Computer simulation method for continuous casting process

Abstract

The invention discloses a computer simulation method for a continuous casting process, which comprises the following steps of: setting an initial condition of metal as an initial temperature of the metal when liquid metal is injected into a mold, setting an initial condition of the mold as a temperature of the mold at a metal inlet, and uniformly dividing an established three-dimensional model of the metal and the mold into a plurality of sections, after the corresponding temperature boundary conditions of each section of metal and the mold are set, flow filling simulation analysis does not need to be carried out like a common casting process, and the temperature distribution of the metal and the mold and the structure evolution process of the metal at any time can be obtained only through numerical simulation of direct cooling and solidification.

Description

Technical Field

[0001] The invention relates to the technical field of continuous casting, and in particular to a computer simulation method for a continuous casting process. Background Art

[0002] Casting refers to a metal processing method in which solid metal is melted into liquid form, and then the liquid metal is poured into a casting mold cavity of a certain shape and size under the action of pressure or gravity, and then cooled and solidified to obtain parts or blanks. Casting has a wide range of applications in the manufacturing industry. Computer simulation of the casting process refers to the use of numerical technology to simulate the pouring, filling and solidification process of the casting in the casting mold cavity, obtain the flow filling of the molten metal in the cavity, and the temperature changes of the casting and the mold, predict the solidification structure and mechanical properties of the casting, and obtain the quantitative relationship between the main process parameters and the solidification structure of the casting, thereby providing a theoretical basis for optimizing the casting process and the best quality control. Conventional casting process is an intermittent processing process, and its computer simulation process is 1. Establishing numerical models of casting parts and molds; 2. Setting the initial conditions and boundary conditions of the molten metal and mold during casting; 3. Performing numerical simulation calculations of the flow and filling of the molten metal in the mold cavity to obtain the flow and filling of the molten metal in the mold cavity and temperature changes at different times; 4. Performing numerical simulation calculations of the casting and mold temperature and the solidification of the casting to obtain the temperature changes of the casting and mold at different times, as well as the solidification and structural changes of the casting. 5. The process law analysis of the casting process can be carried out based on the flow and filling, temperature changes, solidification process, structural changes, etc. of the casting at different times.

[0003] Metal continuous casting is to pour molten metal into the metal mold cavity of the crystallizer from one end, and then pull it out from the other end of the crystallizer after it solidifies gradually. It can obtain castings with constant cross-section of any length or specific length, such as Figure 1 shown.

[0004] Compared with the general casting process, the metal continuous casting process is significantly different in the flow and solidification of the molten metal, and the relationship between the casting and the mold. During the metal continuous casting process, the molten metal basically does not flow relative to the mold of the crystallizer, but will move to the next position synchronously with the mold, gradually cool and solidify until it finally comes out of the mold. At any time, the spatial distribution of various field quantities such as the temperature of the casting and the mold in the corresponding area of ​​the crystallizer is almost exactly the same. Conventional casting computer simulation methods cannot be used to simulate the metal continuous casting process and obtain the flow filling, temperature changes, solidification process, and organizational changes of the casting at different times.

[0005] Moreover, in the process of computer simulation of metal continuous casting, if a small section of metal in the crystallizer is used as the object for numerical simulation analysis, it is difficult to deal with the thermal conductivity relationship and temperature boundary conditions between the analysis object and the front and rear metals because the metal is moving at any time and the temperature conditions are changing from the inlet to the outlet; if the entire section of metal in the crystallizer is used as the object for numerical analysis, it is difficult to impose temperature boundary conditions because the metal is moving at any time, new metal flows into the inlet, and metal is pulled out of the outlet, and the temperature conditions at different positions are different when the metal moves. Summary of the invention

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a computer simulation method for a continuous casting process.

[0007] To achieve the above purpose, the technical solution provided by the present invention is:

[0008] A computer simulation method for a continuous casting process, comprising:

[0009] Create 3D models of metal and molds for metal continuous casting process analysis;

[0010] Input the thermal properties of metal and mold and the material parameters of solidification structure evolution;

[0011] Set the initial conditions of the metal and the die;

[0012] The established three-dimensional model of metal and mold is evenly divided into several sections;

[0013] The computer simulation analysis time of the metal continuous casting process is divided into several equal segments accordingly;

[0014] Input the corresponding temperature boundary conditions of metal and mold in each model area in each time period;

[0015] Combining the input thermal performance parameters of the metal and the mold and the material parameters of the solidification structure evolution, the heat conduction process of the metal and the mold and the solidification process of the metal are numerically calculated to obtain the temperature distribution of the metal and the mold at any time and the metal's organizational evolution process.

