CN111521461A - Prediction method for austenite grain growth behavior in continuous casting billet heating process - Google Patents
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- 238000010438 heat treatment Methods 0.000 title claims abstract description 116
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- 238000004321 preservation Methods 0.000 claims abstract description 28
- 229910000742 Microalloyed steel Inorganic materials 0.000 claims abstract description 15
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- 238000010791 quenching Methods 0.000 claims abstract description 4
- 230000000171 quenching effect Effects 0.000 claims abstract description 4
- 238000004088 simulation Methods 0.000 claims description 23
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Abstract
A prediction method of austenite grain growth behavior in a continuous casting billet heating process belongs to the field of continuous casting process prediction methods. The prediction method of the austenite grain growth behavior in the heating process of the continuous casting billet comprises the following steps: sampling the continuous casting billet, simulating the process of the continuous casting billet entering a heating furnace under the conditions of different heating temperatures and heat preservation time, and then quenching, polishing and corroding to obtain high-temperature austenite grains. Aiming at the characteristics that the section of the microalloy steel continuous casting billet is large and the casting billet has the temperature gradient in the heating process, the prediction model of the isothermal austenite grain growth and the non-isothermal austenite grain growth of the microalloy steel continuous casting billet is obtained by correcting the parameters of the classical austenite grain growth model, and the prediction of the austenite grain growth behavior of the microalloy steel continuous casting billet under the isothermal condition and the non-isothermal condition can be accurately realized through the model.
Description
Technical Field
The invention relates to the technical field of continuous casting process prediction methods, in particular to a prediction method of austenite grain growth behavior in a continuous casting billet heating process.
Background
The purpose of heating and heat preservation of the continuous casting billet sent into the heating furnace is to ensure the tissue uniformity of the continuous casting billet and improve the plasticity of the continuous casting billet, so that the defects of the casting billet are reduced, and the continuous casting billet enters the rolling stage to be smoothly carried out. In the current large-scale iron and steel enterprises, the continuous casting billet enters the heating furnace and is generally subjected to braking heating temperature control, the blocking control is carried out through a thermocouple in the furnace, and the temperature in the furnace is dynamically controlled, so that the temperature and the heat preservation time of the continuous casting billet heating furnace meet the requirements of a rolling process. However, in the actual production process, a lot of possibilities exist, for the microalloy steel wide and thick plate blank, because the casting blank has a large section, a temperature gradient exists from inside to outside in the heating process, the internal and external microstructures of the continuous casting blank are unstable in evolution, the internal and external microstructures of the continuous casting blank can not be measured on line in real time, and the change condition of austenite crystal grains in a high-temperature state along with the heating temperature and the heat preservation time can not be obtained by a method.
The large-section continuous casting billet belongs to non-isothermal heating process in heating process, and the too high or holding time overlength of heating temperature also can make continuous casting billet austenite grain thick, and the holding time overlength makes the phenomenon of overburning probably appear in casting billet top layer austenite grain boundary, causes the energy waste, influences the quality of continuous casting billet. In order to dynamically know the austenite grain change condition of the continuous casting billet in the heating and heat preservation processes, a method is needed for dynamically determining the dynamic change relationship of the continuous casting billet along with the heating temperature and the heat preservation time and accurately regulating and controlling the heating and heat preservation processes of the continuous casting billet. Therefore, a method for predicting austenite grain growth behavior in the continuous casting billet heating process is provided.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a prediction method of austenite grain growth behavior in a continuous casting billet heating process, which aims at the characteristics that the section of the continuous casting billet is large and the casting billet has a temperature gradient in the heating process, obtains a prediction model of isothermal austenite grain growth and a prediction model of non-isothermal austenite grain growth of the continuous casting billet by correcting the parameters of a classical austenite grain growth model, and can accurately predict the behavior of austenite grain growth in isothermal and non-isothermal heating and heat preservation processes of the continuous casting billet.
