oceaneng.2020.107846

Chapter 2 appears that has no need in dividing in two subsections as the first one is too short

 

In the example of application of CFD, the results do not appear to be done after a mesh sensitivity study has concluded that the mesh used is appropriate

Author Response

The title of the paper deals with ship optimization but in fact the examples only deal with hull shape optimization. So at least the title needs to be adjusted.

Reply: Thanks for your careful work and thoughtful suggestions that have helped improve this paper substantially. The title of the paper is modified as “Sequential design-space reduction and its application to hull form optimisation”.

 

The reference list is too limited and does not contain important referenced. Even limiting only to the hull, there are aspects of hull compartmentation hat affect hull shape:

https://doi.org/10.1016/j.oceaneng.2020.107846

Reply: We have added some references in the article.

 

Chapter 2 appears that has no need in dividing in two subsections as the first one is too short

Reply: We have combined the two subsections. It is modified in the article.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors have chosen an interesting topic regarding the ship hull optimization which can be suitable for enhancing hydrodynamic performance of ships and reduce their wave making resistance. The research subject has a considerable importance since it can provide a good solution for reducing ship total resistance and consequently the power required plus it can help in the reduction of ship emissions.

The effort done by the authors is considerably significant and the final CFD simulations have a massive number, which can show the amount of work done by the authors to achieve the contents of the introduced manuscript. However, the data and the concept of the study presentation does not serve the work properly. Here are some comments, from my point of view, that can enhance the quality of the manuscript:

1. The abstract misses important details, since no information regarding the study outcome were provided;

2. The literature review is insufficient and requires more details regarding the previous work, more details regarding the previous research strategies and their pros and cons, and finally, how the current study differs or matches those researches;

3. In sections 2 and 3, authors give significant amount of explanation about the methodology with massive information that causes a little confusion regarding the methodology. I believe these two sections can be summarized to focus on the main idea of the method, and all the other details can be waved to an appendix;

4. The data arrangement causes other confusion, since the figures and tables are usually quoted after their presence in the manuscript, or sometimes not mentioned absolutely in the text (such as Fig.6);

5. The authors stated that the optimization process in case 1, though it reduces the wave making resistance with 9.7%; still, the reduction on the total resistance is within 0.4% (and since the other cases do not differ much on the reduction percentage which is within 10%), this poses some doubts regarding the feasibility of the optimization process compared to the significant cost included in the large number of the CFD studies performed; 

6. in section 4.3.4. the comparative analysis could have been highlighted better with a chart or diagram showing the comparison between the three concepts and their outcomes;

7. the conclusion has nothing significant but some phrases combined from the abstract and introduction, No details about the study's outcome or real conclusions. I propose that it should be rewritten;

8. Though it might be the editors' concern point; however, the referencing in the manuscript does not comply to the rules of the journal. No numbering for the references was used. Plus some technical errors for mentioning some methodologies and equations by other researchers without referring to the corresponding references.

 

 

The manuscript is readable, comprehensible and easy to follow except for some minor grammatical and technical mistakes that should be modified. Plus, there were a lot of long phrases that need to be reformulated to eliminate any possible confusions.

Author Response

The authors have chosen an interesting topic regarding the ship hull optimization which can be suitable for enhancing hydrodynamic performance of ships and reduce their wave making resistance. The research subject has a considerable importance since it can provide a good solution for reducing ship total resistance and consequently the power required plus it can help in the reduction of ship emissions.

The effort done by the authors is considerably significant and the final CFD simulations have a massive number, which can show the amount of work done by the authors to achieve the contents of the introduced manuscript. However, the data and the concept of the study presentation does not serve the work properly. Here are some comments, from my point of view, that can enhance the quality of the manuscript:

Reply: Thanks for your careful work and thoughtful suggestions that have helped improve this paper substantially.

1. The abstract misses important details, since no information regarding the study outcome were provided;

Reply: The results were compared to those of direct optimisation and one-time design space reduction, thus proving the feasibility of this method. It is added in the abstract.

 

2. The literature review is insufficient and requires more details regarding the previous work, more details regarding the previous research strategies and their pros and cons, and finally, how the current study differs or matches those researches;

Reply: Gammon [1] used a multi-objective genetic algorithm to perform multi-objective opti-misation of the resistance performance, seakeeping performance, and stability of fish-ing boats. Feng et al. [2,3] used the potential flow method to optimise the resistance performance of a variety of hull forms. Cheng et al. [4] used Shipflow to optimise S60 hull form. Serani et al. [5] optimise the hull form of the DTMB 5415 model to reduce the resistance for Fn (Froude number) = 0.25. Yang et al. [6] used response surface models and multi-objective optimisation algorithms. Kim and Yang [7] used Radial Ba-sis Function (RBF) to vary the hull forms during the optimisation process. Zhang et al. [8,9] presents a ship hull form optimization loop using the surrogate model to reduce the wave-making resistance of the Wigley ship. Jafaryeganeh et al. [10] applied mul-ti-objective genetic algorithm to deal with the optimization of the internal layout oil tankers under uncertainties. Feng et al. [11] selected Wendland ψ3,1 function as Basis functions of RBF interpolation, and the modification method is used to optimise a tri-maran model.