[0016] Furthermore, the initial condition of the metal is set to be the initial temperature of the metal when the molten metal is injected into the mold;

[0017] The initial condition of the mold is set to the temperature of the mold at the metal inlet.

[0018] Furthermore, according to the analysis accuracy requirements, the established three-dimensional model of the metal and the mold is evenly divided into several sections, and then the divided several sections of the model are meshed for surface mesh and volume mesh finite element division.

[0019] Furthermore, according to the analysis accuracy requirement, the computer simulation analysis time of the metal continuous casting process is divided into several sections that are the same as the model.

[0020] Furthermore, it is assumed that the established three-dimensional model of the metal and mold is evenly divided into M sections, and the time of the computer simulation analysis is also divided into M sections. The i-th section of the metal and the mold sets the temperature boundary conditions from the 1st time period to the i-th time period, and the 1st time period to the i-1th time period is the same as the i-1th section. There is no restriction on whether the boundary conditions of different time periods in each section are the same, and the i+1th time period to the Mth time period are set as adiabatic boundary conditions.

[0021] Furthermore, the thermal performance parameters of metals include thermal conductivity, density, enthalpy, solid fraction, Newtonian viscosity, and Poisson's ratio.

[0022] Furthermore, the material parameters of the solidification structure evolution of metals include the dendrite tip growth kinetic coefficient and nucleation parameter;

[0023] Dendrite tip growth kinetics coefficient a 2 and a 3 They are all determined by the initial composition of the metal, the liquidus slope, the solute equilibrium distribution coefficient, the solute self-diffusion coefficient and the Gibbs-Thomson coefficient.

[0024] Furthermore, the required dendrite tip growth kinetics coefficient a 2 and a 3 , the initial composition of the metal, the liquidus slope, the solute equilibrium distribution coefficient, and the solute self-diffusion coefficient are all calculated using the Scheil diffusion model, and the Gibbs-Thomson coefficient is a constant set through experimental experience.

[0025] Furthermore, the nucleation parameters include surface nucleation parameters and body nucleation parameters, both of which also include average undercooling degree, standard deviation and nucleation density of nucleation;

[0026] The relationship between the surface kernel parameters and the body kernel parameters is as follows:

[0027]

[0028] N v is the body shape kernel parameter, N S is the surface kernel parameter.

[0029] Furthermore, when numerically calculating the heat conduction process of the metal and the mold and the solidification process of the metal, the temperature field of the metal solidification in the model is first calculated, and then it is divided into fine and uniform nodes, and the nucleation and growth calculations are performed using the cellular automaton method;

[0030] The model is established by coupling the cellular automation method with the finite element method.

[0031] Compared with the existing technology, the principles and advantages of this technical solution are as follows:

[0032] The initial condition of the metal set in this technical solution is the initial temperature of the metal when the liquid metal is injected into the mold, and the initial condition of the mold is the temperature of the mold at the metal entrance. The established three-dimensional model of the metal and the mold is evenly divided into several sections. After setting the corresponding temperature boundary conditions for each section of the metal and the mold, there is no need to perform flow filling simulation analysis like a general casting process. Only direct cooling and solidification numerical simulation is required to obtain the temperature distribution of the metal and the mold at any time and the metal's organizational evolution process. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions are briefly introduced below. 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 creative work.

[0034] Figure 1 A principle flow chart of a computer simulation method for a continuous casting process of the present invention;

[0035] Figure 2 It is a schematic diagram of the metal continuous casting process;

[0036] Figure 3 It is a schematic diagram of the three-dimensional model of continuous casting metal;

[0037] Figure 4 This is the relationship between the thermal performance parameters of pure copper and temperature;

[0038] Figure 5 It is a schematic diagram of the segmentation of continuous casting metal;

[0039] Figure 6 It is the temperature boundary condition curve diagram of the 50th segment;

[0040] Figure 7 Schematic diagram of temperature field distribution and grain structure distribution (the left side is temperature field distribution, the right side is grain structure distribution);

[0041] Figure 8 Schematic diagram of temperature field distribution, solid-liquid field distribution and grain structure field distribution in different metal sections at different time periods (temperature field distribution on the left, solid-liquid field distribution in the middle, and grain structure field distribution on the right). DETAILED DESCRIPTION

[0042] The present invention will be further described below in conjunction with specific embodiments:

[0043] like Figure 1 As shown, a computer simulation method for a continuous casting process described in this embodiment includes:

[0044] S1. Establish a three-dimensional model of metal and mold for metal continuous casting process analysis;

[0045] according to Figure 2 A schematic diagram of the metal continuous casting process is used to construct a 3D CAD model of the continuous casting metal, such as Figure 3 The three-dimensional CAD model of continuous casting metal is shown in Table 1.