In order to achieve the purpose, the technical scheme of the invention is as follows:
the invention discloses a prediction method of austenite grain growth behavior in a continuous casting billet heating process, which comprises the following steps:
step 1:
taking a casting blank at the center of the narrow surface of the continuous casting billet, and processing the casting blank into a plurality of continuous casting billet test samples;
determining an austenite temperature area of the continuous casting billet according to the components of the continuous casting billet, taking one blank continuous casting billet test sample, heating to the initial value of the austenite temperature area by a simulated heating process at the initial value of the austenite temperature area, and preserving heat for 0s to obtain an initial high-temperature thermal simulated continuous casting billet;
then under different heating temperatures and heat preservation times, the heating process of the simulated continuous casting billets is carried out on the rest of the continuous casting billet test samples, and a series of high-temperature thermal simulation continuous casting billet samples with different heating temperatures and heat preservation times are obtained;
step 2:
taking out the initial high-temperature thermal simulation continuous casting slab and the series high-temperature thermal simulation continuous casting slab, quenching, grinding and polishing respectively, adding into a corrosive agent, and corroding at 75-85 ℃ for 25-35 min to obtain a series corroded continuous casting slab; the used corrosive agent is the corrosive agent which can enable the austenite grain boundary to be clearly displayed;
and step 3:
observing the continuously cast slab after the series of corrosion by a metallographic microscope to obtain initial austenite grains with the grain size D of the initial high-temperature thermal simulation continuously cast slab0And under different heating temperatures and heat preservation times, the grain size of austenite grains of the continuous casting slab is simulated by the series of high-temperature heat;
and 4, step 4:
the grain size of initial austenite grains of the initial high-temperature thermal simulation continuous casting billet is D0And the grain size of austenite grains of the series of high-temperature thermal simulation continuous casting billets is determined by the combination of the austenite grain size and the grain size of the austenite grainsHeating temperature and holding time are subjected to linear fitting to obtain crystal grain growth activation energy QggAnd a time index m. By introducing a classical austenite grain growth model, the activation energy Q is obtained by grain growthggAnd the error of the time index m, performing error square sum polynomial fitting on the value of n to accurately obtain the exponential power n of the austenite grain size, and fitting m, n and QggSubstituting the parameters into a formula (1) to calculate a constant C, and finally obtaining a prediction model of austenite grain growth under an isothermal condition, wherein the prediction model is shown as the formula (1):
wherein D is0: initial austenite grain size, μm; d: final austenite grain size, μm; t: holding time, s; r: gas constant, 8.314J/(mol K); t: heating temperature, K; qgg: grain growth activation energy, J/(mol), n is an exponential constant, m is a time exponential constant, and C is a constant;
and 5:
on the basis of the prediction model of the austenite grain length under the isothermal condition, the prediction model of the austenite grain length under the non-isothermal condition is established by taking delta t as isothermal heating, and is shown in a formula (2):
wherein D isi+1Austenite grain size at the (i +1) th s point, D0The austenite grain size, μm,
the holding time (i +1) s, Δ t is t ═ ti+1-tiIs the time interval, s, in this formula, the Δ t time is isothermal heating, R: gas constant, 8.314J/(mol K); t: heating temperature, K, Qgg: grain growth activation energy, J/(mol); c is a constant, n is an exponential constant, and m is a time exponential constant.
In the step 1, the continuous casting blank is particularly suitable for a microalloyed steel continuous casting blank under heavy pressure, and the microalloyed steel continuous casting blank contains the following main chemical components in percentage by mass: 0.15% of C, 0.28% of Si, 1.58% of Mn, 0.025% of Cr, 0.0379% of Nb, 0.0397% of V, 0.015% of Ti, and the balance of Fe and inevitable impurities.
