Method for judging and predicting generation of center crack of alloy steel continuous casting billet by combining numerical simulation and experiment

Abstract

The invention discloses a method for judging and predicting generation of center cracks of alloy steel continuous casting billets by combining numerical simulation and experiments, which comprises the following steps of: sampling the continuous casting billets to obtain at least one sample group; treating part of the samples in the sample group according to a preset heating and cooling rate treatment process, and carrying out differential scanning calorimetry analysis on the samples to obtain liquidus temperature and solidus temperature; performing dynamic high-temperature tensile tests on a plurality of groups of samples on part of the samples in the sample group to obtain stress and section shrinkage curves at different tensile temperatures; according to corresponding parameters of the current sample steel grade, simulating and calculating simulation values about stress, a section shrinkage curve and temperature when cracks are generated; and adjusting the current corresponding parameters until the difference value between the simulation value and the corresponding numerical values of the stress and area reduction curve at different stretching temperatures is within a first preset range. The method can effectively solve the problem of unreliable judgment and prediction of the center crack of the alloy steel continuous casting billet.

Description

Technical Field

[0001] The present invention relates to the field of casting technology, and more particularly to a method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiments. Background Art

[0002] In the early stages of continuous casting of alloy steel round billets, the primary focus was on producing small-sized seamless steel pipes. However, driven by industrial demand and improvements in production technology, large-sized and highly alloyed round billets have become increasingly important in continuous casting, serving as the foundation for manufacturing key industrial equipment such as alloy steel round bars and large rings. However, the slow casting speeds, long solidification times, and low center cooling rates of large round billets during continuous casting create serious center quality issues that require urgent resolution. Cracks, which account for approximately 50% of defects in continuous casting billet production, often occur between the zero plasticity temperature (ZDT) and the zero strength temperature (ZST). Consequently, existing techniques have proposed the existence of a viscosity temperature (LIT), further dividing the ZDT to ZST temperature range into the LIT-ZST (molten steel feeding zone) and the ZDT-LIT (cracking zone).

[0003] Regarding the use of numerical simulation to predict the initiation and generation of central cracks in continuous casting slabs, Chinese patent publication number CN103920859A discloses an "online prediction method for internal cracks in continuous casting slabs." This method establishes a two-dimensional solidification heat transfer thermal tracking model for several slices, calculates the bulging strain of the slab in real time based on temperature and solidification parameters, and sets a critical strain value as the initiation criterion for internal cracks. Chinese patent publication number CN102527971A discloses an "online prediction method for internal crack defects in slabs." This method uses real-time online simulation to calculate the internal stress and strain information of the slab, and predicts internal crack defects in the slab in real time based on the strain variation trend. This method can be widely used in the optimization and control of the continuous casting slab cutting process.

[0004] Regarding the experimental detection and prediction of central cracks in continuous casting slabs, Chinese Patent Publication No. CN111024513A discloses a method for conducting dynamic high-temperature thermal simulation and high-temperature tensile testing on continuous casting slab specimens. The experimental crack initiation temperature is determined based on the fracture morphology and liquid phase fraction of the stretched specimens. The strain range for crack initiation is then determined from the stress-strain curve. Finally, tensile tests are conducted at different strain levels at the crack initiation temperature. The presence of cracks in the specimens with different strain levels is examined to determine the critical strain for central crack initiation. Chinese Patent Publication No. CN114993797A discloses a method for analyzing the correlation between crack initiation and propagation behavior and the microstructure of the metal material by simply cutting, grinding, polishing, and etching the specimens after tensile fracture. The method then uses a metallographic microscope or scanning electron microscope to observe the pores, cracks, and microstructure characteristics of the cross-section 1-2 mm below the fracture surface.

[0005] The crack formation and prediction methods are single and do not closely link experimental data and numerical simulation methods.

[0006] In summary, how to effectively solve the problem of unreliable judgment and prediction of the occurrence of central cracks in alloy steel continuous casting billets is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide a method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiments. This method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiments can effectively solve the problem of unreliable judgment and prediction of the occurrence of central cracks in alloy steel continuous casting billets.

