A method for predicting element segregation of a casting blank based on composite simulation correction

Abstract

The application relates to a slab element segregation prediction method based on composite simulation correction. For a specific steel grade with specific composition and cross-sectional size, the temperature change curve of the slab surface, the temperature change curve of the core of the slab at the place and the solid phase rate change curve of the slab from the surface to the core at the place are obtained by adopting a numerical simulation software to perform multi-physical field coupling numerical simulation on the casting process under a specific process system; a 'temperature-solidification model' is obtained by fitting the change curves; the temperature of the slab surface is collected in the casting production field and drawn into a slab surface temperature change curve, which is compared with the simulated temperature change curve, the 'temperature-solidification model' is corrected, and physical simulation is performed. The method has the advantages that physical simulation and numerical simulation are combined, the accuracy of boundary condition setting of element segregation simulation prediction is improved, the prediction result has higher precision, and the prediction cost is reduced.

Description

Technical Field

[0001] This invention belongs to the field of elemental segregation analysis of cast billets, and particularly relates to a method for predicting elemental segregation in cast billets based on composite simulation correction. Background Technology

[0002] Solute element segregation in cast billets is a common and unavoidable defect. Severe segregation can lead to significant differences in the properties of different sections of the steel. Generally, the casting process has a very significant impact on element segregation in cast billets. Through process adjustments, element segregation in cast billets can be controlled within a reasonable range. However, using experimental methods for process screening is costly and inefficient. Therefore, numerical simulation methods are often used to predict solute element segregation in cast billets. Currently, there are some studies on the simulation prediction of solute element segregation. However, most of these studies have the following problems: 1) In the boundary condition settings for segregation prediction simulation, there is a certain error between the variation law of billet temperature or solid fraction and the actual billet, resulting in low accuracy of the prediction results; 2) The diffusion of elements during solidification is mainly affected by the temperature field, solute field and phase field, which is a physical process controlled by three fields. However, the models used in previous studies mostly involve the temperature field and solute field, and failed to couple the phase field into the simulation calculation; 3) Even if the phase field is coupled into the calculation model, due to the single simulation method, these studies can only reflect the growth characteristics of micro-dendritic areas and cannot obtain the results of macro-segregation; 4) Current element segregation simulation predictions mostly focus on qualitative or semi-quantitative analysis and cannot accurately give the specific value of the degree of segregation of a certain element at any position of the billet. Summary of the Invention

[0003] The purpose of this invention is to provide a method for predicting element segregation in cast billets based on composite simulation correction, which breaks through the limitations of previous methods for predicting segregation in cast billets that are singular and have low accuracy, thereby improving the accuracy of predicting solute element segregation in cast billets.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for predicting elemental segregation in cast billets based on composite simulation correction includes the following steps:

[0006] 1) For steel grades with specific composition and cross-sectional dimensions, the casting process under specific process regime is simulated using numerical simulation software to perform multi-physics field coupled numerical simulation, and the temperature change curve of a certain part of the billet surface, the temperature change curve of the billet core at that part, and the solid fraction change curve of the billet from the surface to the core at that part are obtained.

[0007] 2) Fit the temperature change curve of the core of the billet obtained in step 1) to mathematical model one, and fit the solid fraction change curve from the surface of the billet to the core at the same location of the billet to mathematical model two. Mathematical model one and mathematical model two are called "temperature-solidification model".

[0008] 3) The casting production site is selected under the same process conditions as in step 1), and the composition and size of the billet are the same as those in step 1). During the casting process, the temperature change of the billet surface at the same location as in step 1) is collected and plotted as a billet surface temperature change curve. This curve is compared with the temperature change curve of the billet surface at that location obtained through numerical simulation in step 1), thereby correcting the numerical simulation model in step 1) until the temperature change curve of the billet surface at that location obtained through the corrected casting process numerical simulation is completely consistent with the collected temperature change curve of the billet surface at that location. Finally, the casting process in step 1) is numerically simulated again, and the "temperature-solidification model" is obtained again through step 2).

[0009] 4) Input the “temperature-solidification model” from step 3) into the physical simulation experimental device as the control program to perform physical simulation; obtain the solidification unit of the sample from the surface of the billet to the core under the specific casting conditions, and perform experimental characterization of solute element segregation on the solidification unit.

