Structural Design and Parameter Optimization of Bionic Exhaust Tailpipe of Tractors

Round 1

Reviewer 1 Report

The authors did a simulation and experimental study on the various design parameters associated with bionic tailpipes. Noise reduction performance, including the transmission loss was calculated and optimized using a back propagation neural network. Both experimental and simulation study seems to be comprehensive in nature. However, the organization of the manuscript makes it difficult to understand the true potential of the manuscript. Below are a few comments to make the manuscript readable and improve he scientific quality:

 

1. It is suggested to reference the following patent, from the corresponding author of this study
   1. https://patents.google.com/patent/CN105484844A/en
2. Introduction:
   The research gap is not clearly highlighted. The reviewer is happy with the comprehensive review of the literature in the introduction section. However, the gap is not highlighted very well. E.g. Ref 21, a study by the authors of this study, it is not mentioned how this study improved on the existing Ref 21 study. Also, in Lines 84-92, when authors review optimization literature, it is not clear what was the missing components of the existing studies or how this study is different and perhaps better than what is available in literature. It is recommended to clearly highlight the benefits and novelties in the introduction section for clarity.
3. Experimental setup:
   1. Could authors expand on the wire cutting method to manufacture the bionic tailpipe, and the accuracy of this method?
   2. It might have been interesting to measure the sound pressure level of the source itself and compare with the output of the exhaust. Not sure if authors have this data.
4. Experimental verification results:
   1. Could authors clarify the reason for choosing an upper frequency of 2500 Hz? As a reader, I am interested in the typical frequency response of a tractor sound from tailpipe?
   2. Table 2: Can authors walk thought a sample calculation, it is not clear how these numbers are calculated? In reviewer’s opinion, the sound pressure level is dependent on the frequency as indicated in Figure 7 but the table mentions a single numerical value (independent of frequency).
   3. Table 2: Could the authors justify the significance of a 2dB difference in performance? This is less than 2% of the actual sound pressure level. In other words, could this be noise in the measurement and analysis? If authors can support their argument with error margin for data presented in Figure 9, that would bring clarity.
   4. Figure 8: As a reader, the reviewer is trying to understand why the performance of the bionic exhaust is better than prototype for 60 m/s and worse for 70 m/s (specially in the 2000-2500 Hz range)
5. Simulation study:
   1. The authors explain the detailed simulation framework. However, the reviewer could not find the validation of the simulation framework. Could the authors pls. comment on this?
   2. Along the same lines – what is the validity of the simulation results presented in Fig 10? It is perhaps better to have Fig. 10 just after Section 2.3.
6. Organization:
   1. The authors may want to put some of the figures to Appendix. E.g. Figure 10 is overwhelming for readers. The overall page count should be reduced, if possible.
   2. The organization of the manuscript should be improved. Currently, it is very confusing to the readers to an extent that some of the key points are somewhat lost. E.g.
      583. There is too much quantification in some paragraphs. Lines 552 to 583.
      584. The authors may want to try to smoothen the curve for better presentation, if it makes sense, scientifically. E.g. Fig 7.
   3. The graphics could also be improved to make a clear point across
      5. Line 329-330 and Fig 10: “As seen from the transmission loss curve of the prototype exhaust tail pipe, between 10 Hz and 50 Hz, the transmission loss is relatively high: between 5.288 dB and 19.745 dB.” This statement is not clear from Fig 10. There are similar examples elsewhere.
   4. Conclusion:
      1. The conclusion needs to be very specific and clear. E.g. lines 612-613 concludes that the sound pressure level is lowest for 50 m/s. However, it appears that its only true for a particular frequency band (from Fig. 7)
   5. The authors need to review the manuscript carefully for sentence formation and typos, some of them are:
      1. Line 121: the sentence seems incomplete.
      2. Line 128: ‘plus a reference’ reads a little informal. Pls. paraphrase.
      3. Line 151: The unit should be corrected to kg/(m^2.s)
      4. Line 155: variable ‘D’ is a typo.
      5. Lines 162-164: pls. ensure the font size for Greek letters are uniform

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

The paper investigates the design of inner shape of an exhaust tailpipe of tractors by simulations and experimental studies. The topic is very interesting. The bibliographic study is of great value. This study presents high valuable simulations with ANSYS Fluent, LMS and GA and also experimental results.

The paper is clear and well written and the presented results are consistent.

Some improvements are required :

In this paper, the authors investigate a triangular shape. It is an interesting geometry but rather simple and the ‘bionic’ term is the title looks overestimated.

Line 121 page 3: statements are missing: “satisfy is  _ _ _ _ [40]. _ _ _ _ _  is the “

In section 2.4.1, the authors should explain why the value of top angle and texture height do not cover the full range of the values presented in table 1. Moreover, in the conclusion, the authors explain that n is the most significant parameter. So why is this parameter taken as a constant in section 2.4.1?