[0008] In order to achieve the above first object, the present invention provides the following technical solutions:

[0009] A method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiment includes the following steps:

[0010] Sampling the continuously cast slab to obtain at least one set of test specimens;

[0011] Treating some of the samples in the sample group according to a preset heating and cooling rate treatment process to perform differential scanning calorimetry analysis on the samples to obtain liquidus temperature and solidus temperature;

[0012] Performing several groups of dynamic high-temperature tensile tests on some of the samples in the sample group to obtain stress and cross-sectional shrinkage curves at different tensile temperatures;

[0013] Based on the corresponding parameters of the current sample steel grade, simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated are calculated; the corresponding parameters of the current sample steel grade are adjusted until the simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated are calculated, and the difference between the simulated values and the corresponding values of the stress and cross-sectional shrinkage curves at different stretching temperatures is within a first preset range.

[0014] In the above technical solution, by obtaining more appropriate parameters for the current sample steel grade, a more realistic simulation calculation method can be simulated, which can more accurately reflect the actual stress and end shrinkage values, and better judge and predict the occurrence of center cracks in alloy steel continuous casting billets. In summary, this method of combining numerical simulation and experiment to judge and predict the occurrence of center cracks in alloy steel continuous casting billets can effectively solve the problem of unreliable judgment and prediction of the occurrence of center cracks in alloy steel continuous casting billets.

[0015] Some technical solutions also include:

[0016] The stretched samples obtained by performing the dynamic high-temperature tensile test on several groups of samples are processed to obtain a treated cross section, and the actual critical strain and critical stress are determined based on the microscopic crack morphology on the treated cross section.

[0017] Some technical solutions also include:

[0018] Corresponding parameters of the current sample steel grade are set until the difference between the simulated values of the critical strain and critical stress calculated by simulation and the actual critical strain and critical stress is within a second preset range.

[0019] In some technical solutions, the processing of the stretched samples obtained by performing the dynamic high-temperature tensile tests on several groups of samples to obtain the processed cross-sections includes:

[0020] For the stretched specimens obtained by dynamic high temperature tensile tests on several groups of specimens, cutting, grinding, polishing and mounting are carried out in sequence;

[0021] The micro crack morphology is obtained through a metallographic microscope or a scanning electron microscope.

[0022] In some technical solutions, the corresponding parameters of the current sample steel grade include at least Poisson's ratio, Young's modulus, and thermal expansion coefficient.

[0023] In some technical solutions, the Poisson's ratio, Young's modulus, and thermal expansion coefficient are determined by the ZDT of the current sample steel grade.

[0024] In some technical solutions, the sampling of the continuous casting slab to obtain at least one sample group is:

[0025] Two groups of samples are taken from each of the three positions 1 / 4R, 1 / 2R and 3 / 4R from the center of the axial end surface of the continuous casting billet, where R is the radius of the continuous casting billet.

[0026] In some technical solutions, taking a sample group from the two sample groups includes:

[0027] Taking out a round rod from the continuous casting billet, wherein the axial extension direction of the round rod is consistent with the axial extension direction of the continuous casting billet;

[0028] The round rod is divided into a plurality of sections along the axial direction to form a sample group having a plurality of samples.

[0029] In some technical solutions, some samples in the sample group are processed according to a preset heating and cooling rate processing process, which is:

[0030] The sample is heated from room temperature to a first preset temperature at a first preset temperature change rate, and the sample is heated from the first preset temperature to a second preset temperature at a second preset temperature change rate, and the sampling period is a first preset time length; after the sample is kept warm for the second preset time length, the sample temperature is lowered to the first preset temperature at a cooling rate of the second preset temperature change rate, and the sample is lowered from the first preset temperature to room temperature at the first preset temperature change rate.

[0031] In some technical solutions, the first preset temperature change rate is 10~30℃ / min; the first preset temperature is 580℃ to 620℃; the second preset temperature change rate is 1~10℃ / min; the second preset temperature is 1500℃ to 1540℃; the first preset time is 0.9 seconds to 1.1 seconds; the second preset time is 9min to 10min. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 A schematic flow chart of a method for determining and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment, provided in an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of a continuous casting slab sampling position according to an embodiment of the present invention;

[0035] Figure 3 Schematic diagram of thermal analysis test results and solidus-liquidus temperature determination of continuous casting slab samples provided by an embodiment of the present invention;

[0036] Figure 4 Distribution curves of yield stress and area reduction at different temperatures provided by an embodiment of the present invention;

[0037] Figure 5 The high temperature tensile test and microstructure diagram of the P91 steel sample provided in the embodiment of the present invention;

[0038] Figure 6 The stress distribution and phase transformation of P91 steel at different temperatures provided by the embodiment of the present invention;

