Precise Modeling Method for Grain Size Evolution in the Whole Hot Forging Process of Key Load-Bearing Components in Aviation

Abstract

An accurate modeling method for the grain size evolution in the whole hot forging process of key load-bearing components in aviation includes three typical stages: the establishment of the grain growth model during heating and holding, the average dynamic recrystallization grain size model and the average grain size model during hot deformation, and the average grain size model during inter-pass holding. The grain size during inter-pass holding serves as the initial grain size for the next deformation process. The present invention comprehensively considers the influence of process parameters in different stages of the whole hot forging process on grain evolution, fully takes into account the influence of deformation parameters on the grain size and distribution during the hot deformation process, and couples the influence of static recrystallization and meta-dynamic recrystallization mechanisms to establish a unified post-dynamic recrystallization grain size model, and accurately and reliably describes the genetic inheritance relationship of grain evolution in different stages with the grain size as an internal variable. It can effectively solve the problems of difficult accurate prediction and effective control of the grain size evolution in the whole hot forging process of key load-bearing components in aviation, resulting in low finished product rate of parts and poor service performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermoplastic forming, and relates to an accurate modeling method for the evolution of grain size in the whole hot forging process of an aviation key load-bearing component. Technical Background

[0002] Due to the complex structure and large volume size, aviation key load-bearing components often require multi-pass forming, specifically including three typical processes: heating and holding process, hot deformation process, and inter-pass holding process. Grain growth occurs during the heating and holding process, the dynamic recrystallization and dynamic recovery mechanisms are involved in the hot deformation process, and the static recovery and post-dynamic recrystallization mechanisms (including static recrystallization and meta-dynamic recrystallization mechanisms) are involved in the inter-pass holding process. The complex microscopic evolution mechanisms in different stages make the grain size evolution law in different stages of the hot forming process complex and difficult to control. In addition, the microstructure in adjacent stages will interact with each other, making the grain size inheritance relationship complex. The above coupling effects make it difficult to accurately predict and effectively control the grain size evolution in the whole hot forging process of aviation key load-bearing components. The grain size is a key index for detecting the forming quality of aviation key load-bearing components, which is directly related to the product yield and service performance. Therefore, it is necessary to accurately model the grain evolution of aviation key load-bearing components, so as to lay a foundation for the effective control of the grain evolution in the whole hot forging process of aviation key load-bearing components.

[0003] To address the above problems, Qiao Shibin established a grain evolution model for SA508Gr.4N steel during heating and holding, hot deformation, and inter-pass holding processes in "Microstructure Evolution and Process Optimization during Forging of Large SA508Gr.4N Steel Forgings [D], Beijing: Central Iron and Steel Research Institute, 2021". Specifically, for the heating and holding process, a grain growth model considering the effects of holding temperature and holding time was established; for the hot deformation process, a dynamic recrystallization grain size model considering the effects of deformation temperature and strain rate was established; for the inter-pass holding process, static and meta-dynamic recrystallization grain size models considering the effects of initial grain size, deformation temperature, strain rate, and pre-strain were established. Dong Dingqian established grain growth, dynamic recrystallization, static recrystallization, and meta-dynamic recrystallization grain size models for SA508-3 steel respectively in "Mathematical Model of Grain Evolution during the Whole Process of Hot Forging of Nuclear Power Steel SA508-3 and Its Application in Head Forming [D], Shanghai: Shanghai Jiao Tong University, 2016". In addition, combined with the volume fraction of dynamic recrystallization, an average grain size model for the hot deformation process was established using an empirical formula. Huang Shiquan also conducted similar research in "Microstructure Evolution and Digital Characterization during the Whole Process of Integral Forging of Ultra-High Strength Steel [D], Changsha: Central South University, 2013", and Tang Meng in "Numerical Simulation and Experimental Study on Microstructure Evolution during Hot Deformation of 49MnVS3 Non-Quenched and Tempered Steel [D], Chongqing: Chongqing University of Technology, 2016". Invention Patent ZL 202210574104.8 proposed a method for establishing a grain size evolution model for hot forging forming of ultra-high strength steel, aiming at grain growth, dynamic recrystallization grains, static recrystallization grains, and meta-dynamic recrystallization grain evolution during the hot forging forming process of ultra-high strength steel.