The heating process comprises the following steps:
taking one blank continuous casting billet test sample, heating to an initial value 1173K of an austenite temperature region at 10K/min, and keeping the temperature for 0s to obtain an initial high-temperature thermal simulation continuous casting billet;
heating a plurality of continuous casting billet test samples to an initial value 1173K of an austenite temperature region at 10K/min, starting from the initial value of the austenite temperature region, heating to the austenite temperature region at 0-4.5K/min, and preserving heat; wherein the austenite temperature region is 1173-1473K, the heat preservation time is 300-10800 s, and a series of high-temperature thermal simulation continuous casting blank samples with different heating temperatures and heat preservation times are obtained;
in the step 1, the value interval of the heating temperature is 100K, the value interval of the heat preservation time is preferably an unequally spaced value, and the preferable value mode is as follows: 300s, 1800s, 3600s, 7200s and 10800 s.
In the step 2, the corrosive agent comprises picric acid, HCl, a corrosion inhibitor and water, and the corrosion inhibitor comprises the following components in a solid-to-liquid ratio: picric acid: HCl: corrosion inhibitor: water (4-8) g: 5mL of: (0.5-1) mg: 100 mL; among them, the corrosion inhibitor is preferably at least one of alkyl sulfonate or alkylbenzene sulfonate, and more preferably sodium dodecylbenzene sulfonate.
In the step 2, the continuously cast slab after series corrosion obtains austenite crystal boundaries enriched by carbonitrides.
In the step 3, the grain size of the austenite grains is obtained by statistics according to a line cutting method, and under different heating temperatures and heat preservation time, the grain size of the austenite grains of the continuously-corroded continuous casting billet is obtained in a series mode.
The line cutting method comprises the following steps: and (3) introducing the metallographic picture into an Image-pro plus, selecting a measuring tool, changing the scale into a scale in the metallographic picture, selecting grains on a path in the measuring process, measuring for multiple times, measuring the metallographic structure under the same condition for multiple times, and taking the average value of the sizes of the austenite grains.
In the step 4, the classical austenite grain growth model is a selars model and an Anelli model, and the selars model and the Anelli model are used for describing the growth behavior of austenite grains, wherein the selars model considers the initial austenite grains but does not introduce a time index, the Anelli model introduces a time index but does not consider the initial austenite grains, both models are provided by a large amount of experimental data, the time index m is introduced to obtain an austenite grain growth model comprehensively describing the heating temperature and the holding time, the selars model is as shown in formula (a), the Anelli model is as shown in formula (b), and the comprehensive calculation model of the heating temperature and the holding time is a prediction model of the austenite grain growth under the condition, as shown in formula (1):
in the formula D0: initial austenite grain size, μm; d: final austenite grain size, μm; t: holding time, s; r: gas constant, 8.314J/(mol K); t: heating temperature, K; qgg: grain growth activation energy, J/(mol); A. b, C are all constants, n is an exponential constant, and m is a time exponential constant.
According to the formula (1), by pairing ln (D)n-D0 n) And ln (t), ln (D)n-D0 n) Fitting with 1/T to obtain grain growth activation energy QggTime index m, activation energy Q by grain growthggThe time index m error is used for taking the value of n, the square sum polynomial fitting of the error is carried out to obtain the exponential power n of the austenite grain size, and the grain growth activation energy Q is obtainedggWhen in useSubstituting the m index and the n index into a formula (1) to obtain a material constant C, and finally obtaining an austenite grain growth prediction model under the isothermal condition.
In the step 5, the establishment process of the prediction model of austenite grain growth under the non-isothermal condition comprises the following steps:
setting a heat history formula according to the actual heating process of the continuous casting billet, wherein the formula is as follows:
T＝f(tr) (c)
in the formula, tr: heating time, s; t: heating temperature, K;
recognizing the formula of the thermal history, isothermal heating is performed within the time of delta t, wherein, the time of delta t is ti+1-tiFor a time interval according to tiGrain size D at timeiAnd temperature TiD under isothermal conditions is deduced from the formula (1)iTo D0Time t of heat preservationiAs in formula (d):
according to tiT is establishedi+1And (3) a model for predicting the austenite grain growth under the non-isothermal condition at the moment, as shown in the formula (2).