[0039] Figure 7 The present invention provides numerical simulation results of temperature, stress and elastic equivalent strain on the cross section of the continuous casting billet during the continuous casting process. DETAILED DESCRIPTION

[0040] Long-term research has revealed that crack formation generally occurs in three microscopic stages: first, intergranular tensile stress acts on the solidification interface; second, when the tensile stress exceeds its critical stress, cracking occurs along the intergranular interface of the primary dendrite; and third, when the solute-enriched molten steel is unable to fill these gaps, cracking occurs. Changes in the microstructure of the continuous casting ingot manifest macroscopically as numerical variations in stress, strain, and temperature gradients. The integration of experimental data and numerical simulation results for different steel grades offers promising insights into the rational control and prediction of central crack formation in alloy steel continuous casting ingots.

[0041] An embodiment of the present invention discloses a method for judging and predicting the occurrence of center cracks in alloy steel continuous casting billets by combining numerical simulation and experiments. The method conducts relevant experiments on the initiation of center cracks in the continuous casting billets, and uses numerical simulation means to accurately simulate the stress, strain and temperature gradient of the initiation of center cracks in the continuous casting billets. Countermeasures for reducing center crack defects in the production of continuous casting billets are proposed, thereby controlling crack defects and improving the quality of the core of the continuous casting billets.

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0043] See also Figure 1-Figure 7 , Figure 1 A schematic flow chart of a method for determining and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment, provided in an embodiment of the present invention; Figure 2 A schematic diagram of a continuous casting slab sampling position according to an embodiment of the present invention; Figure 3 Schematic diagram of thermal analysis test results and solidus-liquidus temperature determination of continuous casting slab samples provided by an embodiment of the present invention; Figure 4 Distribution curves of yield stress and area reduction at different temperatures provided by an embodiment of the present invention; Figure 5 High-temperature tensile test and microstructure diagram of a P91 steel (new martensitic heat-resistant steel) sample provided in an embodiment of the present invention; Figure 6 The stress distribution and phase transformation of P91 steel at different temperatures provided by the embodiment of the present invention; Figure 7 The present invention provides numerical simulation results of temperature, stress and elastic equivalent strain on the cross section of the continuous casting billet during the continuous casting process.

[0044] In some embodiments, a method combining numerical simulation and experimentation is provided to determine and predict the occurrence of center cracks in alloy steel continuous casting slabs. The method specifically includes the following steps:

[0045] S100: sampling the continuous casting slab to obtain at least one sample group.

[0046] A sample group needs to form multiple samples to facilitate subsequent differential scanning calorimetry analysis and dynamic high-temperature tensile testing. Specifically, the number of samples in a sample group can be selected according to subsequent needs.

[0047] Generally, multiple groups of samples need to be taken for subsequent experiments. The advantages of conducting multiple groups of the same experiment are: first, it can avoid different experimental results due to different locations; second, it can obtain more representative experimental data.

[0048] Specifically, as attached Figure 2 As shown, samples are taken from the axial end of the continuous casting billet at different distances from the center. For example, two sets of samples can be taken from the axial end of the continuous casting billet at positions 1 / 4R, 1 / 2R, and 3 / 4R from the center, where R is the radius of the continuous casting billet. The sampling positions should be kept relatively consistent to avoid areas with severe segregation and looseness.

[0049] In some examples, at least one of the two sample groups can be selected, specifically by taking two sample bases at 1 / 4R, 1 / 2R, and 3 / 4R from the center of the axial end surface of the continuous casting billet, respectively, to obtain a total of six sample bases. The sample bases can be segmented along the axial direction to form multiple sample segments, which serve as samples, and further form a sample group.

[0050] In some examples, at least one sample group can be taken from the two sample groups, specifically: the step of taking a sample group from the two sample groups specifically includes: taking out a round rod from the continuous casting billet, and the axial extension direction of the round rod is consistent with the axial extension direction of the continuous casting billet; dividing the round rod into multiple sections along the axial direction to form a sample group with multiple samples.

[0051] In some examples, the preferred sample substrate is a round rod with a diameter between 15 mm and 25 mm (inclusive) and a length between 140 mm and 160 mm (inclusive), with the axial extension of the round rod aligned with the axial extension of the continuous casting billet. A preferred sample substrate is a round rod with a diameter of approximately 20 mm and a length of approximately 150 mm. Later, the round rod can be segmented along its length to serve as separate samples, and the segmented round rod can then be formed into a sample group.