[0010] 5) Cut the billet in step 3) along the cross section, perform physicochemical tests on the solute element segregation of the cross section, and compare it with the solute element segregation results of the solidification unit in step 4); then make a correction to the "temperature-solidification model" in step 3) until the solute element segregation characterization results of the solidification unit and the actual billet under the mold casting conditions are completely consistent.

[0011] 6) Select several other sets of casting conditions and repeat steps 1) to 5). Make a second correction to the "temperature-solidification model" in step 5) to ensure that under any casting conditions, the "temperature-solidification model" obtained by step 1) can represent the relevant temperature and solidification physical changes in the actual casting process.

[0012] 7) Using the "temperature-solidification model" after secondary correction in step 6) as boundary conditions, within a reasonable casting process regime, adopt a mathematical model based on the coupling of temperature field, phase field and solute field, input these mathematical models into the numerical simulation software in the form of differential equations, and perform numerical simulation of solute element segregation from the surface of the billet to the core at the same location as in step 1) under the casting conditions, obtain the numerical simulation prediction results of solute element segregation, and select the process regime that makes the simulation results have the lowest degree of solute element segregation as the optimal casting process for the steel grade in step 1).

[0013] Compared with the prior art, the beneficial effects of the present invention are:

[0014] 1) This invention combines physical simulation and numerical simulation, which improves the accuracy of setting boundary conditions for element segregation simulation prediction and ensures that the prediction results have higher precision.

[0015] 2) Integrating the phase field into the computational model improves the reliability of the prediction;

[0016] 3) By obtaining the temperature and solid fraction distribution at a certain location on the billet, the specific value of the segregation degree of a certain element at that location can be obtained, thus making the prediction method more flexible;

[0017] 4) By collecting data on elemental segregation at different locations, the macroscopic trend of elemental segregation in the billet can be given. Based on the obtained overall elemental segregation results of the billet, the casting process can be optimized through numerical simulation prediction.

[0018] The method of this invention improves the accuracy and efficiency of predicting solute element segregation in cast billets, reduces prediction costs, and avoids the limitations of previous cast billet segregation prediction methods, which were limited by their simplistic approach and low accuracy. Attached Figure Description

[0019] Figure 1 This is a flowchart of the present invention.

[0020] Figure 2 This is a schematic diagram of the experimental apparatus used for physical simulation.

[0021] Figure 2 In the middle: 1-base, 2-heating furnace, 3-crucible, 4-water-cooled copper rod, 5-displacement servo mechanism.

[0022] Figure 3 This is a schematic diagram showing the location of the segregation points for solidification characteristic unit elements.

[0023] Figure 4 It is a coupled simulation model for predicting solute element segregation in cast billets based on solute field, phase field, and temperature field.

[0024] Figure 5 It consists of the elemental segregation characterization results of the actual cast billet and characteristic units under the optimal process, as well as the simulation prediction results of C element segregation. Detailed Implementation

[0025] The present invention will now be described in detail with reference to the accompanying drawings, but it should be noted that the implementation of the present invention is not limited to the following embodiments.

[0026] Example

[0027] A high-precision prediction method for elemental segregation in cast billets includes the following steps:

[0028] 1) See Figure 1 Taking a continuously cast slab of 45# steel (main solute element C) produced on-site as an example, the slab width is 200mm. Based on symmetry, the unit length for multi-dimensional simulation is determined to be 100mm. The applicable overheating range for this slab continuous casting production is 20~50℃, the casting speed range is 1.0~2.0m / min, and the crystallizer cooling regime is divided into medium cooling and strong cooling, while the secondary cooling zone cooling regime is divided into weak cooling, medium cooling, and strong cooling. Experimental measurements show that the liquidus temperature of this steel is 1492℃.