The invention provides a prediction method of austenite grain growth behavior in a continuous casting billet heating process, which has the following beneficial effects:
the invention considers the growth condition of austenite grains under isothermal and non-isothermal conditions, corrects the conventional model modeling process, and theoretically establishes the austenite grain growth model with high precision of the microalloy steel continuous casting billet.
And because the surface and the core of the casting blank are heated unevenly after the casting blank enters the heating furnace, the size of the initial austenite grain size can be influenced. Therefore, the establishment of the austenite grain growth model under the non-isothermal condition plays an important role in the grain size prediction of the continuous casting billet entering different positions of the heating furnace.
Drawings
FIG. 1 is a graph of the thermal history of a sample;
FIG. 2 shows metallographic structures at different heating temperatures: (a) 1173K; (b) 1273K; (c) 1373K; (d) 1473K;
FIG. 3 is a drawing showing
A relationship to 1/T;
FIG. 4 is a drawing showing
The relationship to ln (t);
FIG. 5 is a graph of the sum of squared errors as a function of n;
FIG. 6 is a comparison of an experimental value with a predicted value predicted by the method for predicting austenite grain growth behavior in a continuous casting slab heating process of the present invention.
Detailed Description
The following detailed description is provided to enable technical problems, technical solutions and advantages to be solved by the present invention more clearly.
In this example, the metallographic microscope was a ZEISS Axio Imager A2m optical metallographic microscope.
Example 1
In this embodiment, the continuous casting billet of selecting for use is the microalloy steel continuous casting billet under the heavy load, and among the microalloy steel continuous casting billet, the main chemical composition that contains and mass fraction are: 0.15% of C, 0.28% of Si, 1.58% of Mn, 0.025% of Cr, 0.0379% of Nb, 0.0397% of V, 0.015% of Ti, and the balance of Fe and inevitable impurities.
A prediction method for austenite grain growth behavior in a continuous casting billet heating process comprises the following steps:
step 1: heating and heat preservation
Taking a casting blank at the central position of the narrow surface of the continuous casting blank, and processing the casting blank into a plurality of square continuous casting blank test samples of 10mm multiplied by 10 mm; through the process that the micro alloy steel continuous casting billet enters the heating furnace by the muffle furnace simulation, the method specifically comprises the following steps:
taking a blank continuous casting billet test sample, heating to an initial value 1173K of an austenite temperature region at a heating rate of 10K/min, and keeping the temperature for 0s to obtain an initial high-temperature thermal simulation continuous casting billet;
heating the rest continuous casting billet test sample to 1173K at the heating rate of 10K/min, and then heating to the heating temperature from 1173K at the heating rate of 4.5K/min, wherein the thermal history chart is shown in figure 1; selecting 1173K, 1273K, 1373K and 1473K and four heating temperatures in the range of an austenite temperature region (1173K-1373K) and keeping the temperature for 300s, 1800s, 3600s, 7200s and 10800s, and adjusting the heating temperatures and the keeping time to obtain a series of high-temperature simulated continuous casting billets with different heating temperatures and keeping time; the numbers of the heating temperature T and the holding time T are shown in Table 1.
TABLE 1 series correspondence table for heating temperature and holding time of high-temperature thermal simulation continuous casting billet
Step 2: etching of
Taking out the series of high-temperature thermal simulation continuous casting slabs related to the table 1, quenching, grinding and polishing respectively, adding into a corrosive agent, and corroding at 80 ℃ for 30min to obtain series corroded continuous casting slabs; the corrosive agent comprises picric acid, HCl, sodium dodecyl benzene sulfonate and water, and the solid-liquid ratio is as follows: picric acid: HCl: sodium dodecylbenzenesulfonate: water 5 g: 5mL of: 0.5 mg: 100 mL;
scanning the continuously cast bloom after the series of corrosion, and observing austenite grains of the continuously cast bloom, wherein the austenite grains are shown in figure 2;
and step 3: grain size statistics of austenite grains
Observing the continuously cast bloom after the series corrosion by a metallographic microscope, and counting according to a line cutting method to obtain the grain size of austenite grains of the continuously cast bloom after the series corrosion at different heating temperatures and different heat preservation times; wherein the grain size of continuous casting blank austenite grains obtained by initial high-temperature thermal simulation of the continuous casting blank is D0；
The line cutting method is characterized in that a metallographic picture is led into an Image-pro plus, a measuring tool is selected, a scale is changed into a scale in the metallographic picture, crystal grains on a path are selected in the measuring process, the measurement is carried out for multiple times, the metallographic structure under the same condition is measured for multiple times, and the average value of the austenitic crystal grains is obtained.