In hull form optimisation, techniques such as parametric hull surface modification and CFD numerical simulation and optimisation are directly used to obtain optimal ship designs that satisfy a given set of constraints. However, considering hull form op-timisation is a complex engineering problem, it involves several numerical simulations and has a complex design-performance space. Consequently, the hull form optimisa-tion process is highly inefficient, making it difficult to determine the global optimum. The most commonly used approaches to solve these problems are as follows:

1) High-efficiency optimisation algorithms: The approach is used to develop an algorithm that can determine the global optimum using a small number of iterations. 2) Approximate modelling: This method uses a set of numerically simulated samples to construct an approximate model that can replace CFD computations, significantly re-ducing computational costs. 3) Using high-performance computing clusters: Modern computing hardware and parallel computing technologies can be used to increase computational speed and decrease computing time [12].

Although significant progress has been made in the aforementioned techniques, their efficiency and the quality of the resulting solutions are insufficient for practical application.

It is modified in the article.

3. In sections 2 and 3, authors give significant amount of explanation about the methodology with massive information that causes a little confusion regarding the methodology. I believe these two sections can be summarized to focus on the main idea of the method, and all the other details can be waved to an appendix;

Reply: We have carefully revised the sections 2 and 3 of the article. Relevant information is shown in article and appendix 1-2.

 

4. The data arrangement causes other confusion, since the figures and tables are usually quoted after their presence in the manuscript, or sometimes not mentioned absolutely in the text (such as Fig.6);

Reply: We have modified in the article.

 

5. The authors stated that the optimization process in case 1, though it reduces the wave making resistance with 9.7%; still, the reduction on the total resistance is within 0.4% (and since the other cases do not differ much on the reduction percentage which is within 10%), this poses some doubts regarding the feasibility of the optimization process compared to the significant cost included in the large number of the CFD studies performed;

Reply: 1. The KCS is a good performance ship, and it is difficult to achieve a significant reduction in total resistance. 2. The displacement of all optimized hull form increased, and the wet surface area also increased with the growth of the bulbous bow, which made the total drag reduction effect not obvious. 3. The optimized speed is low, and the proportion of wave-making resistance is relatively small. These are the reasons for the above phenomenon. However, the proposed method can save large amount of computation.

 

6. in section 4.3.4. the comparative analysis could have been highlighted better with a chart or diagram showing the comparison between the three concepts and their outcomes;

Reply: The table 13 shows the comparison between the three CASE. All optimal ships from Cases 1–3 (see Table 13) showed approximately a 10% de-crease in the wave-making resistance. Therefore, we can conclude that the effective-ness of hull form optimisation was roughly the same in all three cases. In terms of effi-ciency, Case 1 required 1000 CFD calculations, the highest of all cases. Case 2 required a total of 346 CFD calculations, considering the optimisations were performed imme-diately after one reduction. Multiple reductions were performed in Case 3, reducing the total number of CFD calculations to 113 (the lowest of all cases). Therefore, hull form optimisation was least efficient in Case 1 and most efficient in Case 3. Therefore, using SDSR in hull form optimisation gives the same optimisation efficacy while sig-nificantly reducing the computational cost. It was modified in article.

	Y2/m	Y3/m	Y4/m	Y5/m	X1/m	Z1/m	Rw/N	Improvement in wave-making resistance	Number of CFD calculations
CASE1	0.0836	0.1057	0.1411	0.2587	-0.0785	0.2265	11.048	-9.71%	1000
CASE2	0.0850	0.1060	0.1450	0.2602	-0.0633	0.2350	10.976	-10.30%	346
CASE3	0.0850	0.1060	0.1450	0.2550	-0.0689	0.2350	10.999	-10.12%	113

Table 13. Comparison between the optimal solutions from Cases 1 – 3.

 

 

7. the conclusion has nothing significant but some phrases combined from the abstract and introduction, No details about the study's outcome or real conclusions. I propose that it should be rewritten;

Reply: Hull form optimisation is an effective method for improving ship speeds and cost efficiency, making it an important tool for green ship design. With the advent of hull surface modification techniques, CFD numerical simulations, optimisation techniques, and continuously improving computing hardware, CFD-based hull form optimisation has become very common. However, this approach exhibits significant practical flaws owing to its low computational efficiency and difficulty in identifying the global opti-mum. To solve these issues, this study proposed the RST-based SDSR technique that uses interval theory to compute the intersections and unions of the sub-design spaces. Furthermore, a suitable stopping criterion for hull form optimisation was proposed to facilitate the application of RST-based SDSR to hull form optimisation problems. Lastly, a KCS model was optimised using our method to minimise wave-making resistance. The results were then compared to those of direct optimisation and one-time design space reduction, thus proving the feasibility of our method. Cases 1–3 showed ap-proximately a 10% decrease in the wave-making resistance. In terms of efficiency, di-rect optimisation (Cases 1) required 1000 CFD calculations. One-time design space re-duction (Case 2) required a total of 346 CFD calculations. Multiple reductions (Case 3), reducing the total number of CFD calculations to 113 (the lowest of all cases). There-fore, hull form optimisation was least efficient in Case 1 and most efficient in Case 3. Therefore, using SDSR in hull form optimisation gives the same optimisation efficacy while significantly reducing the computational cost. It was modified in article.

 

8. Though it might be the editors' concern point; however, the referencing in the manuscript does not comply to the rules of the journal. No numbering for the references was used. Plus some technical errors for mentioning some methodologies and equations by other researchers without referring to the corresponding references.

Reply: We have modified in the article.

 

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The paper has been improved

Reviewer 3 Report

The authors covered the proposed comments. 

English Language is comprehensible easy to follow.