[0004] However, the current research has the following problems: ① The genetic inheritance relationship of grain sizes in different stages is not fully considered; ② The average grain size model in the hot deformation process is calculated using an empirical formula and cannot accurately reflect the actual situation; ③ The grain growth model in the heating and holding stage does not consider the influence of heating rate; ④ The static and meta-dynamic recrystallization grain size models are independent of each other, and in fact, it is difficult to completely decouple the effects of static recrystallization and meta-dynamic recrystallization on grain size; ⑤ The static and meta-dynamic recrystallization grain size models in the inter-pass holding process do not consider the influence of holding time. The above deficiencies seriously affect the prediction accuracy of grain size during the hot forming process of aviation key load-bearing components, resulting in the performance of aviation key load-bearing components being difficult to meet the requirements.

[0005] Therefore, it is urgent to propose a new grain size modeling method for the whole hot forging process of aviation key load-bearing components that fully considers the influence of different parameters and genetic inheritance relationships, so as to achieve precise control of the grain size of aviation key load-bearing components. Summary of the Invention

[0006] In view of the above defects or improvement requirements of the existing modeling methods, the present invention provides an accurate modeling method for the grain size evolution of the entire hot forging process of key load-bearing components in aviation, aiming to fully consider the deformation parameters and the mutual influence of different stages, establish a grain size model for the entire hot forging process of key load-bearing components in aviation, and further achieve precise control of the grain size of the entire hot forging process of key load-bearing components in aviation, especially for the grain size prediction of components with multiple deformation processes and difficult-to-control structures.

[0007] An accurate modeling method for the grain size evolution of the entire hot forging process of key load-bearing components in aviation according to the present invention includes the following steps:

[0008] Step 1: Conduct heating and holding experiments on the materials used to manufacture key load-bearing components in aviation with different initial grain sizes, heating rates, holding temperatures, and holding times, and use software to statistically calculate the corresponding average grain sizes. Based on the statistically calculated grain sizes, establish a grain growth model for the heating and holding process as shown in Equation (1):

[0009]

[0010] where D g is the grain size during the heating and holding process, α, β, γ are material constants, Q g is the grain growth activation energy, R is the gas constant, T g is the holding temperature, t g is the holding time, is the heating rate. This equation considers the influence of the heating rate on the grain growth behavior.

[0011] The heating and holding experiments described in Step 1 can be carried out using equipment such as a heating furnace or a thermal simulation testing machine, or can also be carried out using in-situ high-temperature equipment such as a high-temperature laser confocal scanning microscope. Among them, using the latter for heating and holding experiments is more efficient and convenient.

[0012] After the heating and holding process ends, the material enters the hot deformation process. Conduct hot compression experiments at different deformation temperatures, strain rates, strains, and initial grain sizes through a thermal simulation testing machine, conduct metallographic corrosion on the experimental results, and statistically calculate their average dynamically recrystallized grain sizes and average grain sizes. Based on the statistically calculated grain sizes, establish an average dynamically recrystallized grain size model and an average grain size model for the hot deformation process. Among them, the average dynamically recrystallized grain size model for the hot deformation process is as shown in Equation (2):

[0013]

[0014] where D d is the average dynamically recrystallized grain size, δ, ε, ζ, η, θ are material constants, Q d is the deformation activation energy, is the strain rate, ε is the strain, and T d is the deformation temperature, and ε c is the critical strain. The critical strain is calculated using Equation (3):

[0015]

[0016] where ω, ψ, χ, are material constants.

[0017] In Equations (2) and (3), by introducing the grain size D g during the heating and holding process, the influence of the heating and holding process on the dynamic recrystallization grain evolution during the hot deformation process is fully considered, and the genetic inheritance of the grain size from the heating and holding process to the hot deformation process is realized.

