A method for predicting the evolution behavior of high temperature austenite structure under non-isothermal heating conditions

Abstract

The present application relates to a method for predicting the evolution behavior of high-temperature austenite organization under non-isothermal heating conditions, belonging to the field of metal materials. The method uses a high-temperature laser confocal microscope to obtain the evolution data of austenite grain size with time under isothermal heating conditions, and establishes an isothermal austenite grain growth model. On this basis, by differentiating the isothermal model and introducing the relationship between heating rate, temperature and time, an austenite grain growth model under non-isothermal heating conditions is constructed. The model parameters are fitted by experimental data, and the model index is determined with the optimization objective of minimizing the prediction error, realizing the prediction of high-temperature austenite grain size under different heating rates, different initial heating temperatures and final heating temperatures. The method can effectively characterize the influence of heating rate, initial heating temperature and final heating temperature on the evolution behavior of austenite grains during non-isothermal heating process, and the model prediction results have good consistency with the measured results.

Description

Technical Field

[0001] This invention belongs to the field of metallic materials and relates to a method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions. Background Technology

[0002] Hot-rolled steel sheets and strips are key materials for manufacturing components such as vehicle body structural parts, heavy equipment frames, and aero-engine parts, accounting for up to 27% of the total output of all metallic materials. Ensuring stable production of hot-rolled products and optimizing their mechanical properties is a current research focus. To maintain the stability of the hot rolling process, strict control of the austenite grain size in the rolled product is necessary. The high-temperature austenite evolution behavior is a crucial factor determining the quality of rolled products, and the initial austenite grain size significantly influences the phase transformation behavior and mechanical properties of hot-rolled products. Generally, fine grains are the primary means of simultaneously improving material strength and plasticity, and the post-rolling ferrite grain size is directly related to the initial austenite grain size of the cast billet. Therefore, studying the austenite grain size evolution behavior during hot rolling heating and predicting the influence of heating process parameters on the initial austenite grain size is of great significance for controlling the mechanical properties of hot-rolled sheets and strips.

[0003] Currently, there are some studies on the prediction of austenite grain size. Chinese patent CN117434100A discloses a method for determining the critical coarsening temperature of austenite grains, focusing on low-alloy high-strength structural steel Q420. It determines the austenite grain coarsening temperature of Q420 steel to be 1150℃ using a two-dimensional coordinate graph of heating temperature versus grain size. However, this patent does not establish a model relating the heating process to austenite grain size. Chinese patent CN114049920B proposes a method for predicting the grain size of alloy materials containing precipitates after solution heat treatment. It predicts the grain size changes of 7075 aluminum alloy during solution treatment by integrating a precipitate dissolution calculation model, a particle pinning force model, and a grain growth microstructure evolution model. However, this patent focuses more on the influence of precipitate kinetics on grain size in aluminum alloys and cannot provide a reference for the evolution of austenite grain size in low-alloy high-strength structural steel. Chinese patent CN111521461A discloses a method for predicting the austenite grain growth behavior during the heating process of continuously cast billets, and derives a grain growth model under non-isothermal conditions based on the austenite grain growth prediction model under isothermal conditions. However, this patent mainly derives the non-isothermal model based on temperature changes, and does not introduce the heating rate as an independent and controllable key process parameter into the model for systematic modeling.

[0004] In summary, although existing technologies have made some progress in predicting austenite grain growth, they still generally suffer from the following shortcomings: (1) There is a lack of modeling methods for the evolution behavior of austenite grains under non-isothermal actual process conditions; (2) The influence of heating rate, a key control parameter in the non-isothermal heating process, on the evolution behavior of austenite grains was not fully considered; (3) It is difficult to make high-precision predictions of austenite grain size under actual industrial conditions such as induction heating or continuous heating.

[0005] Therefore, it is urgent to propose a method for predicting austenite grain evolution that can be applied to non-isothermal heating conditions by introducing the heating rate factor on the basis of the isothermal grain growth model, so as to provide a theoretical basis for the optimization of hot rolling process. Summary of the Invention

[0006] In view of this, the present invention aims to overcome the problems of existing isothermal grain growth models that are difficult to reflect non-isothermal heating conditions in actual production, the influence of heating rate is not fully considered, and the prediction results are difficult to directly guide the optimization of induction heating or continuous heating process parameters. It provides a method for predicting the evolution behavior of high-temperature austenite microstructure under non-isothermal heating conditions. It can not only predict the evolution of austenite grain size during isothermal heating, but also calculate the high-temperature austenite grain size under different heating temperatures and heating rates for real-time heating processes such as induction heating and tunnel furnace heating in hot rolling.

