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Peer-Review Record

Identification of Acoustic Characteristic Parameters and Improvement of Sound Absorption Performance for Porous Metal

Metals 2020, 10(3), 340; https://doi.org/10.3390/met10030340
by Xiaocui Yang 1, Xinmin Shen 2,3,*, Haiqin Duan 2, Xiaonan Zhang 2 and Qin Yin 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Metals 2020, 10(3), 340; https://doi.org/10.3390/met10030340
Submission received: 26 January 2020 / Revised: 18 February 2020 / Accepted: 2 March 2020 / Published: 3 March 2020

Round 1

Reviewer 1 Report

While this is the first time that I have come across the use of the cuckoo search algorithm, there is little novelty in either the acoustical science or conclusions in the paper. 
The emphasis on flow resistivity and porosity misses the potentially important roles of tortuosity and/or effective compressibility.
The effectiveness of perforated coverings for improving the absorption of thin porous layers has been well known for decades. There are more fundamental 'bottom-up' microstructural approaches that could have been used or considered. The authors would benefit from studying the following references: 
F Chevillotte, C, Perrot, R. Panneton, Microstructure based model for sound absorption predictions of perforated closed-cell metallic foams. J. Acoust. Soc. Am. 128 1766 –76 (2010)
C. Perrot, F. Chevillotte, R. Panneton, Bottom-up approach for microstructure optimization of sound absorbing materials, J.
Acoust. Soc. Am. 124 (2008) 940–948
J. H. Park, S. H. Yang, H. R. Lee, C. B. Yu, S. Y. Pak, C. S. Oh, Y. J. Kang, J. R. Youn, Optimization of low frequency sound absorption by cell size control and multiscale poroacoustics modeling, J. Sound Vib. 397 (2017) 17–30.

The use of English would benefit from thorough editing.

Two specifically recommended changes are:
vertical axis labels in Fig.6 should be 'Sound Absorption Coefficient'
line 352 'theoretical data' should be replaced by 'predictions', 'simulation data' should be replaced by 'simulation results'. The term 'data' should be used to refer only to experimental data.

 

 

  

 

Author Response

Response to reviewer 4’s comments
Summary: While this is the first time that I have come across the use of the cuckoo search algorithm, there is little novelty in either the acoustical science or conclusions in the paper. 


Response:
Thank you very much for your kind comments.
Identification of acoustic characteristic parameters and improvement of sound absorption performance for porous metal were conducted by cuckoo search algorithm in this research, which achieved the optimal composite sound absorbing structures with tiny increase in occupied space and few addition in weight. Accuracy and effectiveness of the cuckoo search identification and optimization algorithm were certified by finite element simulation and standing wave tube measurement. The improved sound absorption performance would be favorable to promote practical application of the optimal composite structures in the fields of sound absorption and noise reduction.
Corresponding modifications had been conducted in the revised paper according to your comments, which we wished to meet your requirements.

 


Point 1: The emphasis on flow resistivity and porosity misses the potentially important roles of tortuosity and/or effective compressibility.


Response 1: 
Thank you so much for your kind inquiry.
In this study, sound absorption performance of the porous metal was analysed based on the Johnson–Champoux–Allard model, from which it could be found that the major influencing factors were porosity and static flow resistivity. Therefore, these two parameters were identified in this study.
We agreed with you that missing of the tortuosity, effective compressibility, and other characteristics would make the constructed theoretical sound absorption model have some deviations with the actual experimental data.
Therefore, in future study, we would take the other characteristics (such as tortuosity, effective compressibility, characteristic viscous length and thermal length, and so on) into consideration, which aimed to construct the theoretical sound absorption model with higher accuracy.

 


Point 2: The effectiveness of perforated coverings for improving the absorption of thin porous layers has been well known for decades. There are more fundamental 'bottom-up' microstructural approaches that could have been used or considered. The authors would benefit from studying the following references: 
F Chevillotte, C, Perrot, R. Panneton, Microstructure based model for sound absorption predictions of perforated closed-cell metallic foams. J. Acoust. Soc. Am. 128 1766 –76 (2010)
C. Perrot, F. Chevillotte, R. Panneton, Bottom-up approach for microstructure optimization of sound absorbing materials, J.
Acoust. Soc. Am. 124 (2008) 940–948
J. H. Park, S. H. Yang, H. R. Lee, C. B. Yu, S. Y. Pak, C. S. Oh, Y. J. Kang, J. R. Youn, Optimization of low frequency sound absorption by cell size control and multiscale poroacoustics modeling, J. Sound Vib. 397 (2017) 17–30.