And 4, step 4: establishment of prediction model for austenite grain growth under isothermal condition
Substituting the grain size of the austenite grains of the continuously cast slab after series corrosion into a classical austenite grain growth model, a Serlars model and an Anelli model under different heating temperatures and holding times, and describing the growth behavior of the austenite grains by adopting the Serlars model and the Anelli model, wherein the Serlars model considers the initial austenite grains but does not introduce a time index, the Anelli model introduces the time index but does not consider the initial austenite grains, the two models are provided by a large amount of experimental data, the time index m is introduced to obtain an austenite grain growth model comprehensively describing the heating temperature and the holding time, the Serlars model is shown as a formula (a), the Anelli model is shown as a formula (b), and the heating temperature and holding time comprehensive calculation model is shown as a formula (1), which is an austenite grain growth prediction model under the isothermal condition:
in the formula D0: initial austenite grain size, μm; d: final austenite grain size, μm; t: holding time, s; r: gas constant, 8.314J/(mol K); t: heating temperature, K; qgg: grain growth activation energy, J/(mol); A. b, C are all constants, n is an exponential constant, and m is a time exponential constant.
According to the formula (1) Through a pair of
With ln (t),
Fitting with 1/T, as shown in FIGS. 3 and 4, and performing linear fitting to obtain the grain growth activation energy QggThe time index m, the error is taken to n, and the square of the error and polynomial fitting are carried out;
the fitting yields the exponential power n of the austenite grain size, as shown in FIG. 5, and then is substituted into equation (1) to yield the constant C. A prediction model of austenite grain growth under isothermal conditions after each constant is determined; the model formula is as follows:
and 5: establishment of prediction model of austenite grain growth under non-isothermal condition
The simulation microalloy steel continuous casting billet heat history is shown in figure 1, and a heat history formula is set according to the actual heating process of the continuous casting billet, wherein the heat history formula is as shown in formula (c):
T＝f(tr) (c)
in the formula, tr: heating time, s; t: heating temperature, K;
Δt＝ti+1-tifor a time interval, consider isothermal heating for a time Δ t, according to tiGrain size D at timeiAnd temperature TiD under isothermal conditions is deduced from the formula (c) and the formula (1)iTo D0Time t of heat preservationiAs in formula (d):
according to tiT is establishedi+1A model for predicting austenite grain growth under non-isothermal condition at a moment, as shown in formula (2)
Step 6: prediction
The obtained prediction model of the austenite grain growth under the isothermal condition and the prediction model of the austenite grain growth under the non-isothermal condition are adopted to predict the austenite grain growth behavior in the continuous casting billet heating process:
taking a microalloy steel continuous casting billet to be predicted, adopting the sampling method in the step 1 and the processing method in the step 2, wherein the heating temperature in the step 1 is 1173K, the heat preservation time is 0s, and measuring by adopting the method in the step 3 to obtain the size D of the initial austenite grains of the microalloy steel continuous casting billet to be predicted0；
And (3) carrying the austenite grain growth prediction model formula (1) under the isothermal condition, and calculating to obtain D.
The austenite grain growth prediction model formula (2) under the non-isothermal condition is substituted, and D is obtained by calculationi+1。
According to the obtained D and Di+1Therefore, the austenite grain growth behavior in the heating process of the continuous casting billet is predicted, and the production is guided.
