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Peer-Review Record

Flow-Stress Model of 300M Steel for Multi-Pass Compression

Metals 2020, 10(4), 438; https://doi.org/10.3390/met10040438
by Rongchuang Chen 1,2,*, Jiao Zeng 1, Guichuan Yao 1 and Fei Feng 3
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Metals 2020, 10(4), 438; https://doi.org/10.3390/met10040438
Submission received: 8 March 2020 / Revised: 25 March 2020 / Accepted: 26 March 2020 / Published: 27 March 2020

Round 1

Reviewer 1 Report

The article is very interesting, well written and the subject is treated in a systematic manner.

Following small typos could be found:

  • Table 1: The last (6th) column should not have the unit (s-1) but the number (2); [e2 (2)].
  • Line 275: The softening fraction of 28 % should probably be a much higher (98 % ?).

The understanding of the described physical phenomena occurring during high temperature treatment could be improved if the authors could:

  • Describe what they mean with “meta-dynamic recrystallization”? First mentioned on line 45 and 62-63, and then introduced first time in the section of results on line 127.

 

  • Describe what they mean with “incomplete dynamic recrystallization”, see line 127-128.

 

  • Describe what is meant with “dynamic recrystallization volume fraction”, first introduced on line 115-116.

The reader is struggling with the question of how the dynamic recrystallization in the material should be understood from the physical point of view. Therefore would a more detailed description of the above mentioned denominations improve this.

Author Response

Response:

1.  Table 1: The last (6th) column should not have the unit (s-1) but the number (2); [e2 (2)].

Response: The strain is unitless, so this unit is changed to “1”.

2. Line 275: The softening fraction of 28 % should probably be a much higher (98 % ?).

Response: Yes, it was a mistake. According to the result in Figure 10a, the softening fraction was calculated to be 28%. So, the word “larger” is changed to “smaller”.

3. The understanding of the described physical phenomena occurring during high temperature treatment could be improved if the authors could: Describe what they mean with “meta-dynamic recrystallization”? First mentioned on line 45 and 62-63, and then introduced first time in the section of results on line 127.

Response: Descriptions have been added in the 3rd paragraph of introduction. “From the point of view of dislocation evolution, these microstructure evolution processes all contribute to the annihilation of dislocation, but the time of effect and the degree of contribution are different. Dynamic recovery and dynamic recrystallization occur during deformation, while meta-dynamic recrystallization, static recrystallization, and static recovery occur during holding. Determining the contribution of each microstructure evolution on the flow behaviors of steels is complex, and there are many variables that may affect the flow behavior, for example, strain, strain rate, temperature, interrupt strain, inter-pass holding time, and total pass number..”

4. Describe what they mean with “incomplete dynamic recrystallization”, see line 127-128.

 Response: To make the expression more accurate, this word has been changed to “dynamic recrystallization occurred incompletely”.

5. Describe what is meant with “dynamic recrystallization volume fraction”, first introduced on line 115-116.

 Response: Interpretation of dynamic recrystallization volume fraction (the volume fraction of dynamic recrystallized grains in total grains) has been added.

6. The reader is struggling with the question of how the dynamic recrystallization in the material should be understood from the physical point of view. Therefore would a more detailed description of the above mentioned denominations improve this.

 Response: Descriptions have been added in the 3rd paragraph of introduction according to this reviewer comment.

Reviewer 2 Report

I believe that the results obtained in the reviewed article are interesting and worthy of publication. But the article will become more accessible for understanding and the results obtained will be more reasonable if the authors will consider it possible to take into account the reviewer 's comments.

Comments for author File: Comments.pdf

Author Response

Response:

1. In Fig. 1 (a) in the position corresponding to Stage 2, argument at  is  but must be .

Response: Modification has been made according to this reviewer comment.

2. In Table 1, the dimensions of the  (1) and  (s-1) should be clarified.

Response: The strain is unitless, so this unit is changed to “1”.

3. In line 231, which describes the quantities that are present in the relation (15), it is indicated that b is the Burgess vector. But any vector has a direction. Can be in this case b is the module of the Burgess vector?

Response: Yes, indeed. b is the module of the Burgess vector. Modification has been made accordingly.

4. Method for the model parameter identification needs to describe more in detail. Is it scanning (iterating over) parameters in the area where they change, with a certain step? How is this area defined?