[0052] S200: treating some samples in the sample group according to a preset heating and cooling rate treatment process, and performing differential scanning calorimetry (DSC) analysis on the samples to obtain liquidus temperature and solidus temperature.

[0053] Differential scanning calorimetry (DSC) analysis is primarily performed using a thermal analyzer. Specifically, DSC analysis measures the rate at which a sample absorbs or releases heat, or heat flow rate dH / dt (in millijoules per second), as the vertical axis, against time t as the horizontal axis.

[0054] A specific preset heating and cooling rate processing process may be: heating the sample from room temperature to a first preset temperature at a first preset temperature change rate, heating the sample from the first preset temperature to a second preset temperature at a second preset temperature change rate, and the sampling period is a first preset duration; after keeping the sample warm for a second preset duration, cooling the sample temperature to the first preset temperature at a cooling rate of the second preset temperature change rate, and cooling the sample from the first preset temperature to room temperature at the first preset temperature change rate.

[0055] As attached Figure 3 As shown, the first preset temperature change rate is 10~30℃ / min (degrees Celsius per minute); the first preset temperature is 580℃ (degrees Celsius) to 620℃; the second preset temperature change rate is 1~10℃ / min; the second preset temperature is 1500℃ to 1540℃; the first preset time is 0.9 seconds to 1.1 seconds; the second preset time is 9min to 10min (seconds).

[0056] Specifically, the temperature was raised from room temperature to 600°C at a rate of 10-30°C / min, then from 600°C to 1520°C at a rate of 1-10°C / min, with argon protection throughout the process, and the sampling period was 1 second. After holding for 10 minutes, the temperature was lowered to 600°C at a cooling rate of 1-10°C / min, and then from 600°C to room temperature at a rate of 10-30°C / min.

[0057] As attached Figure 3 As shown in the figure, the specific liquidus temperature and solidus temperature can be obtained by calibrating the positions of the solidus temperature and the liquidus temperature by using the position of the intersection of the tangent lines of the curve on both sides of the inflection point of the endothermic peak during the solidification process. As shown in the figure, the solidus temperature is 1412.3°C and the liquidus temperature is 1499.6°C.

[0058] The obtained liquidus temperature and solidus temperature can be used to set parameters for subsequent numerical simulations, so that the simulation can be closer to the simulation parameters of the current sample.

[0059] It should be noted that, among them, some samples in the sample group are processed according to the preset heating and cooling rate processing process, and the specific number of samples can be set as needed.

[0060] S300: performing several groups of dynamic high-temperature tensile tests on some of the samples in the sample group to obtain stress and cross-sectional shrinkage rate curves at different tensile temperatures.

[0061] Specifically, the theoretical ZDT (zero plasticity temperature), LIT (viscosity temperature) and ZST (zero strength temperature) can be determined according to the steel type, the stretching temperature can be determined within the ZDT and ZST range, and several groups of dynamic high-temperature stretching tests can be carried out on the specimens to obtain the stress and cross-sectional shrinkage curves of the stretched specimens and at different stretching temperatures.

[0062] In the above steps, one method for determining ZDT, LIT, and ZST is as follows: ZDT, LIT, and ZST are determined based on the freezing rate (fs), where fs is determined by the following formula. The temperature at which fs is 1 is defined as ZDT, the temperature between 0.86 and 0.90 as LIT, and the temperature between 0.73 and 0.77 as ZST. Specifically, for example, the temperature at fs = 0.88 is defined as LIT, and the temperature at fs = 0.75 is defined as ZST. The specific method for determining ZDT, LIT, and ZST based on the freezing rate can be based on existing techniques.

[0063]

[0064] Where Ts is the solidus temperature and Tl is the liquidus temperature.

[0065] For example, in a practical application, the calculated ZDT is 1412℃, LIT is 1436℃, and ZST is 1458℃.

[0066] The dynamic high temperature tensile test of several groups of continuous casting billet samples needs to be determined according to the ZDT. For example, five groups of high temperature tensile tests can be conducted at 1200℃, 1250℃, 1300℃, 1350℃ and 1400℃ according to the ZDT temperature. The highest temperature of the experiment is generally close to the ZDT temperature, but not higher than the ZDT temperature, mainly considering the accuracy of the thermometer. Then, the corresponding experiments are carried out to obtain the following Figure 4 As shown, the stress and cross-sectional shrinkage curves of the sample after stretching and at different stretching temperatures are obtained.