Response 2: 
Thank you so much for your kind suggestion.
We have read the 3 suggested references carefully and found that they were all helpful.
Thus, we introduced the corresponding research achievements in the introduction section and added these 3 references in the revised manuscript.

 


Point 3: The use of English would benefit from thorough editing.


Response 3: 
Thank you so much for your kind suggestion.
The English in the manuscript is corrected by two native English speakers in the Hong Kong Polytechnic University and revised by ourselves carefully, and the existed grammar and spelling mistakes are modified, which have been highlighted in yellow in the revised manuscript.

 


Point 4: Two specifically recommended changes are:
vertical axis labels in Fig.6 should be 'Sound Absorption Coefficient'
line 352 'theoretical data' should be replaced by 'predictions', 'simulation data' should be replaced by 'simulation results'. The term 'data' should be used to refer only to experimental data.


Response 4: 
Thank you so much for your kind reminder.
We have modified vertical axis labels in the Fig. 6 in the revised manuscript by using 'Sound Absorption Coefficient' to replace the 'Sound Absorbing Coefficient'.
Meanwhile, we replaced the 'theoretical data' and 'simulation data' by 'predictions' and 'simulation results' respectively all over the whole manuscript.

 


We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.
Once again, thank you very much for your comments and suggestions.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors submitted a paper titled '' identification of acoustic characteristic paramters and improvement of sound absorption performance for porous metal '' The authors used an approach combining a search algorithm, finite element and experimental methods for their investigations. The paper is well generally organized.

However I have some concerns with regards to the overall content of the paper

For scientists active in the field of acoustic of porous materials, this paper does not offer any noticeale novelty for the following reasons:

1. The identification of the acoustic properties of foams has been widely investigated and several commercial software based on inverse method are used to retrieve the proprierties from a simple impedance tube measurements.

2. It is well known that a thin perforated sheet backed by a air or foam improves the acoustic absorption. Again, there is nothing quite new here.

Assuming thatthe novelty of the article is based on the scientific method used, there are still some issues to be clarified:

I do understand that paper is intended for specific audience but focussing metal foam in the introduction is restrictive. Polymeric foams can be as good as their metal counterparts acoustically and mechanically. in addition polymeric foam have interesting specific properties which make them suitable for many engineering application where the weight is a concern.

It was not clear to me, why the authors choose to focuss solely on the porosity and the static flow resistivity. Besides these two properties, the JCA model clearly states that a foam is characterized by the viscous and thermal characteristic lenghts, the static permeability and the tortuosity. As far as I am concerned, the use of inverse method would have been more helpful to get these parameters.

The authors were able to experimentally measured the porosity (which is standard). This means that, the only unknown parameter left for the search algorithm is the static flow resistivity. Again, I am wondering why the authors used this algorithm instead of a simple curve fitting of the experimental absorption?

Finally I do understand the investigation was comprative, but it would have been interesting to have more details on the dissipation mechanism occuring in the porous materials and in the multilayer material (perforatedsheet/porous metals. This can be done if a clear correlation betwen the microstructure of porous metals and their acoustic properties is done which is not the case in the present work

Comments for author File: Comments.pdf

Author Response

Response to reviewer 3’s comments

 

Summary: The authors submitted a paper titled '' identification of acoustic characteristic paramters and improvement of sound absorption performance for porous metal '' The authors used an approach combining a search algorithm, finite element and experimental methods for their investigations. The paper is well generally organized.

However I have some concerns with regards to the overall content of the paper

 

Response:

Thank you very much for your kind comment.

Identification of acoustic characteristic parameters and improvement of sound absorption performance for porous metal were conducted by cuckoo search algorithm in this research, which achieved the optimal composite sound absorbing structures with tiny increase in occupied space and few addition in weight. Accuracy and effectiveness of the cuckoo search identification and optimization algorithm were certified by finite element simulation and standing wave tube measurement. The improved sound absorption performance would be favorable to promote practical application of the optimal composite structures in the fields of sound absorption and noise reduction.