[0007] To achieve the above objectives, the present invention provides a method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions, comprising the following steps: First, under the conditions of high-temperature laser confocal microscopy, a heating experiment was conducted on the steel material sample, and data on the change of austenite grain size over time were obtained in real time. Under isothermal heating conditions, based on the obtained grain size data, an isothermal austenite grain growth model is established, which satisfies the following formula (1): (1) Where: D0 is the initial grain size in μm; D is the grain size after heat preservation in μm; t is the heat preservation time in s; Q is the grain growth activation energy in J / mol; R is the gas constant, taken as 8.314 J / (mol·K); T is the heating temperature in K; A and n are constants related to materials and processes; Based on the isothermal austenite grain growth model, the formula (1) is differentiated and the relationship between heating rate and temperature and time is introduced to construct an austenite grain growth model under non-isothermal heating conditions, which is used to predict the evolution behavior of austenite grain size under different heating rate conditions.

[0008] Specifically, differentiating both sides of the above formula (1) with respect to time, we obtain the following formula (2): (2) And combine the relationship between heating rate and temperature and time By transforming and integrating formula (2), we obtain the austenite grain growth model under non-isothermal conditions, as shown in formula (3): (3) in: The starting heating temperature, in K; The final heating temperature is expressed in Kelvin (K).

[0009] Furthermore, when constructing a non-isothermal austenite grain growth model, the value of the exponent n is first given, and the parameters A and Q are fitted by experimental data. The error between the model calculation value and the experimental measured value is used as a function of n, and the minimum error is used as the optimization objective to determine the parameters A, Q and n.

[0010] Furthermore, the grain growth activation energy Q ranges from 250,000 to 300,000 J / mol, and the exponent n ranges from 3 to 8.

[0011] Furthermore, the heating temperature under the isothermal heating condition is 950–1250°C, and the holding time is 1800 s.

[0012] Furthermore, before performing non-isothermal heating, the sample is first heated to 850–950°C and held for 30 seconds before non-isothermal heating is performed.

[0013] Furthermore, the heating rate of the non-isothermal heating process is 0.5–30 °C / s. Furthermore, an in-situ characterization platform was constructed based on a high-temperature laser confocal microscopy imaging system. By monitoring the grain size changes in real time through grain boundary migration trajectories, the evolution process of high-temperature austenite grains was quantitatively characterized.

[0014] Furthermore, the non-isothermal austenite grain growth model is used to predict the high-temperature austenite grain size under real-time heating process conditions such as induction heating or tunnel furnace heating.

[0015] Furthermore, the average relative error between the grain size predicted by the non-isothermal austenite grain growth model and the experimentally measured grain size is controlled within ±11%.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) It can accurately describe the evolution behavior of austenite grains under non-isothermal heating conditions. Based on the isothermal grain growth model, this invention introduces a heating rate factor, which overcomes the defect of traditional isothermal models that cannot reflect the continuous temperature change in actual hot rolling heating process, making the model more consistent with actual industrial heating conditions.

[0017] (2) The heating rate is incorporated as a key process parameter into the prediction model. By constructing a non-isothermal austenite grain growth model that includes the heating rate, heating start temperature and heating end temperature, the quantitative prediction of grain evolution behavior under non-isothermal heating regimes such as induction heating and tunnel furnace heating is realized.

[0018] (3) The model parameters are clearly derived, the prediction accuracy is high, and the applicability is strong. This invention retrieves the model parameters from isothermal experimental data and verifies the model with experimental measured values, so that the established non-isothermal grain growth model has good prediction accuracy. The average relative error of its grain size prediction can be controlled within ±11%, which has high application value.

[0019] (4) The method is highly versatile and applicable to a variety of low-alloy steel material systems. The method of this invention is based on the general theory of grain growth kinetics and experimental modeling ideas. It does not depend on a specific production line or a single steel grade. After adjusting the material composition and process parameters, it can be extended to the hot rolling heating process of different steel grades.