[0018] The average grain size model for the hot deformation process is as shown in Equation (4):

[0019]

[0020] where D a is the average grain size during the hot deformation process, ι, κ, λ are material constants. is the modification of the Zener–Hollomon parameter. The Zener–Hollomon parameter is often used to judge whether dynamic recrystallization is complete, but this parameter does not consider the influence of strain. The present invention introduces the influence of strain into the Zener–Hollomon parameter. Z mc is the Z m critical value. When Z m is greater than Z mc , that is, dynamic recrystallization is incomplete. At this time, the material interior is composed of elongated grains and dynamically recrystallized grains; conversely, the dynamic recrystallization in the material is complete, and at this time, all the grains in the material interior are composed of dynamically recrystallized grains. Compared with the average grain size calculated based on the traditional dynamic recrystallization volume fraction, the method proposed in the present invention is based on actual microstructure statistics and has higher accuracy and reliability.

[0021] The hot simulation experiment described in Step 2 can be a hot compression experiment, a hot tensile experiment, or a hot torsion experiment, which is determined according to the actual stress state of the component during the actual hot deformation process. In addition, the specimen size and shape of the hot simulation experiment should also be determined according to the actual forming process.

[0022] Step 3: When the deformation process ends, the material will enter the inter-pass holding process. During the inter-pass holding process, static recrystallization, meta-dynamic recrystallization, or both will occur simultaneously. The average grain size model for the inter-pass holding process (also known as the post-dynamic recrystallization grain size) is calculated using Equation (5):

[0023]

[0024] wherein, D s is the average grain size during the static heat preservation process, v, ξ, ρ, φ are material constants, ε r is the unloading strain, Q s is the activation energy for post-dynamic recrystallization, T s is the inter-pass heat preservation temperature, t s is the inter-pass heat preservation time. This formula fully considers the effects of static recovery, static recrystallization, and meta-dynamic recrystallization during the inter-pass heat preservation process on the grain size. Compared with the grain size model for the traditional inter-pass heat preservation process, the present invention considers the influence of the grain size evolution during the deformation process on the grain size during the inter-pass heat preservation process, thereby realizing the genetic inheritance of the grain size from the hot deformation process to the inter-pass heat preservation process. In addition, the newly proposed grain size model for the inter-pass heat preservation process considers the influence of the inter-pass heat preservation time, and thus can effectively describe the evolution process of the grain size during the inter-pass heat preservation process.

[0025] The research on the grain evolution during the inter-pass heat preservation process described in step 3 can be carried out using equipment such as a thermal simulation testing machine, or can be carried out using in-situ equipment such as a high-temperature laser confocal scanning microscope.

[0026] When the three typical stages of the above heating and heat preservation process, hot deformation process, and inter-pass heat preservation process are completed, the average grain size of the inter-pass heat preservation is used as the initial grain size for the next deformation process, that is, the initial grain sizes of the average dynamic recrystallized grain size and the average grain size model in step 2. As the deformation continues, the grain size calculation method repeats steps 2 and 3. The above-mentioned modeling method of the invention fully considers the genetic inheritance relationship of the grain size in different stages and the influence of different parameters on the grain size and its distribution during the hot deformation process. The material constants in the above model can be obtained through multiple non-linear regression.

[0027] Generally speaking, compared with the prior art, the above technical solution conceived by the present invention can achieve the following beneficial effects:

[0028] (1) The present invention fully considers the influence of different conditions on the grain evolution during the heating and heat preservation, hot deformation, and inter-pass heat preservation processes, so that the established model can accurately describe the grain size evolution under different working conditions.

[0029] (2) The present invention fully considers the genetic inheritance relationship of the grain evolution during the multi-pass or multi-heat deformation process, so that the established model can accurately describe the mutual influence relationship between the deformation parameters and the grain size in different stages.

[0030] (3) The present invention proposes a modified Zener–Hollomon parameter. By combining the critical value of the modified Zener–Hollomon parameter with the critical strain, the start and end signs of dynamic recrystallization under different deformation temperatures, strain rates, and strains can be accurately determined. Furthermore, a more accurate average dynamic recrystallized grain size model and average grain size model are constructed.

[0031] (4) The present invention proposes a new average grain size model for the hot deformation process. Compared with the traditional empirical formula calculation method, the model proposed by the present invention is established based on microscopic statistical results and can more accurately describe the influence law of hot deformation parameters on the average grain size.

[0032] (5) The present invention establishes a unified average grain size model for the inter-pass holding process, which couples the influences of the static recrystallization mechanism and the meta-dynamic recrystallization mechanism, effectively avoiding the problem of inaccurate models caused by not considering the coupling effect of the two recrystallization mechanisms when separately establishing the static and meta-dynamic recrystallized grain size models. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the modeling process of the present invention.