Corresponding modifications had been conducted in the revised paper according to your comments, which we wished to meet your requirements.

 

 

Point 1: For scientists active in the field of acoustic of porous materials, this paper does not offer any noticeale novelty for the following reasons:

  1. The identification of the acoustic properties of foams has been widely investigated and several commercial software based on inverse method are used to retrieve the proprierties from a simple impedance tube measurements.
  2. It is well known that a thin perforated sheet backed by a air or foam improves the acoustic absorption. Again, there is nothing quite new here.

 

Response 1:

Thank you so much for your kind comment.

We utilized cuckoo search method in identification of acoustic characteristic parameters and optimization of sound absorption performance for the porous metal, which was different from other present methods. Meanwhile, finite element simulation and standing wave tube measurement were conducted to validate the optimization results, which certified effectiveness of this identification and optimization method.

It was well known that sound absorption performance of porous metal would be improved by adding a microperforated panel, but the improvement could not reach the best if the parameters were not optimized. Meanwhile, constraint conditions should also be taken into consideration, as what had been done in this study. Selecting the appropriate structural parameters would obtain excellent sound absorption coefficients with tiny increase in occupied space and few addition in weight.

Based on the achievements in this study, we supposed it would be favorable to promote practical application of porous metal in noise reduction and the research was meaningful.

 

 

Point 2: Assuming thatthe novelty of the article is based on the scientific method used, there are still some issues to be clarified:

I do understand that paper is intended for specific audience but focussing metal foam in the introduction is restrictive. Polymeric foams can be as good as their metal counterparts acoustically and mechanically. in addition polymeric foam have interesting specific properties which make them suitable for many engineering application where the weight is a concern.

It was not clear to me, why the authors choose to focuss solely on the porosity and the static flow resistivity. Besides these two properties, the JCA model clearly states that a foam is characterized by the viscous and thermal characteristic lenghts, the static permeability and the tortuosity. As far as I am concerned, the use of inverse method would have been more helpful to get these parameters.

The authors were able to experimentally measured the porosity (which is standard). This means that, the only unknown parameter left for the search algorithm is the static flow resistivity. Again, I am wondering why the authors used this algorithm instead of a simple curve fitting of the experimental absorption?

Finally I do understand the investigation was comprative, but it would have been interesting to have more details on the dissipation mechanism occuring in the porous materials and in the multilayer material (perforatedsheet/porous metals. This can be done if a clear correlation betwen the microstructure of porous metals and their acoustic properties is done which is not the case in the present work.

 

Response 2:

Thank you very much for your kind inquiry.

We agreed with you that polymeric foam was also a common porous material used in the sound absorption, which was similar with the porous metal. However, relative to polymeric foam, porous metal has some special advantages. Firstly, most of the polymeric foam was not flame retardant, and the porous metal had outstanding flame resistance. Secondly, fabrication of the polymeric foam had more damage to the environment than that of the porous metal. Thirdly, mechanical property of the porous metal was better than that of the polymeric foam. Therefore, porous metal and polymeric foam might be suitable for different conditions in the noise reduction, and porous metal was selected in this study.

We agreed with you that acoustic characteristic parameters of the porous metal, which affected its sound absorption performance, not only included porosity and static flow resistivity, but also consisted of tortuosity, viscous and thermal characteristic lengths, and so on. However, judging from calculation of sound absorption coefficient of the porous metal in the manuscript according to the JCA model, only the porosity and static flow resistivity appeared in the derivation equations. Therefore, we took the porosity and static flow resistivity as the pending identified acoustic characteristic parameters in this study. In future, we would attempt to improve accuracy of the theoretical sound absorption model by taking other parameters into consideration.

We supposed that there were two major reasons for selection of the cuckoo search identification method instead of a simple curve fitting. Firstly, simple curve fitting did not have any physical meaning. Secondly, it could be judged from calculation of sound absorption coefficients of the porous metal by these equations that the relationship between sound absorption coefficient and the parameter was complex, which would decrease the prediction accuracy by simple curve fitting.