[0067] S400: Based on the corresponding parameters of the current sample steel grade, simulate and calculate the simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated; adjust the corresponding parameters of the current sample steel grade until the simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated are calculated, and the difference between the simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated and the corresponding values of the stress and cross-sectional shrinkage curves at different stretching temperatures is within a first preset range.

[0068] The simulation calculation can be performed based on existing simulation formulas. The simulation formulas can be based on actual experiments, multiple sets of actual values of stress, cross-sectional reduction curves, and temperature when cracks occur, and corresponding parameters are used to build a mathematical model. Alternatively, the calculation can be performed using general mechanical analysis software, such as general mechanical analysis software that couples thermal analysis and structural mechanics analysis modules. General mechanical analysis software can be used to perform the corresponding calculation. Examples of general mechanical analysis software include ANSYS Mechanical software and ADINA software.

[0069] When dividing the simulation curve and taking values, it is necessary to ensure the accuracy of the values. The specific division method is that the grid where the model curve is divided is a hexahedral structure, the grid size is ≤1mm (millimeter), and the grid quality is above 0.5.

[0070] Specifically, the parameters of the current sample steel grade may include Poisson's ratio, Young's modulus, and thermal expansion coefficient. These parameters are generally determined by the ZDT of the current sample steel grade. These parameters can be calculated using material performance simulation software, such as JmatPro or Materials Studio.

[0071] When adjusting the corresponding parameters of the current sample steel grade, you can first adjust according to the first preset amplitude. If the requirements are not met, you can further divide it until the requirements are met. If you first adjust the first preset amplitude and the optimal value is between the first value and the second value, but both the first value and the second value are not satisfied, then you can continue to divide the first value and the second value into N parts according to the second preset amplitude to further determine the interval where the optimal value is located until the error meets the requirements. In this application, all adjustment methods can be adjusted with reference to this method.

[0072] The corresponding values of the stress and cross-sectional shrinkage curves at different stretching temperatures refer to the corresponding values of the stress and cross-sectional shrinkage curves at different stretching temperatures obtained in step 300 .

[0073] In the above embodiment, a method combining numerical simulation and experimental research on the generation of center cracks in continuous casting alloy steel slabs is provided. By performing DSC analysis and high-temperature tensile testing on the initiation of center cracks in continuous casting slabs, and using numerical simulation to simulate the stress, strain, and temperature gradient of center crack initiation in continuous casting slabs, countermeasures for reducing center crack defects in continuous casting slab production are proposed, providing a theoretical basis for the generation of center cracks in continuous casting slabs. Relying on actual continuous casting production conditions, combined with existing experimental methods for determining crack initiation and numerical simulation methods for predicting cracking limits, the data obtained is more realistic and accurate, and the theoretical analysis of the generation of center cracks in continuous casting slabs is more efficient. Compared with existing research methods, the method has wider applicability and more accurate results.

[0074] By obtaining more appropriate parameters for the current sample steel grade, a more realistic simulation can be achieved, which in turn can more accurately reflect the actual stress and end shrinkage values, allowing for better judgment and prediction of the occurrence of center cracks in alloy steel continuous casting billets. In summary, this method of combining numerical simulation and experiment to judge and predict the occurrence of center cracks in alloy steel continuous casting billets can effectively solve the problem of unreliable judgment and prediction of the occurrence of center cracks in alloy steel continuous casting billets.

[0075] In some embodiments, further, after step 300, the method further includes:

[0076] Step 500: Processing the stretched samples obtained from the dynamic high-temperature tensile tests on several groups of samples to obtain a treated cross-section, and determining the actual critical strain and critical stress based on the microcrack morphology on the treated cross-section.

[0077] Specifically, the cross section of the stretched sample may be processed by cutting, grinding, polishing and mounting the cross section of the stretched sample.

[0078] As attached Figure 5 As shown, the microcrack morphology on the treated cross-section is generally obtained through microscopic observation. Specifically, a metallographic microscope or a scanning electron microscope can be used as an observation device to observe the microcrack morphology on the treated cross-section. Specifically, how to observe the critical strain and critical stress through microcrack morphology can refer to the existing technology.