[0034] Figure 2 It is the average grain size under different heating rates during the heating and holding process.

[0035] Figure 3 It is the average grain size under different holding temperatures during the heating and holding process.

[0036] Figure 4 It is the comparison between the predicted value and the experimental value of the average grain size during the heating and holding process.

[0037] Figure 5 It is the comparison between the predicted value and the experimental value of the critical strain during the hot deformation process.

[0038] Figure 6 It is the average dynamically recrystallized grain size under different deformation parameters during the hot deformation process.

[0039] Figure 7 It is the average grain size under different deformation parameters during the hot deformation process.

[0040] Figure 8 It is the comparison between the predicted value and the experimental value of the average dynamically recrystallized grain size during the hot deformation process.

[0041] Figure 9 It is the comparison between the predicted value and the experimental value of the average grain size during the hot deformation process.

[0042] Figure 10is the average post - dynamic recrystallization grain size at different holding temperatures during the inter - pass holding process.

[0043] Figure 11 is the average post - dynamic recrystallization grain size at different pre - strains during the inter - pass holding process.

[0044] Figure 12 is the average post - dynamic recrystallization grain size at different strain rates during the inter - pass holding process.

[0045] Figure 13 is the comparison between the predicted value and the experimental value of the average post - dynamic recrystallization grain size during the inter - pass holding process. Specific Embodiments

[0046] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0047] Taking the multi - pass hot forging forming of 300M high - strength steel for aircraft landing gears as an example, the precise modeling method for the grain size evolution of the entire hot forging process of the present invention mainly includes the following steps:

[0048] Step 1: Conduct heating and holding experiments using a high - temperature laser confocal scanning microscope, where the heating rate range is 2 - 15 K / s, the holding temperature range is 1173 - 1473 K, the holding time is 600 s, and the specimen size is 8 mm in diameter and 3 mm in height. First, place the specimen into the high - temperature laser confocal scanning microscope, then perform vacuum pumping on the equipment three times to ensure that the specimen is not oxidized during the heating and holding process. Subsequently, heat the specimen at the set heating rate. When the heating reaches the set temperature, start the holding process. When the holding time reaches 600 s, immediately quench the specimen with argon. During the heating and holding process, the equipment will automatically record the changes in the microstructure of the specimen in real - time. At the end of the experiment, use Image ProPlus software to count the grain sizes of the specimens under different heating and holding parameters. The results are as Figure 2 and Figure 3 shown. According to the average grain sizes counted under different heating and holding parameters, the constant values of each material in formula (1) can be obtained by using multiple non - linear regression analysis. The calculation results are shown in Table 1. Compare the calculation results of formula (1) with the average grain sizes counted in the heating and holding experiments as Figure 4As shown, the correlation coefficient between the two is 0.99963, indicating that the established grain evolution model during the heating and holding process can accurately describe the effects of heating rate, holding temperature, and holding time on grain evolution.

[0049] Table 1 Material constant values in formula (1)

[0050] α β γ <![CDATA[Q g > 28767.5 0.349 -0.033 92895.4

[0051] Step 2: Use the Gleeble3500 thermal simulation equipment to conduct hot compression experiments under different austenitizing temperatures, strain rates, deformation temperatures, and strains, where the austenitizing temperature range is 1173 - 1473K, the strain rate range is 0.01 - 10s -1 , the deformation temperature range is 1173 - 1473K, and the strain range is 0 - 1.2. The diameter of the hot compression specimen is 8mm and the height is 12mm. First, weld a resistance wire at the center of the specimen for temperature control, place graphite sheets and tantalum sheets at both ends of the specimen to reduce the friction between the specimen and the anvils and play a heat insulation role at the same time. Subsequently, place the specimen in the Gleeble3500 thermal simulation equipment and evacuate the equipment to prevent the specimen from being oxidized during the deformation process. After the above preparations are completed, heat the specimen to the set austenitizing temperature at a heating rate of 5K / s, then hold for 240s to achieve temperature uniformity inside the specimen. Subsequently, cool the specimen temperature to the set deformation temperature at a cooling rate of 5K / s and hold for 60s to eliminate the possible temperature gradient inside the specimen during the cooling process. Finally, conduct a hot compression experiment at the set deformation temperature and strain rate. When the deformation amount of the hot compression specimen reaches the set value, the equipment automatically quenches the specimen to retain the high-temperature microstructure.