The detailed dissipation mechanism occurring in the porous materials and that occurring in the composite sound absorbing structure would be taken into consideration in our future research. The present research focused on the achievement of better sound absorption performance with the constraint conditions. Meanwhile, we supposed that the present constructed theoretical sound absorption model of composite sound absorbing structure based on the JCA model and Maa’s theory was enough to develop practical sound absorber, and these theories had presented corresponding sound absorption mechanisms basically.

 

 

Point 3:  Review comments in the manuscript.

(1) “these” should be replaced by “the” in the line 17.

(2) Not all porous materials have flame  resistance . Please need to be more precise. Again the cost-effectiveness depends on the nature of the material and the manufacturing process.

(3) Compared to polymeric foams , metals foam are generally  heavier which  limit their applications in several engineering fields such transportation and aeronautics.

(4) According to the  JCA, along with porosity and the static flow resistivity, a porous material is  completely  defined through the determination  of the tortuosity,  the thermal and viscous characteristic lengths.  How is it that they are not taken into account in your optimization algorithm?

(5) “them” should be replaced by “the” in the line 189.

(6) since the porosity can be easily  measured and assuming that the only other parameter is the flow resistivity , I am wondering what is the point using and optimization algorithm.

A curve fitting would have  got the same result  in simpler way..

(7) It is widely known that  a perforated sheet closing a volume of air leads to an increase of sound absorption. So in the case presented in the paper, it would be interesting to know what is the size of the porosity of the porous metal.

(8) The comparative analysis is interesting but  analysis of the dissipation mechanism would have been welcome.

 

 

Response 2:

Thank you very much for your kind suggestion.

(1) “these” had been replaced by “the” in the line 17 in the revised manuscript.

(2) In the paragraph 1 of the introduction section, outstanding flame resistance and satisfactory cost–effective ratio was considered as the normal advantages of the porous metal, not all the porous materials. These advantages were widely accepted for normal porous metal used in the sound absorption, which could be found in the related references.

(3) We agreed with you that polymeric foam was also a common porous material used in the sound absorption, which was similar with the porous metal. However, relative to polymeric foam, porous metal also has some special advantages. Firstly, most of the polymeric foam was not flame retardant, and the porous metal had outstanding flame resistance. Secondly, fabrication of the polymeric foam had more damage to the environment than that of the porous metal. Thirdly, mechanical property of the porous metal was better than that of the polymeric foam. Therefore, porous metal and polymeric foam might be suitable for different conditions in the noise reduction, and porous metal was selected in this study.

(4) We agreed with you that acoustic characteristic parameters of the porous metal, which affected its sound absorption performance, not only included porosity and static flow resistivity, but also consisted of tortuosity, viscous and thermal characteristic lengths, and so on. However, judging from calculation of sound absorption coefficient of the porous metal in the manuscript according to the JCA model, only the porosity and static flow resistivity appeared in the derivation equations. Therefore, we took the porosity and static flow resistivity as the pending identified acoustic characteristic parameters in this study. In future, we would attempt to improve accuracy of the theoretical sound absorption model by taking other parameters into consideration.

(5) “them” had been replaced by “the” in the line 198 in the revised manuscript (corresponding to the line 189 in the original manuscript).

(6) We supposed that there were two major reasons for selection of the cuckoo search identification method instead of a simple curve fitting. Firstly, simple curve fitting did not have any physical meaning. Secondly, it could be judged from calculation of sound absorption coefficients of the porous metal by these equations that the relationship between sound absorption coefficient and the parameter was complex, which would decrease the prediction accuracy by simple curve fitting.

(7) It was well known that sound absorption performance of porous metal would be improved by adding a microperforated panel, but the improvement could not reach the best if the parameters were not optimized. Meanwhile, constraint conditions should also be taken into consideration, as what had been done in this study. Selecting the appropriate structural parameters would obtain excellent sound absorption coefficients with tiny increase in occupied space and few addition in weight. Porosity of the porous metal used in this study was measured through the drainage method, and its actual value was 0.9136, as mentioned in the manuscript.