[0029] 2) Using a superheat of 20℃, a casting speed of 1.2 m / min, a medium-cooling crystallizer, and a strong-cooling secondary cooling zone as the selected continuous casting conditions, physical field numerical simulations of the continuous casting process were performed. This yielded temperature change curves at a certain point on the billet surface, the billet core at that point, and the solid fraction change curve from the surface to the core of the billet at that point. The obtained temperature change curve of the billet core at that point was fitted as follows:

[0030]

[0031] In equation (1), T is temperature (K), t is time (s), and A, B, P, m, n, h1, and h2 are fitting coefficients. The obtained solid fraction change curve of the slab from the surface to the core is fitted into the following formula:

[0032] V = a + bt + ct 2 +dt 3 +ed 4 (2)

[0033] In equation (2), V is the interface movement distance (mm), t is the time (s), and a, b, c, d and e are fitting coefficients; equations (1) and (2) are called the “temperature-condensation model”.

[0034] 3) At the continuous casting production site, the steel grade was continuously cast using the process described in 2). The temperature change curve of the billet surface at position 1) during the continuous casting process was then collected and compared with the numerical simulation results of the curve in 2). The numerical simulation process in 2) was then corrected until the temperature change of the billet surface at that location obtained after numerical simulation of the ingot casting process completely corresponded to the collected results at the same location. Finally, the "temperature-solidification model" was fitted again, and the fitting parameters are shown in Table 1 and ① of Table 2.

[0035] Table 1. Optimization of Fitting Parameters for Temperature Curves

[0036]

[0037] Table 2. Optimization of fitting parameters for solidification curves

[0038]

[0039] In Tables 1 and 2, L is a coefficient, L = (0.72T) m *v) / C 2 T m V represents the casting temperature in Kelvin (K); v represents the casting speed in m / min; and C represents the average cooling intensity of the secondary cooling system in W / (m*K).

[0040] 4) Using the "temperature-solidification model" from 3) as the control program input into the physical simulation device, a physical simulation of the continuous casting process in 2) is performed. The physical simulation device is as follows: Figure 2 As shown. The device has a heating system, a water cooling system, and a displacement servo mechanism 5; the cooling curve controls the temperature change of the heating furnace 2, the displacement servo mechanism 5 controls the displacement of the sample (the sample is inside the crucible 3), and the water cooling system is used to simulate the heat transfer from the sample and crucible 3 to the outside of the heating zone during the simulation process, simulating the movement of the solid / liquid interface during casting, and controlling the solidification process. Characteristic units that reflect the solidification structure from the surface of the billet to the core at the same location in 3) are obtained, and then these characteristic units are analyzed according to... Figure 3 The points shown were used to characterize solute element segregation. Then, the slab in step 2) was characterized for element segregation in the same way. The two characterization results were compared, and then the "temperature-solidification model" in step 3) was modified until the two element segregation characterization results corresponded completely. The modified fitting parameters are shown in Table 1 and ② in Table 2.

[0041] 5) Select two additional sets of continuous casting conditions. The first set uses a superheat of 40℃, a casting speed of 1.4m / min, a strong cooling in the crystallizer, and a weak cooling in the secondary cooling zone. The second set uses a superheat of 50℃, a casting speed of 1.8m / min, a medium cooling in the crystallizer, and a medium cooling in the secondary cooling zone. Then, repeat steps 2) to 4) to perform a secondary correction on the "temperature-solidification model" to make it universally applicable for high-precision prediction of solute element segregation in the billet under any continuous casting conditions. The fitting parameters after the secondary correction are shown in Table 1 and ③ of Table 2.

[0042] 6) Using the "temperature-solidification model" in 5) as boundary conditions, a mathematical model for predicting solute element segregation in the billet based on the temperature field, solute field, and phase field is established using COMSOL Multiphysics numerical simulation software. This model is as follows: Figure 4 As shown. The mathematical model for the temperature field is:

[0043]

[0044] In equation (3), T is temperature (in K); t is time (in s); ρ is the dendritic phase angle, L is the latent heat of solidification (J / g); Cp is the specific heat capacity at constant pressure (J / kg*K); D T This refers to the diffusion coefficient (m) 2 / s).