And 7: authentication
Comparing the model calculation results with the experimental measurement values, as shown in fig. 6; by means of FIG. 6, it is shown that the prediction model of the present invention is close to the real data with an error of 0.97129, and can accurately guide production.
Claims (10)
1. A prediction method for austenite grain growth behavior in a continuous casting billet heating process is characterized by comprising the following steps:
step 1:
taking a casting blank at the center of the narrow surface of the continuous casting billet, and processing the casting blank into a plurality of continuous casting billet test samples;
determining an austenite temperature area of the continuous casting billet according to the components of the continuous casting billet, taking one blank continuous casting billet test sample, heating to the initial value of the austenite temperature area by a simulated heating process at the initial value of the austenite temperature area, and preserving heat for 0s to obtain an initial high-temperature thermal simulation continuous casting billet;
then under different heating temperatures and heat preservation times, the heating process of the simulated continuous casting billets is carried out on the rest of the continuous casting billet test samples, and a series of high-temperature thermal simulation continuous casting billet samples with different heating temperatures and heat preservation times are obtained;
step 2:
taking out the initial high-temperature thermal simulation continuous casting slab and the series high-temperature thermal simulation continuous casting slab, quenching, grinding and polishing respectively, adding into a corrosive agent, and corroding at 75-85 ℃ for 25-35 min to obtain a series corroded continuous casting slab; the used corrosive agent is the corrosive agent which can enable the austenite grain boundary to be clearly displayed;
and step 3:
observing the continuously cast slab after the series of corrosion by a metallographic microscope to obtain initial austenite grains with the grain size D of the initial high-temperature thermal simulation continuously cast slab0And under different heating temperatures and heat preservation times, the grain size of austenite grains of the continuous casting slab is simulated by the series of high-temperature heat;
and 4, step 4:
the grain size of initial austenite grains of the initial high-temperature thermal simulation continuous casting billet is D0And the grain size of austenite grains of the series of high-temperature thermal simulation continuous casting billets is subjected to linear fitting through the austenite grain size, the heating temperature and the heat preservation time to obtain grain growth activation energy QggTime index m, into a classical austenite grain growth model, activating energy Q by grain growthggAnd the error of the time index m, performing error square sum polynomial fitting on the value of n to accurately obtain the exponential power n of the austenite grain size, and fitting m, n and QggSubstituting the parameters into a formula (1) to calculate a constant C, and finally obtaining an austenite grain growth prediction model under the isothermal condition, wherein the model is the formula (1):
wherein D is0: initial austenite grain size, μm; d: final austenite grain size, μm; t: holding time, s; r: gas constant, 8.314J/(mol K);t: heating temperature, K; qgg: grain growth activation energy, J/(mol), n is an exponential constant, m is a time exponential constant, and C is a constant;
and 5:
on the basis of the prediction model of the austenite grain length under the isothermal condition, the prediction model of the austenite grain length under the non-isothermal condition is established by taking delta t as isothermal heating, and is shown in a formula (2):
wherein D isi+1Austenite grain size at the (i +1) th s point, D0The austenite grain size, μm,
the holding time (i +1) s, Δ t is t ═ ti+1-tiIs the time interval, s, in this formula, the Δ t time is isothermal heating, R: gas constant, 8.314J/(mol K); t: heating temperature, K, Qgg: grain growth activation energy, J/(mol); c is a constant, n is an exponential constant, and m is a time exponential constant.
2. The method for predicting austenite grain growth behavior in the slab heating process according to claim 1, wherein in the step 1, the slab is a heavy-weight microalloyed steel slab, and the microalloyed steel slab comprises the following main chemical components in percentage by mass: 0.15% of C, 0.28% of Si, 1.58% of Mn, 0.025% of Cr, 0.0379% of Nb, 0.0397% of V, 0.015% of Ti, and the balance of Fe and inevitable impurities.