[0046] Table 1 Specific parameters of 3D CAD model

[0047]

[0048] S2, input the thermal properties parameters of metal and mold and the material parameters of solidification structure evolution;

[0049] (1) Thermal performance parameters

[0050] Accurate thermal performance parameters are the key to high-quality simulation. Through a comprehensive thermodynamic database, the curves of key parameters such as thermal conductivity, density, enthalpy, solid fraction, Newtonian viscosity, Poisson's ratio, etc. can be automatically calculated based on the chemical composition input by the user. These data will be automatically saved for use during the simulation. At the same time, if more accurate information is available, these automatically calculated results can also be manually adjusted to ensure the accuracy of the simulation results. According to the thermodynamic database, the thermal performance parameters of the metal copper material are obtained, such as Figure 4 shown.

[0051] (2) Material parameters of solidification structure evolution

[0052] The microstructure of the metal is simulated, and the microstructure simulation parameters are mainly the dendrite tip growth kinetics coefficient and nucleation parameters.

[0053] (a) Dendrite tip growth kinetics coefficient

[0054] The dendrite tip growth kinetics coefficient affects the growth behavior of the dendrite at the solidification front, including the growth rate and growth direction. This coefficient is determined by the initial composition of the metal (C0), the liquidus slope (m), the solute equilibrium distribution coefficient (k), the solute self-diffusion coefficient (Dl) and the Gibbs-Thomson coefficient. The Gibbs-Thomson coefficient involves the relationship between the solid-liquid interface energy and the grain size, and has a significant regulatory effect on the curvature and growth kinetics of the dendrite tip, and determines the dendrite growth kinetics coefficient a during the solidification simulation process. 2 and a 3In simulation, these coefficients are usually determined by experimental data or theoretical models (such as the Kurz-Giovanola-Trivedi (KGT) model). For the Gibbs-Thomson coefficient, this coefficient is difficult to obtain experimentally. Based on experimental experience, this parameter is set to 2x10 -7 .

[0055] The required dendrite growth kinetics coefficient a can be calculated using the Scheil diffusion model 2 =2.805561×10 -8 and a 3 =4.717442×10 -6 As well as the initial composition of the metal (C0), liquidus slope (m), solute equilibrium distribution coefficient (k), solute self-diffusion coefficient (Dl), etc.

[0056] (b) Nucleation parameters

[0057] According to the cellular automaton (CA) model, the nucleation parameters are divided into surface nucleation parameters and volume nucleation parameters, both of which include the average undercooling degree, standard deviation and nucleation density.

[0058] In actual solidification simulation, these parameters need to be accurately determined through experimental data or theoretical calculations so that the simulation results can truly reflect the solidification behavior of the alloy under actual production conditions. There is a relationship between the surface nucleation parameters and the body nucleation parameters:

[0059]

[0060] In the following experimental design, the surface kernel density N is taken s,max =1.5x10 7 , then the body shape kernel density is N v,max =1.5x10 8 Take the average supercooling degree of surface nucleation ΔT s,max =1K, average supercooling of bulk nuclei ΔT v,max =3, standard deviation of face kernel and body kernel ΔT s,σ , ΔT v,σ All are 0.5K, used for simulation calculations.

[0061] Table 2 Microscopic simulation parameters

[0062]

[0063] S3, setting the initial conditions of the metal and the mold;

[0064] In this step,

[0065] The initial condition of the metal is set to an initial temperature of 1120°C when the metal is injected into the mold. This temperature is higher than the melting point of pure copper (1083.4°C), ensuring that the copper is completely in liquid form while providing sufficient superheat to optimize the casting process. Superheating helps reduce the oxide and gas content in the molten metal, improves fluidity, and thus helps fill the mold cavity, and reduces turbulence and oxidation during the filling process, thereby improving the overall quality of the casting and reducing casting defects.