[0052] According to the stress-strain curves obtained from the experiments, the critical strains of the material under different deformation parameters are calculated by taking the derivative of stress with respect to strain as shown in Table 2. Based on the critical strains under different deformation parameters, the parameter values in formula (3) can be obtained by using multiple nonlinear regression analysis as shown in Table 3. Figure 5 For the comparison between the calculated value and the experimental value of the critical strain, the correlation coefficient between the two is 0.99591, indicating that the established critical strain model is reliable.

[0053] Subsequently, the deformed specimens are subjected to metallographic corrosion, and the average dynamic recrystallized grain size and average grain size under different deformation parameters are statistically analyzed using Image Pro Plus software as Figure 6 and Figure 7 shown. Based on the statistical values of the average grain size and average dynamic recrystallized grain size under different deformation parameters, the material constants in formulas (2) and (4) can be calculated through multiple nonlinear regression analysis, and the calculation results are shown in Tables 4 and 5. Figure 8For the comparison between the experimental value and the predicted value of the average dynamic recrystallized grain size, it can be seen that the correlation coefficient between the two is 0.97664. Figure 9 For the comparison between the experimental value and the predicted value of the average grain size, the correlation coefficient between the two is 0.97807. The above results indicate that the established model can accurately describe the average dynamic recrystallization and the change of average grain size under different deformation parameters.

[0054] Table 2 Critical strain under different deformation parameters

[0055] Austenitizing temperature / K Deformation temperature / K <![CDATA[Strain rate / s -1 > Critical strain 1473 1173 0.01 0.221 1473 1273 0.01 0.144 1473 1373 0.01 0.101 1473 1473 0.01 0.073 1473 1173 0.1 0.25 1473 1273 0.1 0.185 1473 1373 0.1 0.141 1473 1473 0.1 0.108 1473 1173 1 0.292 1473 1273 1 0.245 1473 1373 1 0.209 1473 1473 1 0.182 1473 1173 10 0.326 1473 1273 10 0.29 1473 1373 10 0.262 1473 1473 10 0.248 1173 1273 0.01 0.093 1273 1273 0.01 0.108 1373 1273 0.01 0.123

[0056] Table 3 Material constant values in formula (3)

[0057]

[0058] Table 4 Material constant values in formula (2)

[0059] lnδ ∈ ζ η θ 11.44 -0.196 -0.131 0.622 -0.238

[0060] Table 5 Material constant values in formula (4)

[0061]

[0062] Step 3: Cut the deformed specimen in step 2 along the central part of the specimen. Since the deformation in the central region of the specimen is uniform, take the central plane of the specimen as the observation surface, and make a small cylinder with a diameter of 5 mm and a height of 1 mm for the study of the inter-pass holding process in a high-temperature laser confocal scanning microscope. The operating steps of the high-temperature laser confocal are the same as those in step 1, except that during the inter-pass holding process, it is heated at the fastest heating rate of the equipment, which is 16.6 K / s. The holding temperature range is 1173 - 1473 K, and the holding time is 600 s. When the holding time reaches the set value, the equipment will automatically quench the specimen. Conduct a statistical analysis on the microstructures under different inter-pass holding parameters, and the obtained average post-dynamic recrystallized grain sizes are as Figures 10 - 12 shown. According to the statistically obtained average post-dynamic recrystallized grain sizes under different inter-pass holding parameters, the parameter values in formula (5) can be calculated by using multiple nonlinear regression analysis as shown in Table 6. Figure 13 is the comparison between the experimental value and the predicted value of the average post-dynamic recrystallized grain size. It can be seen that the correlation coefficient between the two is 0.97241, indicating that the established model is reliable.

