Simulation method of CET transformation in welding pool of lightweight magnesium alloy for automobile based on phase field dynamics

Abstract

The present invention belongs to the technical field of material welding process, and specifically relates to a CET transformation simulation method in a lightweight magnesium alloy welding pool for automobiles based on phase field dynamics and its application. The simulation method comprises the following steps: (1) initializing the simulation conditions, initializing the model, and constructing the model according to the parameters of the welding pool solidification process; (2) constructing a macro model, assuming that the solidification area of ​​the welding pool is one-quarter of the ellipse, and establishing a macro heat transfer and growth model based on the assumption; (3) constructing a phase field model, establishing a phase field model that simulates the CET transformation; (4) calculating the phase field model, introducing the dendrite growth rate into the phase field model, introducing the nucleation model, solving, and calculating the macro-micro coupled phase field model. The present invention can dynamically reproduce the change process of columnar crystals and equiaxed crystals during welding, which helps to deepen the understanding of the evolution process of alloy welding microstructure and lays the foundation for the evolution of microstructure and optimization of welding process.

Description

Technical Field

[0001] The present invention belongs to the technical field of material welding processes, and in particular relates to a CET transformation simulation method in a lightweight automotive magnesium alloy welding molten pool based on phase field dynamics and its application. Background Art

[0002] The CET transition (columnar to equiaxed transition) occurs during the solidification process of an alloy. Equiaxed crystals slowly nucleate and grow ahead of the columnar crystals, ultimately blocking their growth and forcing a physical transformation from columnar to equiaxed crystals. Due to the high welding speeds and rapid cooling of the weld pool during laser welding, an undercooled zone easily forms within the weld pool. This creates extremely favorable conditions for the CET transition to occur within the weld pool. Observing this phenomenon requires extensive experimental research, which requires significant effort, time, and money. However, the rapid development of high-performance computing technology and the continuous improvement of solidification theory in recent years have made numerical simulation a novel technique for studying microstructural changes during solidification. This technology can more accurately and dynamically demonstrate the various phenomena and evolutionary patterns during alloy solidification, thus overcoming the shortcomings of traditional experimental methods.

[0003] Commonly used numerical simulation methods are as follows: deterministic method, Monte Carlo method (MC), Cellular automaton method (CA), Phase field method (PF), etc. Since the cooling speed of the welding pool is high and the metal in the welding pool is in motion, its internal changes are very complex. The phase field method uses one or more field variables that are continuously distributed in space to characterize the changes of the system. By introducing the order parameter It avoids explicitly tracking the position of the solid / liquid interface, thus avoiding the trouble of having to deal with different phases and interfaces separately in traditional sharp interface models. At the same time, it also overcomes the tedious mathematical processing problems brought about by real-time tracking of the interface and can describe the changes in arbitrarily complex microstructure morphology.

[0004] Magnesium is the lightest metal structural material and plays a vital role in the advancement of lightweighting in automobiles. It is primarily used in automobile body brackets, and welding is a crucial step in the automobile manufacturing process. Because the mechanical properties of an alloy are closely related to the microstructure formed during welding solidification, it is necessary to conduct in-depth research on the microstructural evolution of magnesium alloys. Currently, simulations of the solidification microstructure of magnesium alloys tend to focus on the growth of columnar or equiaxed crystals, while simulations of the evolution of columnar to equiaxed crystals are relatively rare. However, the growth of columnar to equiaxed crystals often occurs during solidification. In summary, establishing a model for the CET transformation in the magnesium alloy weld pool is particularly important. This helps to address the problem of the lack of CET transformation process in magnesium alloys in existing technologies and is of great significance for revealing the evolution of magnesium alloy microstructure and improving the mechanical properties of welds.

[0005] Therefore, it is crucial to establish a phase field model that can reflect the CET transformation in the welding pool based on the Ginzburg-Landau theory. Summary of the Invention

[0006] One of the objectives of the present invention is to provide a phase field dynamics-based method for simulating the CET transformation in the weld pool of lightweight automotive magnesium alloys. Based on the Ginzburg-Landau theory, a phase field model that can reflect the CET transformation of magnesium alloys in the weld pool is established to solve the problem of the lack of CET transformation process of magnesium alloys in the existing technology, so as to reveal the changing laws of the microstructure of magnesium alloys and improve the mechanical properties of welds.

[0007] The technical solution of the present invention for simulating CET transformation in a lightweight automotive magnesium alloy welding pool based on phase field dynamics is as follows:

[0008] The phase field dynamics-based CET transformation simulation method in the weld pool of lightweight automotive magnesium alloys includes the following steps:

[0009] (1) Initialization of simulation conditions: First, the model is initialized based on the real thermodynamic data of the alloy constructed by thermodynamic calculation software. Then, the conditions are simplified and the model is constructed based on the parameters of the welding pool solidification process.