[0020] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0021] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a thermal history diagram of the non-isothermal heating sample of the present invention; Figure 2 The relative error predicted by the isothermal grain growth model under different n values ​​in this invention; Figure 3 The microstructures corresponding to different heating rates at a heating temperature of 1230℃ in Example 1 of the present invention are: (a) 0.5℃ / s; (b) 5℃ / s; (c) 30℃ / s; Figure 4 This is to compare the predicted values ​​and measured values ​​obtained by the prediction method of the induction heating process of the present invention for predicting the evolution behavior of high-temperature austenite structure. Detailed Implementation

[0022] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0023] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0024] I. Explanation of Implementation Principles This invention is based on the understanding that during hot rolling heating and reheating, the evolution behavior of austenite grains is affected not only by heating temperature and holding time, but also significantly by changes in heating rate. Traditional grain growth models based solely on isothermal conditions are insufficient to accurately describe the non-isothermal heating processes that are prevalent in actual production.

[0025] Therefore, this invention first records the evolution of austenite grain size over time in real time using a high-temperature laser confocal microscope under isothermal heating conditions, and establishes an isothermal grain growth model. Based on this, the isothermal grain growth model is mathematically derived, and the relationship between heating rate and temperature and time is introduced to construct an austenite grain growth model under non-isothermal heating conditions, thereby enabling the prediction of the evolution behavior of high-temperature austenite microstructure under different heating rates.

[0026] II. Establishment of the Isothermal Grain Growth Model Under isothermal heating conditions, the austenite grain growth behavior satisfies the following relationship: (1) in: D0 is the initial grain size, in μm; D represents the grain size after heat preservation, in μm. t represents the heat preservation time, measured in seconds (s). Q is the activation energy for grain growth, expressed in J / mol. R is the gas constant, taken as 8.314 J / (mol·K); T represents the heating temperature, measured in K. A and n are constants related to materials and processes.

[0027] By conducting heat preservation experiments under different isothermal temperature conditions and measuring the grain size change in real time, the parameters A, Q, and n can be fitted using the experimental data, thereby establishing an isothermal grain growth model suitable for the target steel grade.

[0028] III. Derivation of the Non-Isothermal Grain Growth Model Differentiating both sides of equation (1) with respect to time t, we get: (2) Under non-isothermal heating conditions, the heating rate satisfies the following relationship with temperature and time:

[0029] Substituting the heating rate into equation (2), and performing corresponding transformations and integrations, the grain growth model under non-isothermal conditions can be derived: (3) in: The starting heating temperature, in K; The final heating temperature is expressed in Kelvin (K).

[0030] Formula (3) can be used to predict the austenite grain size under different heating rates, given the known isothermal model parameters A, Q, and n.

[0031] IV. Parameter Determination Method In practical applications, this invention first gives an initial range of values ​​for the exponent n, fits parameters A and Q with experimental data, compares the grain size calculated by the model with the experimentally measured grain size, takes the calculation error as a function of n, takes the minimum error as the optimization target, and finally determines the parameter combination suitable for the target steel grade.

[0032] in: The value of n ranges from 3 to 8; The value of Q ranges from 250,000 to 300,000 J / mol; A is a constant related to the materials and process conditions, and its specific value is obtained by fitting experimental data.

[0033] Verification has shown that the non-isothermal grain growth model established in this invention has an average relative error in grain size prediction that is controlled within ±11%. V. Specific Implementation Method 1 The experimental conditions for Example 1 are as follows: S1: Low-alloy high-strength steel was selected as the experimental sample. The composition (mass percentage) of its billet is as follows: C: 0.146%; Si: 0.05%; Mn: 0.4%; P: 0.021%; S: 0.012%; Cr: 0.028%; Ni: 0.021%; Cu: 0.022%; Als: 0.015%; V: 0.41%, with the balance being Fe and its unavoidable impurities.

[0035] S2: The billet is processed into a high-temperature laser confocal microscope test sample, cut into cylindrical samples with a diameter of 5 mm and a height of 4 mm, and the sample surface is ground and polished.

[0036] S3: Place the prepared cylindrical test sample in the crucible of a high-temperature laser confocal microscope and heat it to 950℃, 1000℃, 1050℃, 1100℃, 1150℃, 1200℃ and 1250℃ respectively at a heating rate of 10℃ / s, and hold it at each temperature for 1800s.