(8) The detailed dissipation mechanism occurring in the porous materials and that occurring in the composite sound absorbing structure would be taken into consideration in our future research. The present research focused on the achievement of better sound absorption performance with the constraint conditions. Meanwhile, we supposed that the present constructed theoretical sound absorption model of composite sound absorbing structure based on the JCA model and Maa’s theory was enough to develop practical sound absorber, and these theories had presented corresponding sound absorption mechanisms basically.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.pdf

Reviewer 3 Report

The manuscript titled: Identification of Acoustic Characteristic Parameters and Improvement of Sound Absorption Performance for Porous Metal describes improvements of sound absorption for porous metals by adding a thin layer of perforated foil/microperforated penal. The paper describes differences of sound absorption regarding using different types of microperforeted panel (different parameters of laser perforation) at different frequency range. The paper is interesting especially for some applications which need to absorb specific range of frequency (without adding much of weight or space). This study is a continues work from previously investigated study published in Appl. Sci. Parameter Optimization for Composite Structures of Microperforated Panel and Porous Metal for Optimal Sound Absorption Performance and Appl. Sci. Low Frequency Sound Absorption by Optimal Combination Structure of Porous Metal and Microperforated Panel. Previous research work was performed using different material/frequencies with similar calculations and experimental performances.

 

The paper is well written and it doesn’t need much improvements.

There is missing the standard deviation at experimental data. How repeatable are measurements?

Also more detailed description of the porous material would be good. You use open cell porous copper material with average pour size below 500 µm. Would calculation work on aluminium or titanium as well? Did you try using some different type of porous material – thin walled/thick walled? A great benefit of this work would be if you can add some characteristic of the used porous metals as well.

Author Response

Response to reviewer 2’s comments

 

Summary: The manuscript titled: Identification of Acoustic Characteristic Parameters and Improvement of Sound Absorption Performance for Porous Metal describes improvements of sound absorption for porous metals by adding a thin layer of perforated foil/microperforated penal. The paper describes differences of sound absorption regarding using different types of microperforeted panel (different parameters of laser perforation) at different frequency range. The paper is interesting especially for some applications which need to absorb specific range of frequency (without adding much of weight or space). This study is a continues work from previously investigated study published in Appl. Sci. Parameter Optimization for Composite Structures of Microperforated Panel and Porous Metal for Optimal Sound Absorption Performance and Appl. Sci. Low Frequency Sound Absorption by Optimal Combination Structure of Porous Metal and Microperforated Panel. Previous research work was performed using different material/frequencies with similar calculations and experimental performances. The paper is well written and it doesn’t need much improvements.

 

Response:

Thank you very much for your positive opinion.

Identification of acoustic characteristic parameters and improvement of sound absorption performance for porous metal were conducted by cuckoo search algorithm in this research, which achieved the optimal composite sound absorbing structures with tiny increase in occupied space and few addition in weight. Accuracy and effectiveness of the cuckoo search identification and optimization algorithm were certified by finite element simulation and standing wave tube measurement. The improved sound absorption performance would be favorable to promote practical application of the optimal composite structures in the fields of sound absorption and noise reduction.

Corresponding modifications had been conducted in the revised paper according to your comments, which we wished to meet your requirements.

 

 

Point 1: There is missing the standard deviation at experimental data. How repeatable are measurements?

 

Response 1:

Thank you so much for your kind inquiry.

In order to reduce the measuring error in the testing program, each porous metal sample was tested for 10 times, and the final experimental data was average value of the ten testing data. It had been proved by Duan et al. [39] that undulation of the experimental data could be kept in ±0.2% among the ten testing data, which certified veracity and repeatability of this experimental measurement.

  1. Duan, H.Q.; Shen, X.M.; Yang, F.; Bai, P.F.; Lou, X.F.; Li, Z.Z. Parameter Optimization for Composite Structures of Microperforated Panel and Porous Metal for Optimal Sound Absorption Performance. Appl. Sci. 2019, 9(22), 4798.

Similar with standing wave tube measurement of the porous metal sample, each optimal composite sound absorbing structure was measured for 10 times, and the final experimental data was average value of the ten testing data, which aimed to reduce the measuring error in the testing program.

These presentations are added in the revised manuscript and highlighted in yellow, which we wish can meet your requirement.

 

 

Point 2: Also more detailed description of the porous material would be good. You use open cell porous copper material with average pour size below 500 µm. Would calculation work on aluminium or titanium as well? Did you try using some different type of porous material – thin walled/thick walled? A great benefit of this work would be if you can add some characteristic of the used porous metals as well.