Response: For genetic algorithm, the optimized parameters could be obtained simply by providing the parameter ranges, for example, from -∞ to +∞, but the drawback was the optimization speed. For none-derivative method, the optimization could be much quicker, but an initial solution needed to be set. Therefore, in order to speed up the solving process, the model parameters were firstly identified by genetic algorithm. Then, the combination of model parameters was set as initial solution for none-derivative method. In this way, the optimized model parameters were obtained. Explanations have been added according to this comment.

5. The calculated values of the volume of recrystallized grains (Figs. 10, 11) should be confirmed by experimental data obtained by direct study of the material structure. I do not insist that the authors do this in this paper, but they should keep this in mind.

Response: Yes. If the model can be supported by the metallographic observations, it will greatly reduce the work of microstructure calibration, which is also one of the purposes of the study. This study is going on, and metallographic observation is an important part of the following work.

Author Response File: Author Response.pdf

Reviewer 3 Report

300M alloy steel is a vacuum melted low alloy of superior strength and hardenability, with good ductility, toughness, and wear-resistance characteristics. The flow stress of 300M steel during a single-pass compression have been investigated by many authors. The originality of this article lies in study of flow stress of 300M steel during multi-pass compression with taking into account the influences of inter-pass holding time, interrupt strains, and total pass number. The developed model can be used in more precise prediction of flow stress of 300M steel during hot forging or rolling.

The questions:

1) Line 93, in Table 1, in column 6. Parameter ?2 (s-1). Is it strain or strain rate?

2) The flow stress model for 300M steel includes 34 unknown parameters that needed to be determined. In order to determine the unknown parameters, it is necessary to solve the system of equations. This system must include as many equations as there are unknown parameters. So, we need at least 34 equations, which can be obtained from at least 34 experimental tests. But only 14 experimental tests (T1-T14) were performed by authors. It should be explained clearer, how 34 unknown parameters were determined by 14 experimental tests? How many equations were obtained from 14 experimental tests?

3) Microstructure evolution (grain size, dislocation density) of 300M steel during multi-pass compression should be confirmed by metallography.

Author Response

Response:

1) Line 93, in Table 1, in column 6. Parameter ?2 (s-1). Is it strain or strain rate?

Response: Parameter ?2 is strain. So, the unit is modified to “1”. Modification has been made in Table 1.

2) The flow stress model for 300M steel includes 34 unknown parameters that needed to be determined. In order to determine the unknown parameters, it is necessary to solve the system of equations. This system must include as many equations as there are unknown parameters. So, we need at least 34 equations, which can be obtained from at least 34 experimental tests. But only 14 experimental tests (T1-T14) were performed by authors. It should be explained clearer, how 34 unknown parameters were determined by 14 experimental tests? How many equations were obtained from 14 experimental tests?

Response: In this work, the experiments were designed mainly to understand the influence of various factors on the flow stress. Then, a model to describe these influences was proposed. The model parameters could be obtained even if the number of experiments was less than the number of model parameters (34), because the model parameters were solved in an iterative way. In other words, a combination of parameters that was closest to the results was obtained, and other parameter combinations may also exist. By increasing the number of experiments, the possible combinations of parameters become less, and eventually the real solution could be approached. The experiment design is systematic work. The ideal number of experiments should be greater than the number of model parameters, and in these experiments, the distribution of parameters should be as dispersed as possible, so that the overall model prediction is optimal. The authors agree that in order to improve the accuracy of the model, the number of experiments should be as large as possible, and further improvement of the model accuracy can be studied in the future. Explanation of the solving process has been added. “For genetic algorithm, the optimized parameters could be obtained simply by providing the parameter ranges, for example, from -∞ to +∞, but the drawback was the optimization speed. For none-derivative method, the optimization could be much quicker, but an initial solution needed to be set. Therefore, in order to speed up the solving process, the model parameters were firstly identified by genetic algorithm. Then, the combination of model parameters was set as initial solution for none-derivative method.”

 

3) Microstructure evolution (grain size, dislocation density) of 300M steel during multi-pass compression should be confirmed by metallography.

Response: Yes. If the model can be supported by the metallographic observations, it will greatly reduce the work of microstructure characterization in industrial productions, which is also one of our purposes. The authors are urging to confirm the results by metallography, but this work is still carrying on.

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