Figure 8 is not the good one, it is the same as figure 7.

Section 3.2 presents the optimization of design parameters. The authors should provide more details on the GA exploited : population size, mutation rate, number de generations…

Once again, the optimization process only optimizes top angle and texture height and do not try to optimize the n value. Why? Other n values (22, 23, or 25) could give better results but it is not investigated.

Figure 11 is very confusing. The variables of the optimization process are presented to be top angle and height. So Figure 11a is a map in which the horizontal coordinates are the variables and the vertical is the transmission loss. This map is obtained by an analyzing process : z = f(x,y).

 Is there a third optimization variable to explain the difference between figure 11a and 11b? An explanation is required.

Figure 11 a exhibits high gradients related to the top angle . How do you explain such different results when top angle changes from 40 to 45 to 50…? It does not confirm that the “the top angle did not greatly change the tailpipe acoustic wave propagation”. Could it traduce instability in the simulations?

Moreover, the optimal point ( h=0.95 and angle = 61°  ) is located in at the bottom of a narrow cliff. Please provide the value of the associated: Transmission Loss (objective function). Such an optimal solution appears as not robust. Please give more explanations.

Please explain what ‘increase’ curve means in Figure 12.

Please update label of Figure 15.

Section 3.4 presents a too descriptive and long paragraph. Please synthetize and add analyses of results of figure 20 instead of a long basic description without added value.

End of figure 20 doesn’t appear, please update.

Results of figure 21 exhibits great instability of insertion loss. Is it realistic? Does it means that the insertion loss (less than 5 dB) is in fact negligible?

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Authors should use a unique bibliographic reference system. For example the IEEE system: [1], [2], [3-5]. The authors mix several bibliographic reference systems. For example, at line 33: Fu et al [1, 2]. On line 35, 38, 40, 42, etc., to the end of the paper.

Instead, in the Reference section, only the IEEE system appears.

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In the paper, why is any text highlighted in yellow?

Lines 71-76, lines 87-108, 135-138, line 167, 178-186, 437-439, 450-451, 465-466, 561-581, 603-606 and line 21 in References section.

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What is the thickness of the experimental specimen (fig 4)? On line 244, the authors say that the heights hs were 0.75 mm, 1.0 mm, and 1.25 mm. I suppose that the thickness must be greater than 1.25, but how much is it worth?

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In lines 267-268, the first time the authors measure the sound pressure level without the experimental specimen. The next time the authors measure the sound pressure level with the experimental specimen. Is my deduction true?

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The authors should indicate the main technical characteristics of the sound source, the sensor (microphone), the semi-anechoic chamber, the LMS analyzer and the power amplifier.

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In Figure 8 (b), in the legend, h= 1.5 mm appears. In line 244 this height does not appear.

In the graphs, are experimental or simulated the values shown?

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Table 1 shows data from the simulation. There appears citation = 90 and h=1.5. Authors should address this, as graphics lead to confusion.

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Have the authors thought about the possible accumulation of soot with the internal triangular texture that you propose?

 

Author Response

Comments and Suggestions for Authors

Authors should use a unique bibliographic reference system. For example the IEEE system: [1], [2], [3-5]. The authors mix several bibliographic reference systems. For example, at line 33: Fu et al [1, 2]. On line 35, 38, 40, 42, etc., to the end of the paper. Instead, in the Reference section, only the IEEE system appears.

Answer:

Thank you for your suggestions. We have revised the questions you raised in the revised draft.

In the paper, why is any text highlighted in yellow? Lines 71-76, lines 87-108, 135-138, line 167, 178-186, 437-439, 450-451, 465-466, 561-581, 603-606 and line 21 in References section.

Answer:

According to the reviewers’ round 1 comments, we have made great efforts to improve the quality of the manuscript. The main changes have been highlighted by yellow color in the revised manuscript.

What is the thickness of the experimental specimen (fig 4)? On line 244, the authors say that the heights hs were 0.75 mm, 1.0 mm, and 1.25 mm. I suppose that the thickness must be greater than 1.25, but how much is it worth?

Answer:

The thickness of the experimental specimen is 3mm. We have revised the questions you raised in the revised draft.

In lines 267-268, the first time the authors measure the sound pressure level without the experimental specimen. The next time the authors measure the sound pressure level with the experimental specimen. Is my deduction true?

Answer:

Dear expert, your deduction is correct. In the first test, we used the prototype exhaust tail pipe as the test object. And in the next test, we used the bionic texture exhaust tail pipe as the test object.

The authors should indicate the main technical characteristics of the sound source, the sensor (microphone), the semi-anechoic chamber, the LMS analyzer and the power amplifier.