 

Response 2:

Thank you very much for your kind suggestion.

In our previous research, we had compared sound absorption performance of the porous copper with that of the porous iron and that of the porous nickel when their structural parameters were same, and the results indicated that their sound absorption performance had little difference. It could also be judged from theoretical sound absorption model of the porous metal based on the Johnson–Champoux–Allard model that sound absorption performance of the porous metal was determined by its structural parameters and had little relationship with its physical and chemical parameters.

Porous aluminium and porous titanium had not been studied right now, because there were close cells for most of the porous aluminium and cost of the porous titanium was high, which indicated that they were not suitable to develop practical sound absorber.

Until now, thin-walled and thick-walled porous material had not been taken into account, we would take them into consideration in our future research.

In this study, sound absorption performance of the porous metal was analysed based on the Johnson–Champoux–Allard model, from which it could be found that the major influencing factors were porosity and static flow resistivity. Therefore, these two parameters were identified in this study. In future study, we would take the other characteristics (such as tortuosity, characteristic viscous length and thermal length, and so on) into consideration, which aimed to construct the theoretical sound absorption model with higher accuracy.

Thank you again for your kind guidance.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.pdf

Reviewer 4 Report

This paper shows a way for identifying the acoustic characteristic parameters: porosity and static flow resistivity of porous metals by using cuckoo search algorism. Furthermore, a microperforated panel is examined so as to improve the sound absorption coefficient. The FEM, theoretical and experimental results are in good agreement.

It is considered to be acceptable and useful to find the acoustic characteristic parameters of porous metals by cuckoo search algorism from experimental data. Once the parameter: the product of porosity and static flow resistivity in particular is identified from experimental data, the sound absorption coefficients of porous metals for different thicknesses could be found with the Johnson-Champoux-Allard model. In this chapter, the complex effective bulk modulus of the porous metal in the eq. (7) is a question point. Is it a sort of air pressure?

In finding the parameters of the microperforated panel to improve the sound absorption coefficient by cuckoo search algorism, the optimal values are only shown in Table 1. You should show the reason why they are the optimum. Chap. 4 makes little sense in judgement of optimum.

 

Author Response

Response to reviewer 1’s comments

 

Summary: This paper shows a way for identifying the acoustic characteristic parameters: porosity and static flow resistivity of porous metals by using cuckoo search algorism. Furthermore, a microperforated panel is examined so as to improve the sound absorption coefficient. The FEM, theoretical and experimental results are in good agreement.

 

Response:

Thank you very much for your positive opinion.

Identification of acoustic characteristic parameters and improvement of sound absorption performance for porous metal were conducted by cuckoo search algorithm in this research, which achieved the optimal composite sound absorbing structures with tiny increase in occupied space and few addition in weight. Accuracy and effectiveness of the cuckoo search identification and optimization algorithm were certified by finite element simulation and standing wave tube measurement. The improved sound absorption performance would be favorable to promote practical application of the optimal composite structures in the fields of sound absorption and noise reduction.

Corresponding modifications had been conducted in the revised paper according to your comments, which we wished to meet your requirements.

 

 

Point 1: it is considered to be acceptable and useful to find the acoustic characteristic parameters of porous metals by cuckoo search algorism from experimental data. Once the parameter: the product of porosity and static flow resistivity in particular is identified from experimental data, the sound absorption coefficients of porous metals for different thicknesses could be found with the Johnson-Champoux-Allard model. In this chapter, the complex effective bulk modulus of the porous metal in the eq. (7) is a question point. Is it a sort of air pressure?

 

Response 1:

Thank you so much for your kind inquiry.

We had checked the Equation (7) carefully and confirmed that it was correct. The theoretical sound absorption model, which included the Equation (7), was constructed based on the Johnson–Champoux–Allard model [19–21]. Thus, you can check calculation of the complex effective bulk modulus of the porous metal in these references. The complex effective bulk modulus represented deformation of the air in the porous metal.