[0045] The solute field equation is:

[0046]

[0047] In equation (4), C is the concentration of the solute element (µmol / L); D is the diffusion coefficient D0. T The relevant coefficient, k, is related to the solute equilibrium partition coefficient (k eq ), solid-liquid interface migration rate (v, unit: mm / s), and equilibrium solidification rate (v eq (Unit: mm / s) Related to:

[0048] The phase field equation is:

[0049]

[0050] In equation (5), σ is the anisotropy intensity, and m is the slope of the phase-corrected liquidus line (unit: τ). c It is the partial derivative of time with respect to the square of length, ε c It is a constant related to the thickness of the solid-liquid interface, and θ is the phase angle. These four parameters can be expressed as:

[0051]

[0052] In equation (6), α and γ are constants, and T m Where m is the liquidus temperature. L The slope of the liquidus line is given by ε, which is a constant related to the thickness of the solidification section. l denoted as , where is the equilibrium concentration of the solute element in the liquid phase, c0 is the actual concentration of the solute element, and j is a constant related to the crystal lattice type.

[0053] Then, within the continuous casting process range of step 1), the carbon element segregation of the 45# steel continuous casting billet was predicted. After screening, the billet produced under the continuous casting conditions of 30℃ superheat, 1.0m / min casting speed, strong cooling in the crystallizer, and strong cooling in the secondary cooling zone exhibited the lowest element segregation. Under these conditions, the measured values, characteristic unit values, and numerical simulation prediction values ​​of element segregation at 5mm intervals from the center to the surface of the billet are as follows: Figure 5 As shown, these three have a high degree of consistency, which is sufficient to prove that the model has very high accuracy in predicting solute element segregation in cast billets.

Claims

1. A method for predicting elemental segregation in cast billets based on composite simulation correction, characterized in that, Includes the following steps: 1) For steel grades with specific composition and cross-sectional dimensions, the casting process under specific process regime is simulated using numerical simulation software to perform multi-physics field coupled numerical simulation, and the temperature change curve of a certain part of the billet surface, the temperature change curve of the billet core at that part, and the solid fraction change curve of the billet from the surface to the core at that part are obtained. 2) Fit the temperature change curve of the core of the billet obtained in step 1) to mathematical model one, and fit the solid fraction change curve from the surface of the billet to the core at the same location of the billet to mathematical model two. Mathematical model one and mathematical model two are called "temperature-solidification model". 3) The casting production site is selected under the same process conditions as in step 1), and the composition and size of the billet are the same as those in step 1). During the casting process, the temperature change of the billet surface at the same location as in step 1) is collected and plotted as a billet surface temperature change curve. This curve is compared with the temperature change curve of the billet surface at that location obtained by numerical simulation in step 1), thereby correcting the numerical simulation model in step 1) until the result of the temperature change curve of the billet surface at that location obtained by the corrected numerical simulation of the casting process is completely consistent with the collected temperature change curve of the billet surface at that location. Finally, numerical simulation of the casting process in step 1) is performed, and the "temperature-solidification model" is obtained again through step 2). 4) Input the "temperature-solidification model" from step 3) into the physical simulation experimental device as the control program to perform physical simulation; obtain the solidification unit of the sample from the surface of the billet to the core under the specific casting conditions, and perform experimental characterization of solute element segregation on the solidification unit. 5) Cut the billet in step 3) along the cross section, perform physicochemical tests on the solute element segregation of the cross section, and compare it with the solute element segregation results of the solidification unit in step 4); then make a correction to the "temperature-solidification model" in step 3) until the solute element segregation characterization results of the solidification unit and the actual billet under the mold casting conditions are completely consistent. 6) Select several other sets of casting conditions and repeat steps 1) to 5). Make a second correction to the "temperature-solidification model" in step 5) to ensure that under any casting conditions, the "temperature-solidification model" obtained by step 1) can represent the relevant temperature and solidification physical changes in the actual casting process. 7) Using the "temperature-solidification model" after secondary correction in step 6) as boundary conditions, within a reasonable casting process regime, adopt a mathematical model based on the coupling of temperature field, phase field and solute field, input these mathematical models into the numerical simulation software in the form of differential equations, and perform numerical simulation of solute element segregation from the surface of the billet to the core at the same location as in step 1) under the casting conditions, obtain the numerical simulation prediction results of solute element segregation, and select the process regime that makes the simulation results have the lowest degree of solute element segregation as the optimal casting process for the steel grade in step 1).

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