Answer:

Thank you for your suggestions. The sound source working voltage was DC 3.7V and product power ≥25W. The 1/2" PCB sensor of American company has been used. Semi-anechoic chamber for noise testing provided low background noise environment to meet test requirements. LMS vibration and noise analyzer LMS Simcenter SCADAS was used for data collection. The type of power amplifier was Microlab M-200.

In Figure 8 (b), in the legend, h=1.5 mm appears. In line 244 this height does not appear. In the graphs, are experimental or simulated the values shown?

Answer:

The simulated values are shown in Figure 8 (b).

Table 1 shows data from the simulation. There appears citation θ=90° and h=1.5mm. Authors should address this, as graphics lead to confusion.

Answer:

Table 1 shows the dimension parameters of the bionic exhaust tail pipes during the simulation calculation. We have emphasized this in the revised draft.

Have the authors thought about the possible accumulation of soot with the internal triangular texture that you propose?

Answer:

Due to the existence of bionic texture, the drag reduction effect of the exhaust tail tube surface may be increased, so the accumulation of soot will not have a great impact. The following articles have mentioned the drag reduction effect of bionic triangular texture.

1. Hou Q.M., Yang X.F., Cheng J. Optimization of Performance Parameters and Mechanism of Bionic Texture on Friction Surface. Coatings. 2020, 10, 171. https://org/ 10.3390/coatings10020171.
2. Tian, G.Z., Zhang, Y.S., Feng, X.M., Hu, Y.S. Focus on Bioinspired Textured Surfaces toward Fluid Drag Reduction: Recent Progresses and Challenges. Eng. Mater. 2021, 2100696. https://doi:10.1002/adem.202100696.
3. Dean B., Bhushan B. Shark–skin surfaces for fluid–drag reduction in turbulent flow: a review. T. R. Soc. A. 2010, 368, 4775–4806. https://doi.org/10.1098/rsta.2010.0201.
4. Bixler, G.D., Bhushan, B. Fluid drag reduction and efficient self-cleaning with rice leaf and butterfly wing bioinspired surfaces. Nanoscale. 2013, 5, 7685. https://doi.org/10.1039/c3nr01710a.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors revised the manuscript and also provided response to my comments. I am happy with most of the responses but the three responses below are not satisfactory or additional work is needed:

 

1. Figure 7: As a reader, the reviewer is trying to understand why the performance of the bionic exhaust is better than prototype for 60 m/s and worse for 70 m/s (specially in the 2000-2500 Hz range)

I did not see a response to this comment. The authors responded that Fig. 8 was incorrect but a technical response to my comment is missing.

 

 

1. Table 2: Could the authors justify the significance of a 2dB difference in performance? This is less than 2% of the actual sound pressure level. In other words, could this be noise in the measurement and analysis? If authors can support their argument with error margin for data presented in Figure 9, that would bring clarity.

The response to this is unsatisfactory. The authors did not answer the noise in the measurements. There is no error bar in their measurements – could authors justify with any other arguments? What if the measurement error is +/-2dB – how would you justify 2dB change as significant? Please plan to add explanation to the manuscript as well.

 

2. From authors response on my comment on validation: “Since some of the boundary conditions are quite difficult to complete in actual experiments, this article has done a comparative verification in the experiment. By measuring and calculating the insertion loss, it is proved that the bionic tailpipe has a noise reduction effect compared with the prototype exhaust tail pipe.”

If so, then what is the need for sections that describe FEA and boundary conditions if they don’t add value to the manuscript. Can those sections be deleted to make manuscript easier to read?

Author Response

Comments and Suggestions for Authors

The authors revised the manuscript and also provided response to my comments. I am happy with most of the responses but the three responses below are not satisfactory or additional work is needed:

1. Figure 7: As a reader, the reviewer is trying to understand why the performance of the bionic exhaust is better than prototype for 60 m/s and worse for 70 m/s (specially in the 2000-2500 Hz range)

I did not see a response to this comment. The authors responded that Fig. 8 was incorrect but a technical response to my comment is missing.

Answer:

Thank you for your suggestions. The noise reduction performance of 70m/s is worse than 60m/s, mainly due to the increase of airflow velocity, which leads to the increase of airflow regeneration noise. The sound wave at high frequency propagates in the form of non-plane wave, which leads to more obvious airflow regeneration noise. Therefore, the performance of the bionic exhaust tail pipe is better at 60m /s than 70m/s especially in the 2000-2500 Hz range.

Table 2: Could the authors justify the significance of a 2dB difference in performance? This is less than 2% of the actual sound pressure level. In other words, could this be noise in the measurement and analysis? If authors can support their argument with error margin for data presented in Figure 9, that would bring clarity.