Allard, J.F.; Champoux, Y. New empirical equations for sound propagation in rigid frame fibrous materials. J. Acoust. Soc. Am. 1992, 91, 3346–3353. Kino, N. Further investigations of empirical improvements to the Johnson–Champoux–Allard model. Appl. Acoust. 2015, 96, 153–170. Yang, X.C.; Bai, P.F.; Shen, X.M.; Zhang, X.N.; Zhu, J.W.; Yin, Q.; Peng, K. Theoretical modeling and experimental validation of sound absorbing coefficient of porous iron. J. Porous Media 2019, 22(2), 225–241.

 

Point 2: In finding the parameters of the microperforated panel to improve the sound absorption coefficient by cuckoo search algorism, the optimal values are only shown in Table 1. You should show the reason why they are the optimum. Chap. 4 makes little sense in judgement of optimum.

 

Response 2:

Thank you very much for your kind comment.

The optimal structural parameters for each target frequency range were obtained by the cuckoo search algorithm, as shown in the Table 1 in the manuscript. In fact, in the optimization process, a large series of structural parameters were tested in the cuckoo search algorithm, and the exhibited optimal structural parameters in the Table 1 were the optimal one to achieve the best sound absorption performance. If the optimal structural parameters were replaced by other series of structural parameters, the calculated average sound absorption coefficients would be smaller than that obtained by the optimal structural parameters. They were theoretical optimal structural parameter, and their effectiveness and accuracy were proved by the finite element simulation and standing wave tube measurement.

Chapter 4 was finite element simulation and standing wave tube measurement of the theoretical optimal composite sound absorbing structures. Consistencies among the theoretical data, simulation data, and experimental data proved effectiveness and precision of the constructed theoretical sound absorption model, the selected cuckoo search identification and optimization algorithm, and the adopted finite element simulation method. In fact, if we choose another series of structural parameters, fabricate the composite sound absorbing structures, conduct finite element simulation and standing wave tube measurement, the obtained average sound absorption coefficients will be smaller than that obtained by the optimal structural parameters. In fact, validation of effectiveness and accuracy of the optimal structural parameters had been widely applied in developing other sound absorbers, which could be found in the following references.

Yang, X.C.; Shen, X.M.; Bai, P.F.; He, X.H.; Zhang, X.N.; Li, Z.Z.; Chen, L.; Yin, Q. Preparation and characterization of gradient compressed porous metal for high-efficiency and thin–thickness acoustic absorber. Materials 2019, 12(9), 1413. Shen, X.M.; Bai, P.F.; Chen, L.; To, S.; Yang, F.; Zhang, X.N.; Yin, Q. Development of thin sound absorber by parameter optimization of multilayer compressed porous metal with rear cavity. Appl. Acoust. 2020, 159, 107071. Yang, F.; Shen, X.M.; Bai, P.F.; Zhang, X.N.; Li, Z.Z.; Yin, Q. Optimization and Validation of Sound Absorption Performance of 10-Layer Gradient Compressed Porous Metal. Metals 2019, 9(5), 588. Duan, H.Q.; Shen, X.M.; Yang, F.; Bai, P.F.; Lou, X.F.; Li, Z.Z. Parameter Optimization for Composite Structures of Microperforated Panel and Porous Metal for Optimal Sound Absorption Performance. Appl. Sci. 2019, 9(22), 4798.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Thanks for the changes.

Apart from further improvement in the use of English which would be desirable. the authors have made adequate responses to my criticisms. However the scientific quality and novelty remain marginal. 

Author Response

Response to reviewer 1’s comments

 

Summary: Thanks for the changes.

Apart from further improvement in the use of English which would be desirable, the authors have made adequate responses to my criticisms. However the scientific quality and novelty remain marginal.

 

 

Response:

Thank you very much for your positive opinion.

The English in the manuscript is corrected by two native English speakers in the Hong Kong Polytechnic University and revised by ourselves carefully, and the existed grammar and spelling mistakes are modified, which have been highlighted in yellow in the revised manuscript.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.docx

Reviewer 2 Report

I feel the authors have made a good attempt to address  my concerns. 

Author Response

Response to reviewer 2’s comments

 

Summary: I feel the authors have made a good attempt to address my concerns.

 

Response:

Thank you very much for your positive opinion.

Some grammar and spelling mistakes are modified, and the presentations are further polished, which aim to make the manuscript more readable.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.docx

Reviewer 4 Report

 The question is not clear for the authors and changed below.