[0066] The initial condition of the mold is set to 300℃ at the metal inlet, which is lower than the melting point of copper. This temperature difference helps to form an appropriate temperature gradient, ensuring that the molten metal can be quickly cooled when entering the mold and start the solidification process, and also avoids the phenomenon of cold shut caused by the molten metal being chilled. It helps to quickly form a solidified shell, thereby helping to control the size of the casting and reduce deformation, and form a fine-grained structure on the surface of the casting to improve the mechanical properties of the casting.

[0067] S4. The established three-dimensional model of metal and mold is evenly divided into 100 segments, and then the 100 segment models are divided into surface mesh and volume mesh finite element. Meshing is to divide the model into smaller units. Meshing is an important part of the pre-processing of finite element analysis. The quality of the mesh directly determines the quality of the subsequent finite element calculation. In order to obtain more accurate results, the overall mesh division of the geometric model is relatively dense. The grid size is set to 4mm, the number of mesh nodes is 182945, the number of surface meshes is 38536, and the number of volume meshes is 144409. The division results are as follows: Figure 5 shown.

[0068] S5. According to the analysis accuracy requirements, the computer simulation analysis time of the metal continuous casting process is divided into several sections that are the same as the model.

[0069] S6. Input the corresponding temperature boundary conditions of the metal and the mold in each model area in each time period;

[0070] Since the established three-dimensional model of metal and mold is evenly divided into 100 segments, the time of computer simulation analysis is also divided into 100 segments. The i-th segment area of ​​the metal and mold sets the temperature boundary conditions from the 1st time period to the i-th time period, and the 1st time period to the i-1th time period is the same as the i-1th segment area. There is no restriction on whether the boundary conditions of different time periods in each segment are the same. The i+1th time period to the 100th time period are set as adiabatic boundary conditions.

[0071] Heat transfer parameters need to be set between the metal and the mold, and between the mold and the water cooling area. According to the casting manual, the recommended value of the heat transfer coefficient h of the metal-to-metal interface is 1000-5000. Under natural convection or low-speed forced convection conditions during water cooling, the heat transfer coefficient may be 800-6000W / (m2 ·K) Through production verification and numerical simulation, the heat transfer coefficient of copper is 1000-3000, and the heat transfer coefficient between metal and mold and the heat transfer coefficient of mold water cooling is selected as h=1300.

[0072] The metal and mold are divided into 100 segments, and the total analysis time is also divided into 100 segments. The total temperature field simulation running time is 24.3s, and the crystallization time is 25s. The temperature boundary conditions for the first segment of the metal and mold are set, and the adiabatic boundary conditions are set for the 2nd to 100th segments; the temperature boundary conditions from the 1st segment to the 1st segment are set for the i-th segment of the metal and mold, and the adiabatic boundary conditions are set for the i+1st to 100th segments; the temperature boundary conditions from the 1st segment to the 100th segment of the metal and mold are set.

[0073] For example, the temperature boundary condition of the 50th section of the metal and mold area is set to 1300W / (m 2 ·K), adiabatic boundary conditions are set from time 51 to time 100. That is, heat exchange is carried out from 0 to 12.15s in the 50th segment, and the adiabatic state is in 12.18 to 25s.

[0074] Similarly, set the corresponding temperature boundary conditions for each segment. There is no restriction on whether the boundary conditions of each segment are the same. They can be the same or different. The temperature boundary condition curve of segment 50 is as follows: Figure 6 shown.

[0075] S6. Combine the input thermal performance parameters of the metal and the mold and the material parameters of the solidification structure evolution, perform numerical calculations on the heat conduction process of the metal and the mold and the solidification process of the metal, and obtain the temperature distribution of the metal and the mold at any time and the metal's structure evolution process.

[0076] In this step, after all the parameters required for numerical simulation are sorted out, simulation calculations can be carried out. First, the temperature field of metal solidification in the model is calculated, and then it is divided into fine and uniform nodes, and the nucleation and growth calculations are performed using the cellular automation method.

[0077] The CAFE method is used here to simulate the grain structure. The CAFE model is a model established by coupling the cellular automaton method (CA) and the finite element method (FE). Its main function is to simulate the growth of copper grain structure and clearly see the growth state of the grains, reflecting the process of high-temperature copper liquid solidifying into a copper layer.

[0078] Open the file obtained after numerical calculation to observe the changes in the temperature field, solidification field and micro grain growth simulation of the metal over time. Switching different views can observe specific changes.