[0037] S4: During the heat preservation process, the grain size of the sample is recorded in real time using a high-temperature laser confocal microscope to obtain the grain size change law of the sample under isothermal heating conditions, and an isothermal grain growth model is established based on the experimental data.

[0038] S5: Heat the sample to 850℃ at a heating rate of 10℃ / s and hold for 30s.

[0039] S6: Heat the sample treated with S5 to 1250℃ at heating rates of 0.5℃ / s, 2℃ / s, 5℃ / s, 10℃ / s, and 30℃ / s.

[0040] S7: During the non-isothermal heating process, the grain size change of the sample is recorded in real time by a high-temperature laser confocal microscope to obtain grain size evolution data under different heating rates.

[0041] S8: Based on the isothermal grain growth model and combined with experimental data under different heating rates, the evolution behavior of high-temperature austenite grain size under different induction heating process parameters is analyzed. An austenite grain growth model under non-isothermal conditions is established, and the model calculation results are compared with the experimental results.

[0042] The non-isothermal grain growth model established in this embodiment has been verified to have an average relative error of 10.7% in predicting grain size. VI. Specific Implementation Example 2 Example 2 follows the same method steps as Example 1, the difference being the composition of the experimental sample and the starting temperature of the non-isothermal heating.

[0044] S1: The composition (mass percentage) of the cast billet of the experimental sample is as follows: C: 0.152%; Si: 0.11%; Mn: 0.51%; P: 0.018%; S: 0.010%; Cr: 0.021%; Ni: 0.018%; Cu: 0.022%; Als: 0.013%; V: 0.35%, with the balance being Fe and its unavoidable impurities.

[0045] S5: Heat the sample to 900℃ at a heating rate of 10℃ / s and hold for 30 s.

[0046] The remaining steps are the same as in Example 1.

[0047] The non-isothermal grain growth model established in this embodiment has been verified to have an average relative error of 10.2% in predicting grain size. VII. Specific Implementation Method 3 Example 3 follows the same method steps as Example 1, the difference being the composition of the experimental sample and the starting temperature of the non-isothermal heating.

[0049] S1: The composition (mass percentage) of the cast billet of the experimental sample is as follows: C: 0.184%; Si: 0.15%; Mn: 0.6%; P: 0.019%; S: 0.013%; Cr: 0.025%; Ni: 0.024%; Cu: 0.023%; Als: 0.011%; V: 0.32%, with the balance being Fe and its unavoidable impurities.

[0050] S5: Heat the sample to 950℃ at a heating rate of 10℃ / s and hold for 30 s.

[0051] The remaining steps are the same as in Example 1.

[0052] The non-isothermal grain growth model established in this embodiment has been verified to have an average relative error of 9.8% in predicting grain size.

[0053] VIII. Description of Implementation Methods (with Reference Drawings) To further illustrate the method of predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions, the specific implementation process and experimental results of the present invention will be further explained below with reference to the accompanying drawings.

[0054] Figure 1 Typical thermal history curves of the sample during non-isothermal heating in embodiments of the present invention are shown.

[0055] The sample is first heated from room temperature to the predetermined initial heating temperature at a heating rate of 10℃ / s, and then held at that temperature for a short time. Subsequently, the temperature is continued to rise to the rolling temperature range at different heating rates to complete the non-isothermal heating process.

[0056] By setting different heating rate conditions, the non-isothermal heating behavior under induction heating or continuous heating processes in actual hot rolling production can be simulated, providing an experimental basis for the subsequent analysis of austenite grain evolution and model establishment.

[0057] Figure 2 The average relative error of the isothermal austenite grain growth model prediction results is shown under different values ​​of the exponent n.

[0058] By comparing the grain size calculated by the isothermal grain growth model with the experimentally measured grain size, it can be seen that the model prediction error first decreases and then increases with the value of n, and reaches its minimum near a certain value of n.

[0059] In this invention, it is based on Figure 2 The error variation pattern shown is used to treat the prediction error as a function of n, and the minimum error is taken as the optimization objective. This determines the range of values ​​for the exponent n applicable to the target steel grade, and further fits the model parameters A and Q to obtain them. This parameter determination method provides a reliable parameter basis for the subsequent construction of a non-isothermal austenite grain growth model.