 

The optimization process of the structural parameters is not clear, so that the results in Table 1 make no sense. The reason why the parameters you found is optimum should be proved. The comparison between the calculated and experimental data is not evidence of the optimization process, that is the evidence of the excellent theoretical model.

 

What is the difference of the paper and another, for example the reference (18) which shows the structural parameters found by cuckoo search algorism? The structure in the reference (18) is more complicated than that in this paper. It should be clear.

 

The presentation of the paper should be revised.

 

Author Response

Response to reviewer 4’s comments

Point 1: The question is not clear for the authors and changed below.

The optimization process of the structural parameters is not clear, so that the results in Table 1 make no sense. The reason why the parameters you found is optimum should be proved. The comparison between the calculated and experimental data is not evidence of the optimization process, that is the evidence of the excellent theoretical model.

 

Response 1:

Thank you very much for your kind explication.

For each cuckoo search optimization program, 2000 generations were iterated to find the optimal parameters, and each generation had 1000 groups of solutions, which indicated that total 2 million optional groups of parameters were examined and the obtained optimal parameters were the best among them. Taking a random group of parameters (d=0.5 mm, b=1.5 mm, t=0.3 mm) for example, it could be calculated that the corresponding average sound absorption coefficients of the composite structures were 0.1888, 0.3751, 0.5167, 0.5810, 0.5917, and 0.5813 when the target frequency ranges were 100–1000 Hz, 100–2000 Hz, 100–3000 Hz, 100–4000 Hz, 100–5000 Hz, and 100–6000 Hz respectively, which could prove that the obtained optimal parameters in the Table 1 was the best option.

These presentations were added in the revised manuscript and highlighted in yellow, which aimed to make the manuscript more readable and reasonable.

 

 

Point 2: What is the difference of the paper and another, for example the reference (18) which shows the structural parameters found by cuckoo search algorism? The structure in the reference (18) is more complicated than that in this paper. It should be clear.

 

Response 2:

Thank you so much for your kind inquiry.

Firstly, the research object was different. In reference (18), which was titled “Optimization and Validation of Sound Absorption Performance of 10-Layer Gradient Compressed Porous Metal”, the research object was the 10-layer gradient compressed porous metal, which was different from the research object of composite sound absorbing structures in this study.

Secondly, the obtained sound absorption performance was different. Although the structure of 10-layer gradient compressed porous metal in the reference (18) was more complicated than that of composite sound absorbing structure in this study, sound absorption performance of the former was worse than that of the latter. When the target frequency ranges were 100-1000 Hz, 100-2000 Hz, and 100-4000 Hz, with the same total thickness of 20 mm, corresponding actual average sound absorption coefficients of the 10-layer gradient compressed porous metal were 0.3325, 0.5412, and 0.7461, and those of the composite sound absorbing structure in this study were 0.5393, 0.6533, and 0.7562.

Thirdly, the fabrication process was different. The structure of 10-layer gradient compressed porous metal in the reference (18) was obtained by assembling 10 monolayer compressed porous metal samples. For the composite sound absorbing structure in this study, it consisted of the microperforated metal panel and porous metal.

Fourthly, the optimized parameters were different. For the 10-layer gradient compressed porous metal in the reference (18), the optimized parameters were compression ratios of each monolayer. For the composite sound absorbing structure in this study, the optimized parameters were diameter of the hole and distance of the neighboring holes.

Therefore, this research was quite different from that in the reference (18) or those in other references. The developed sound absorbers in this research and previous studies had variable characters, which could be used for practical applications with different conditions.

 

 

Point 3: The presentation of the paper should be revised.

 

Response 3:

Thank you very much for your kind suggestion.

Some grammar and spelling mistakes are modified, and the presentations are further polished, which aim to make the manuscript more readable.

 

 

We appreciate for your warm work and wish that the correction will meet with approval. We are looking forward to the result of final acceptance.

Once again, thank you very much for your comments and suggestions.

Author Response File: Author Response.pdf

Round 3

Reviewer 4 Report

It is very sorry to say that I cannot find the scientific contents of the optimization process in the paper because of no data about the optimization process and just mention only. I cannot check and follow the paper enough.

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