[0079] Furthermore, the following steps may be included: comparing the actual critical strain and critical stress with the critical strain and critical stress calculated by simulation; if they are incorrect, adjusting the relevant parameters of the simulation calculation, such as adjusting the corresponding parameters of the current sample steel grade as mentioned above.

[0080] Specifically, the following steps may be included: setting corresponding parameters of the current sample steel grade until the difference between the simulated values of the critical strain and critical stress calculated by simulation and the actual critical strain and critical stress is within a second preset range.

[0081] After setting the corresponding parameters of the current sample steel grade, when the difference between the simulated values of the critical strain and critical stress calculated and the actual critical strain and critical stress is not within the second preset range, it is necessary to adjust the corresponding parameters of the current sample steel grade. The specific adjustment method can refer to the above embodiment, which is generally coarse adjustment first and then fine adjustment.

[0082] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0083] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiment, characterized in that: The steps include: Sampling the continuously cast slab to obtain at least one set of test specimens; Treating some of the samples in the sample group according to a preset heating and cooling rate treatment process to perform differential scanning calorimetry analysis on the samples to obtain liquidus temperature and solidus temperature; Performing several groups of dynamic high-temperature tensile tests on some of the samples in the sample group to obtain stress and cross-sectional shrinkage curves at different tensile temperatures; Based on the corresponding parameters of the current sample steel grade, simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated are calculated; the corresponding parameters of the current sample steel grade are adjusted until the simulated values of stress, cross-sectional shrinkage curve and temperature when cracks are generated are calculated, and the difference between the simulated values and the corresponding values of the stress and cross-sectional shrinkage curves at different stretching temperatures is within a first preset range.

2. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiment according to claim 1, characterized in that: Also includes: The stretched samples obtained by performing the dynamic high-temperature tensile test on several groups of samples are processed to obtain a treated cross section, and the actual critical strain and critical stress are determined based on the microscopic crack morphology on the treated cross section.

3. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting billets by combining numerical simulation and experiment according to claim 2, characterized in that: Also includes: Corresponding parameters of the current sample steel grade are set until the difference between the simulated values of the critical strain and critical stress calculated by simulation and the actual critical strain and critical stress is within a second preset range.

4. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 2, characterized in that: The step of processing the stretched samples obtained by performing the dynamic high-temperature tensile test on the plurality of groups of samples to obtain the processed cross-sections comprises: For the stretched specimens obtained by dynamic high temperature tensile tests on several groups of specimens, cutting, grinding, polishing and mounting are carried out in sequence; The micro crack morphology is obtained through a metallographic microscope or a scanning electron microscope.

5. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 1, characterized in that: The corresponding parameters of the current sample steel grade include at least Poisson's ratio, Young's modulus, and thermal expansion coefficient.

6. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 5, characterized in that: The Poisson's ratio, Young's modulus and thermal expansion coefficient are determined by the ZDT of the current sample steel.

7. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 1, characterized in that: The continuous casting slab is sampled to obtain at least one sample group, which is: Two groups of samples are taken from each of the three positions 1 / 4R, 1 / 2R and 3 / 4R from the center of the axial end surface of the continuous casting billet, where R is the radius of the continuous casting billet.

8. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 7, characterized in that: The method of taking a sample group from the two sample groups comprises: Taking out a round rod from the continuous casting billet, wherein the axial extension direction of the round rod is consistent with the axial extension direction of the continuous casting billet; The round rod is divided into a plurality of sections along the axial direction to form a sample group having a plurality of samples.

9. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 1, characterized in that: Some samples in the sample group are processed according to a preset heating and cooling rate processing process, which is: The sample is heated from room temperature to a first preset temperature at a first preset temperature change rate, and the sample is heated from the first preset temperature to a second preset temperature at a second preset temperature change rate, and the sampling period is a first preset time length; After the sample is kept warm for a second preset time, the sample temperature is cooled to the first preset temperature at a cooling rate of the second preset temperature change rate, and the sample temperature is cooled from the first preset temperature to room temperature at the first preset temperature change rate.

10. The method for judging and predicting the occurrence of central cracks in alloy steel continuous casting slabs by combining numerical simulation and experiment according to claim 9, characterized in that: The first preset temperature change rate is 10~30℃ / min; the first preset temperature is 580℃ to 620℃; the second preset temperature change rate is 1~10℃ / min; the second preset temperature is 1500℃ to 1540℃; the first preset time is 0.9 seconds to 1.1 seconds; the second preset time is 9min to 10min.

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