[0063] Table 6 Material constant values in formula (5)

[0064]

[0065] So far, the grain size models for the three typical stages in the multi-pass deformation process of 300M high-strength steel have been established. The grain size during the inter-pass holding process will be used as the initial grain size for the next deformation process, and by cycling in this way, the grain size evolution during the multi-pass deformation process of 300M high-strength steel can be accurately predicted. Further, by secondary development of the finite element simulation software, the grain size evolution during the multi-pass deformation process of 300M high-strength steel can be accurately simulated. From the correlation coefficient between the above predicted values and experimental values, it can be seen that the model established according to the method of the present invention has high accuracy, can comprehensively and accurately describe the influence of different parameters on grain evolution, and can also well describe the genetic inheritance relationship of grain size.

Claims

1. An accurate modeling method for the grain size evolution of the entire hot forging process of an aviation key load-bearing component, characterized in that Including the following steps: Step 1: Conduct heating and holding experiments on the materials used to manufacture the key load-bearing components of aircraft under different initial grain sizes, heating rates, holding temperatures, and holding times, and statistically calculate the corresponding average grain sizes; based on the statistically obtained grain sizes, establish a grain growth model for the heating and holding process as shown in Equation (1): Among them, D g is the grain size during the heating and heat preservation process, α, β, γ are material constants, Q g is the grain growth activation energy, R is the gas constant, T g is the heat preservation temperature, t g is the heat preservation time, is the heating rate; Step 2: After the heating and holding process ends, the material enters the hot deformation process. Conduct hot compression experiments under different deformation temperatures, strain rates, strains, and initial grain sizes through a hot simulation experimental device. Corrode the experimental results metallographically and statistically calculate their average dynamically recrystallized grain sizes and average grain sizes; based on the statistically obtained grain sizes, establish an average dynamically recrystallized grain size model and an average grain size model for the hot deformation process; among them, the average dynamically recrystallized grain size model for the hot deformation process is as shown in Equation (2): Among them, D d is the average dynamic recrystallized grain size, δ, ∈, ζ, η, θ are material constants, Q d is the deformation activation energy, is the strain rate, ε is the strain, T d is the deformation temperature, ε c is the critical strain; the critical strain is calculated using Equation (3): where ω, ψ, χ, are material constants; The average grain size model for the hot deformation process is as shown in Equation (4): Among them, D a is the average grain size during the hot deformation process, ι, κ, and λ are material constants; is the correction of the Zener–Hollomon parameter; Z mc is Z m 's critical value. When Z m is greater than Z mc , that is, the dynamic recrystallization is incomplete. At this time, the material is composed of elongated grains and dynamically recrystallized grains; conversely, the dynamic recrystallization in the material is complete, and all the grains in the material are composed of dynamically recrystallized grains. Step 3: When the deformation process ends, the material enters the inter-pass holding process. Static recrystallization, meta-dynamic recrystallization, or both occur simultaneously during the inter-pass holding process. The average grain size model for the inter-pass holding process is calculated through Equation (5): Among them, D s is the average grain size during the static heat preservation process, v, ξ, ρ, φ are material constants, ε r is the pre-strain, Q s is the activation energy for post-dynamic recrystallization, T s is the inter-pass heat preservation temperature, t s is the inter-pass heat preservation time; When the above three typical stages, namely the heating and holding process, the hot deformation process, and the inter-pass holding process, are completed, the average grain size of the inter-pass holding is used as the initial grain size for the next deformation process. The method for establishing the grain size model repeats Steps 2 and 3; the material constants in the above models can be obtained through multiple nonlinear regression.

2. A precise modeling method for the grain size evolution of the entire hot forging process of key load-bearing components of aircraft according to Claim 1, characterized in that the heating and holding experiment described in Step 1 is carried out using a heating furnace or a hot simulation experimental machine, or using an in-situ high-temperature device of a high-temperature laser confocal scanning microscope.

3. A precise modeling method for the grain size evolution in the whole hot forging process of an aviation key load-bearing component according to claim 1, characterized in that The hot simulation experiment described in Step 2 is a hot compression experiment, a hot tensile experiment, or a hot torsion experiment, which is determined according to the actual stress state of the component during the actual hot deformation process; the sample size and shape of the hot simulation experiment are determined according to the actual forming process.

4. A precise modeling method for the grain size evolution of the entire hot forging process of key load-bearing components of aircraft according to Claim 1, characterized in that the experiment on the grain evolution during the inter-pass holding process described in Step 3 is carried out using a hot simulation experimental machine or an in-situ device of a high-temperature laser confocal scanning microscope.

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