[0060] Figure 3 (a)~ Figure 3 (c) The microstructures of high-temperature austenite under different heating rates at the same final heating temperature (1250℃) are presented. Figure 3 (a) is under conditions of a lower heating rate (0.5℃ / s). Figure 3 (b) is under medium heating rate conditions (5℃ / s). Figure 3 (c) represents a higher heating rate condition (30℃ / s), with a scale bar of 50μm.

[0061] from Figure 3 It can be seen that under lower heating rates, austenite grains have a longer growth time and relatively larger grain sizes; as the heating rate increases, the austenite grain growth process is suppressed, and the grain size decreases significantly. These experimental results indicate that under non-isothermal heating conditions, the heating rate has a significant impact on the evolution behavior of austenite grains.

[0062] Figure 3 The microstructure comparison results shown experimentally verify the rationality and necessity of introducing heating rate as a key parameter in the non-isothermal heating grain evolution model.

[0063] Figure 4The invention illustrates the prediction method for the evolution of high-temperature austenite microstructure during induction heating, and compares the calculated results of austenite grain size prediction under different non-isothermal heating conditions with the corresponding experimentally measured grain size.

[0064] from Figure 4 It can be seen that the model predictions and experimental measurements are generally distributed near the diagonal, showing good consistency. Statistical analysis shows that the average relative error between the model-predicted grain size and the experimentally measured grain size is controlled within ±11%, indicating that the non-isothermal austenite grain growth model established in this invention can accurately describe the evolution behavior of high-temperature austenite grains under different heating rates, demonstrating high prediction accuracy and application value.

[0065] In summary, based on the model, it is possible to predict the high-temperature austenite grain size under different heating rates, different heating start temperatures, and different heating end temperatures.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions, characterized in that, Includes the following steps: Under high-temperature laser confocal microscopy, a heating experiment was conducted on steel material samples, and data on the change of austenite grain size over time were acquired in real time. Under isothermal heating conditions, based on the obtained grain size data, an isothermal austenite grain growth model is established, which satisfies the following formula (1): （1） Where: D0 is the initial grain size in μm; D is the grain size after heat preservation in μm; t is the heat preservation time in s; Q is the grain growth activation energy in J / mol; R is the gas constant, taken as 8.314 J / (mol·K); T is the heating temperature in K; A and n are constants related to materials and processes; Based on the isothermal austenite grain growth model, the formula (1) is differentiated and the relationship between heating rate and temperature and time is introduced to construct an austenite grain growth model under non-isothermal heating conditions, so as to calculate the austenite grain size under different heating rate conditions based on the model.

2. The method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to claim 1, characterized in that, Differentiating both sides of the above formula (1) with respect to time, we obtain the following formula (2): （2） And combine the relationship between heating rate and temperature and time By transforming and integrating formula (2), we obtain the austenite grain growth model under non-isothermal conditions, as shown in formula (3): （3） in: The starting heating temperature, in K; The final heating temperature is expressed in Kelvin (K).

3. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to claim 1 or 2, characterized in that, When constructing a non-isothermal austenite grain growth model, the value of the exponent n is first given, and the parameters A and Q are fitted by experimental data. The error between the model calculation value and the experimental measured value is used as a function of n, and the minimum error is used as the optimization objective to determine the parameters A, Q and n.

4. The method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to claim 3, characterized in that, The grain growth activation energy Q ranges from 250,000 to 300,000 J / mol, and the exponent n ranges from 3 to 8.

5. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to any one of claims 3, characterized in that, The heating temperature under the isothermal heating conditions is 950–1250°C, and the holding time is 1800 s.

6. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to any one of claims 3, characterized in that, Before performing non-isothermal heating, the sample is first heated to 850–950°C and held for 30 seconds before proceeding with non-isothermal heating.

7. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to any one of claims 3, characterized in that, The heating rate of the non-isothermal heating process is 0.5–30 °C / s.

8. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to any one of claims 3, characterized in that, An in-situ characterization platform was constructed based on a high-temperature laser confocal microscopy system. The changes in grain size were monitored in real time by observing the grain boundary migration trajectory, and the evolution process of high-temperature austenite grains was quantitatively characterized.

9. A method for predicting the evolution behavior of high-temperature austenitic microstructure under non-isothermal heating conditions according to any one of claims 3, characterized in that, The non-isothermal austenite grain growth model is used to predict the high-temperature austenite grain size under real-time heating process conditions such as induction heating or tunnel furnace heating.

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