[0010] (2) Construct a macroscopic model, assuming that the solidification area of ​​the weld pool is one-quarter of the ellipse, and establish a macroscopic heat transfer and growth model based on this assumption;

[0011] (3) Construct a phase field model based on the Ginzburg-Landau theory to simulate the CET transformation in the welding pool;

[0012] (4) Calculating the phase field model, introducing the dendrite growth rate and temperature gradient calculated in step (2) into the above phase field model, then introducing the nucleation model, solving the above nucleation model with the finite difference method, and calculating the macro-micro coupled phase field model.

[0013] This CET transformation simulation method can simulate the evolution of dendrites from columnar crystals to equiaxed crystals during the solidification process of magnesium alloys, and can also simulate different parameters, which is of great significance for refining the weld microstructure and improving the mechanical properties of the weld.

[0014] Preferably, to ensure the computability and simplicity of the model, in step (1), the following assumptions are made during the model construction process:

[0015] ① Assume that the shape of the weld pool does not change during the laser welding process;

[0016] ② Ignore the effect of liquid flow inside the welding pool on temperature and solute distribution;

[0017] ③The temperature in the welding pool is distributed linearly with a gradient.

[0018] Further preferably, in step (1), the alloy phase diagram generated by the Pandat phase diagram software is used to calculate the solute distribution coefficient k and the liquidus slope m of the alloy; and the parameters required for the alloy phase field are obtained according to the thermodynamic database of the Pandat phase diagram software to achieve the purpose of model digitization.

[0019] More preferably, the parameters required for the alloy phase field include the melting point T m , initial concentration C0, solute diffusion coefficient D, Gibbs-Thomson coefficient Γ.

[0020] Preferably, in step (1), the simplified conditions include defining the temperature field equation, order parameter, and solute concentration field equation, so as to simplify the established model accordingly. Before the simulation calculation, each grid in the calculation area is assigned an initial value.

[0021] Preferably, in step (2), the equation of the semi-ellipse of the solidification area of ​​the welding pool is:

[0022]

[0023] Among them, l a is the length of the second half of the molten pool, l b is the depth of the weld pool, the x-axis is the forward direction of welding, and the y-axis is the vertical direction;

[0024] Assuming that the angle between the crystallization direction and the welding direction at any point on the fusion line is θ, during the laser welding process, the welding pool moves at a constant speed following the laser, while the advancement speed of the solid / liquid interface V s(t) is consistent with the welding speed in the normal direction of the solid / liquid interface and is expressed as:

[0025] V s (t)=Vcosθ

[0026] Among them, V is the welding speed.

[0027] Preferably, in step (3), in order to improve the calculation efficiency, the interface width of the diffusion interface is defined as several orders of magnitude multiples of the actual interface thickness in the phase field model. At the same time, the influence of the latent heat of crystallization is ignored, and the welding pool temperature field T(z) equation is defined as:

[0028]

[0029] Where z is the coordinate parallel to the dendrite growth direction, T0 is the temperature of the reference point, is the solute concentration in the liquid phase, l T is the length of the solidification interval, T is the dimensionless temperature, m is the liquidus slope, and G is the maximum temperature gradient of the solid / liquid interface. The expression is:

[0030]

[0031] Where t is the solidification time, T c is the temperature at the center of the weld pool, T s is the crystallization temperature, x(t), y(t) are the positions of the solid / liquid interface relative to the center of the molten pool.

[0032] Further preferably, in order to more accurately describe the evolution process of columnar crystals to equiaxed crystals and make the model more precise, in step (3), a nucleation model describing the evolution process of columnar crystals to equiaxed crystals is introduced, and its expression is:

[0033]

[0034]

[0035] Where s is the degree of supercooling, ρ max is the maximum nucleation density, s σ is the standard deviation of supercooling, s ρ is the degree of supercooling of nucleation; when s≥s ρ When , the crystal form changes from columnar crystal to equiaxed crystal; a random number is introduced as a restriction condition to determine the nucleation site. If ρ(s) is greater than the random number, nucleation occurs, where the random number is between 0 and 1; the finite difference method is used to solve it after applying boundary conditions.

[0036] Furthermore, an order parameter ξ is introduced to characterize the physical state, where ξ = -1 represents the liquid phase, ξ = 1 represents the solid phase, and ξ changes continuously between the solid and liquid phases. The phase field equation including the order parameter ξ is as follows:

[0037]

[0038] in, is the dimensionless form of T(z), W is the interface width, τ0 is the relaxation time parameter, which links W and τ0 through the coupling parameter λ, eliminating the interface dynamic parameters under arbitrary temperature and orientation conditions;

[0039]

[0040] The solute concentration field is expressed by introducing the dimensionless supersaturation field U:

[0041]

[0042] Among them, k is the solute distribution coefficient, c is the solute solubility distribution, c ∞ It is the equilibrium solubility in the liquid phase away from the solid-liquid interface.

[0043] Preferably, step (4) includes the following steps: bringing the temperature gradient and dendrite growth rate calculated in step (2) into the phase field model; calculating the solute field distribution through step (3); and finally using the solute field calculation results, temperature field and growth rate results to solve the phase field parameter changes and solve the introduced nucleation model; the change of the phase field parameters represents the movement of the solid-liquid interface, and finally forms different dendrite growth processes, solute solubility distributions and flow field distributions, and the calculated phase field variables affect the molten pool field distribution and flow field distribution of the next time step; the above calculation process will be performed once at each time step until the calculation is completed. Finally, the simulation calculation and the results are exported to obtain and export the evolution results of the CET transition.