[0079] The temperature field distribution and grain structure distribution of steady-state calculation are as follows Figure 7 As shown in the figure, it can be seen that as the horizontal continuous casting proceeds, under the cooling effect, the temperature of the copper billet gradually decreases from the head to the tail of the crystallizer, completing the solidification and forming process of the copper-clad steel. It can be seen from the figure that during the solidification and forming process, a certain thickness of copper structure has been formed on the outer surface of the front section of the mold. As time goes by, under the effect of water cooling, the amount of copper structure in the rear section increases sharply, and the rear section is completely solidified.

[0080] Through the slicing operation, we can observe the temperature field distribution, solid-liquid field distribution and grain structure field distribution diagram of different metal parts in different time periods, such as Figure 8 shown.

[0081] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A computer simulation method for a continuous casting process, characterized in that: include: Create 3D models of metal and molds for metal continuous casting process analysis; Input the thermal properties of metal and mold and the material parameters of solidification structure evolution; Set the initial conditions of the metal and the die; The established three-dimensional model of metal and mold is evenly divided into several sections; The computer simulation analysis time of the metal continuous casting process is divided into several equal segments accordingly; Input the corresponding temperature boundary conditions of metal and mold in each model area in each time period; Combining the input thermal performance parameters of the metal and the mold and the material parameters of the solidification structure evolution, the heat conduction process of the metal and the mold and the solidification process of the metal are numerically calculated to obtain the temperature distribution of the metal and the mold at any time and the metal's organizational evolution process.

2. A computer simulation method for a continuous casting process according to claim 1, characterized in that: The initial condition of the metal is set to be the initial temperature of the metal when the liquid metal is injected into the mold; The initial condition of the mold is set to the temperature of the mold at the metal inlet.

3. A computer simulation method for a continuous casting process according to claim 1, characterized in that: According to the analysis accuracy requirements, the established three-dimensional model of metal and mold is evenly divided into several sections, and then the divided several sections of the model are meshed for surface mesh and volume mesh finite element division.

4. A computer simulation method for a continuous casting process according to claim 1, characterized in that: According to the analysis accuracy requirements, the computer simulation analysis time of the metal continuous casting process is divided into several sections that are the same as the model.

5. A computer simulation method for a continuous casting process according to claim 1, characterized in that: Assume that the established three-dimensional model of metal and mold is evenly divided into M sections, and the time of computer simulation analysis is also divided into M sections. The i-th section of the metal and mold is set with temperature boundary conditions from the 1st time period to the i-th time period, and the 1st time period to the i-1th time period is the same as the i-1th section. There is no restriction on whether the boundary conditions of different time periods in each section are the same. The i+1th time period to the Mth time period are set as adiabatic boundary conditions.

6. A computer simulation method for a continuous casting process according to claim 1, characterized in that: The thermal properties of metals include thermal conductivity, density, enthalpy, solid fraction, Newtonian viscosity, and Poisson's ratio.

7. A computer simulation method for a continuous casting process according to claim 1, characterized in that: The material parameters of the solidification structure evolution of metals include the dendrite tip growth kinetics coefficient and nucleation parameters; Dendrite tip growth kinetics coefficient a 2 and a 3 They are all determined by the initial composition of the metal, the liquidus slope, the solute equilibrium distribution coefficient, the solute self-diffusion coefficient and the Gibbs-Thomson coefficient.

8. A computer simulation method for a continuous casting process according to claim 6, characterized in that: The required dendrite tip growth kinetics coefficient a 2 and a 3 , the initial composition of the metal, the liquidus slope, the solute equilibrium distribution coefficient, and the solute self-diffusion coefficient are all calculated using the Scheil diffusion model, and the Gibbs-Thomson coefficient is a constant set through experimental experience.

9. A computer simulation method for a continuous casting process according to claim 6, characterized in that: The nucleation parameters include the surface nucleation parameters and the body nucleation parameters, both of which include the average undercooling degree, standard deviation and nucleation density of nucleation. The relationship between the surface kernel parameters and the body kernel parameters is as follows: N v is the body shape kernel parameter, N S is the surface kernel parameter.

10. A computer simulation method for a continuous casting process according to claim 1, characterized in that: When numerically calculating the heat conduction process of metal and mold and the solidification process of metal, the temperature field of metal solidification in the model is first calculated, and then it is divided into fine and uniform nodes, and the nucleation and growth calculations are performed using the cellular automation method; The model is established by coupling the cellular automation method with the finite element method.

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