The response to this is unsatisfactory. The authors did not answer the noise in the measurements. There is no error bar in their measurements – could authors justify with any other arguments? What if the measurement error is +/-2dB – how would you justify 2dB change as significant? Please plan to add explanation to the manuscript as well.

Answer:

In the process of simulation calculation, the grid partition settings meet the requirements of simulation analysis. The grid division of computational aeroacoustics is shown in Fig. 3(a) and Fig. 3(b). To make accurate calculations, a hexahedral structural grid was used for mesh generation. The number of total grids of the prototype tailpipe is approximately 1,831,074, and that of the bionic tailpipe is approximately 7,000,000. In the calculation process of simulation analysis, the grid quality detection also meets the requirements, so the simulation calculation meets the requirements and will not cause a large error. Yu Liu et al. studied on noise reduction of a wavy multi-copter rotor, the attenuation of total sound pressure level of the wavy rotor with respect to the baseline rotor is about 1.4-2 dB [46]. Aerodynamic and acoustic investigations of multi-copter rotors with Trailing Edge serrations have been performed. The results suggested that the serrated rotor had an total sound pressure level attenuation of 0.9-1.6 dB [47,48]. The noise reduction effect through leading edge serrations was studied on two dimensional airfoils, and alleviate the total sound pressure level of 1.5 dB [49]. Therefore, the role played by the bionic exhaust tail pipe in this paper has achieved a significant effect in aeroacoustics. The explanation has been added to the manuscript.

46. Yang Y.N., Liu Y, Hu H.T. Experimental study on noise reduction of a wavy multi-copter rotor. Acoust. 2020, 165:107311. https://doi.org/10.1016/j.apacoust.2020.107311.
47. Ning Z., Wlezien R.W., Hu Hui. An Experimental Study on Small UAV Propellers with Serrated Trailing Edges. 47th AIAA Fluid Dynamics Conference, Denver, Colorado, 2017. https://doi.org/10.2514/6.2017-3813.
48. Lee H.M., Lu Z.B., Lim K.M., Xie J.L., Lee H.P. Quieter propeller with serrated trailing edge. Acoust. 2019,146, 227–236. https://doi:10.1016/j.apacoust.2018.11.02.
49. Agrawal B.R., Sharma A. Numerical analysis of aerodynamic noise mitigation via leading edge serrations for a rod-airfoil configuration. J. Aeroacoust. 2016;15 734–756. https://doi.org/10.1177/1475472X16672322.
50. From authors response on my comment on validation: “Since some of the boundary conditions are quite difficult to complete in actual experiments, this article has done a comparative verification in the experiment. By measuring and calculating the insertion loss, it is proved that the bionic tailpipe has a noise reduction effect compared with the prototype exhaust tail pipe.”

If so, then what is the need for sections that describe FEA and boundary conditions if they don’t add value to the manuscript. Can those sections be deleted to make manuscript easier to read?

Answer:

Thank you for your valuable advice. If the part describing FEA and boundary conditions is deleted, it will be impossible to form the comparison verification between simulation and experiment, which will cause the loss of the integrity of the paper. Therefore, this paper may be useful to preserve this part for consideration.

 

Author Response File: Author Response.docx

Reviewer 2 Report

I'm afraid not to have understood the objective function and variables of your optimization process.

Author Response

Comments and Suggestions for Authors

I'm afraid not to have understood the objective function and variables of your optimization process

Answer:

Thank you for your suggestions. In this paper, the effect of noise reduction is optimized by optimizing the structural parameters of bionic texture. The noise reduction effect is measured by transmission loss, so the objective function in the optimization process is transmission loss, the variables are parameters of bionic texture. To increase the transmission loss, The Genetic Algorithms (GA) optimized Back-Propagation neural network (BP) was used to optimize the bionic triangular convex texture parameters.

Author Response File: Author Response.docx

Round 3

Reviewer 2 Report

The optimization process is a key issue in your paper (it apperas in the title) so it has to be very clear for the readers.

Thank you for having explained what is the objective function.

Now could you please precisely detail the list of the variables of the optimization problem (parameters of bionic texture)?

Author Response

Comments and Suggestions for Authors

The optimization process is a key issue in your paper (it apperas in the title) so it has to be very clear for the readers.

Thank you for having explained what is the objective function.

Now could you please precisely detail the list of the variables of the optimization problem (parameters of bionic texture)?

Answer:

Thank you for your suggestions. We have revised the questions in the revised draft.

In the process of transmission loss of tractor bionic exhaust tail pipes optimization, since the fitting function has two input parameters and one output parameter, the transmission loss (TL), top angle θ and texture height h were selected for BP neural network optimization analysis based on genetic algorithm optimization. The variables listed are shown in Table 3. During the optimization process, the input parameters are the bionic texture include top angle θ and texture height h and the maximum transmission loss is the output parameter.

Author Response File: Author Response.docx