3. The method for predicting austenite grain growth behavior in a continuous casting billet heating process according to claim 1, wherein the continuous casting billet test sample heating process is as follows:
taking one blank continuous casting billet test sample, heating to an initial value 1173K of an austenite temperature region at 10K/min, and preserving heat for 0s to obtain an initial high-temperature thermal simulation continuous casting billet;
heating a plurality of continuous casting billet test samples to an initial value 1173K of an austenite temperature region at 10K/min, starting from the initial value of the austenite temperature region, heating to the austenite temperature region at 0-4.5K/min, and preserving heat; wherein the austenite temperature area is 1173-1473K, the heat preservation time is 300-10800 s, and a series of high-temperature thermal simulation continuous casting slab samples with different heating temperatures and heat preservation times are obtained.
4. The method for predicting austenite grain growth behavior in the continuous casting billet heating process according to claim 1, wherein in the step 1, the value interval of the heating temperature is 100K, the value interval of the heat preservation time is an unequally-spaced value, and the value mode is as follows: 300s, 1800s, 3600s, 7200s and 10800 s.
5. The method for predicting austenite grain growth behavior in slab heating according to claim 1, wherein in the step 2, the corrosive agent comprises picric acid, HCl, a corrosion inhibitor and water, and the ratio of solid to liquid: picric acid: HCl: corrosion inhibitor: water (4-8) g: 5mL of: (0.5-1) mg: 100 mL.
6. The method of claim 1, wherein the corrosion inhibitor is at least one of alkyl sulfonate or alkyl benzene sulfonate.
7. The method for predicting austenite grain growth behavior in slab heating according to claim 1, wherein in step 2, the slab after the series of etching is subjected to carbonitride-enriched austenite grain boundaries.
8. The method for predicting austenite grain growth behavior in the heating process of continuous casting slab as claimed in claim 1, wherein in step 3, the grain size of austenite grains is obtained by statistics according to a line cutting method, and the austenite grain size of continuous casting slab after series corrosion is obtained under different heating temperatures and holding times.
9. The method for predicting austenite grain growth behavior in a slab heating process according to claim 1, wherein in step 4, the classical austenite grain growth models are selars model and Anelli model, the selars model and the Anelli model are used for describing the growth behavior of austenite grains, the time index m is introduced to obtain the austenite grain growth model comprehensively describing the heating temperature and the holding time, the selars model is as formula (a), the Anelli model is as formula (b), and the heating temperature and holding time comprehensive calculation model is the austenite grain growth prediction model under the isothermal condition, as formula (1):
in the formula D0: initial austenite grain size, μm; d: final austenite grain size, μm; t: holding time, s; r: gas constant, 8.314J/(mol K); t: heating temperature, K; qgg: grain growth activation energy, J/(mol); A. b, C are all constants, n is an exponential constant, m is a time constant;
according to the formula (1), by pairing ln (D)n-D0 n) And ln (t), ln (D)n-D0 n) Fitting with 1/T to obtain the grain growth activation energy QggTime index m, activation energy Q by grain growthggObtaining the value of n by the error of the time index m, carrying out error square sum polynomial fitting to obtain the exponential power n of the austenite grain size, and activating the grain growth energy QggThe time index m,Substituting the exponential power n into the formula (1) to obtain a material constant C, and finally obtaining an austenite grain length prediction model under the isothermal condition.
10. The method for predicting austenite grain growth behavior in the slab heating process according to claim 1, wherein in the step 5, the establishment of the austenite grain growth prediction model under the non-isothermal condition comprises:
setting a heat history formula according to the actual heating process of the continuous casting billet, wherein the formula is as follows:
T＝f(tr) (c)
in the formula, tr: heating time, s; t: heating temperature, K;
recognizing the formula of the thermal history, isothermal heating is performed within the time of delta t, wherein, the time of delta t is ti+1-tiFor a time interval according to tiGrain size D at timeiAnd temperature TiD under isothermal conditions is deduced from the formula (1)iTo D0Time t of heat preservationiAs in formula (d):
according to tiT is establishedi+1And (3) a model for predicting the austenite grain growth under the non-isothermal condition at the moment, as shown in the formula (2).
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