[0044] A second object of the present invention is to provide an application of a CET transformation simulation method in a lightweight automotive magnesium alloy welding pool based on phase field dynamics.

[0045] An application of the above-mentioned CET transformation simulation method in the molten pool of lightweight automotive magnesium alloy welding based on phase field dynamics, which is used to simulate the welding of lightweight automotive magnesium alloy.

[0046] Preferably, the simulation method is used to simulate the evolution of columnar crystals to equiaxed crystals during welding of lightweight magnesium alloys for automobiles.

[0047] This simulation method can simulate the microstructure evolution process of lightweight automotive magnesium alloy welding, which will help to deeply study the evolution mechanism of magnesium alloy microstructure, promote the application of magnesium alloy industry in lightweight automobiles, and advance the realization of "dual carbon".

[0048] Beneficial effects: The CET transformation simulation method can simulate the evolution of dendrites from columnar crystals to equiaxed crystals during the solidification process of magnesium alloys. It can also simulate the influence of different parameters such as time and the number of heterogeneous nucleation substrates on the solidification process. It is of great significance to refine the weld microstructure and improve the mechanical properties of the weld, and lays the foundation for the study of microstructure evolution and the optimization of welding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is the molten pool morphology in Example 2 of the present invention;

[0050] Figure 2 is the molten pool temperature field in Example 2 of the present invention;

[0051] Figure 3 It is a schematic diagram of the CET transformation simulation results in the Mg-6wt% Gd alloy molten pool in Example 2 of the present invention. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is further described below in conjunction with specific implementation methods.

[0053] Example 1

[0054] A phase field dynamics-based CET transformation simulation method in a lightweight automotive magnesium alloy welding molten pool comprises the following steps:

[0055] (1) Initialization of simulation conditions. First, the model is initialized by constructing the real thermodynamic data of the alloy according to the thermodynamic calculation software. That is, the solute distribution coefficient k and liquidus slope m of the alloy can be calculated by using the alloy phase diagram generated by Pandat software. According to the thermodynamic database of Pandat phase diagram software, the parameters required for the alloy phase field are obtained. Then, the conditions are simplified, such as defining the temperature field equation, order parameter, and solute concentration field equation, and the model is constructed according to the parameters of the welding pool solidification process. To ensure the computability and simplicity of the model, the following assumptions are made in the process of model construction: ① Assume that the shape of the welding pool does not change during the laser welding process; ② Ignore the influence of liquid flow inside the welding pool on the temperature and solute distribution; ③ The temperature in the welding pool is distributed linearly in a gradient;

[0056] (2) Construct a macroscopic model, assuming that the solidification area of ​​the weld pool is one-quarter of the ellipse, and establish a macroscopic heat transfer and growth model based on this assumption; the equation of the semi-ellipse of the weld pool solidification area is:

[0057]

[0058] Among them, l a is the length of the second half of the molten pool, l b is the depth of the weld pool, the x-axis is the forward direction of welding, and the y-axis is the vertical direction;

[0059] Assuming that the angle between the crystallization direction and the welding direction at any point on the fusion line is θ, during the laser welding process, the welding pool moves at a constant speed following the laser, while the advancement speed of the solid / liquid interface V s (t) is consistent with the welding speed in the normal direction of the solid / liquid interface and is expressed as:

[0060] V s (t)=Vcosθ

[0061] Where V is the welding speed.

[0062] (3) Construct a phase field model. Based on the Ginzburg-Landau theory, a phase field model simulating the CET transition is established. The welding pool temperature field T(z) equation is defined as:

[0063]

[0064] Where z is the coordinate parallel to the dendrite growth direction, T0 is the temperature of the reference point, is the solute concentration in the liquid phase, l T is the length of the solidification interval, T is the dimensionless temperature, m is the liquidus slope, and G is the maximum temperature gradient of the solid / liquid interface. The expression is:

[0065]

[0066] Where t is the solidification time, T c is the temperature at the center of the weld pool, T s is the crystallization temperature, x(t), y(t) are the positions of the solid / liquid interface relative to the center of the molten pool;

[0067] A nucleation model is introduced to describe the evolution process of columnar crystals to equiaxed crystals. Its expression is:

[0068]

[0069]

[0070] Where s is the degree of supercooling, ρ max is the maximum nucleation density, s σ is the standard deviation of supercooling, s ρ is the degree of supercooling of nucleation; when s≥s ρWhen , the crystal form changes from columnar crystal to equiaxed crystal; a random number is introduced as a restriction condition to determine the nucleation site. If ρ(s) is greater than the random number, nucleation occurs, where the random number is between 0 and 1; the finite difference method is used to solve it after applying boundary conditions;

[0071] The order parameter ξ is introduced to characterize the physical state, where ξ = -1 represents the liquid phase, ξ = 1 represents the solid phase, and ξ changes continuously between the solid phase and the liquid phase. The phase field equation including the order parameter ξ is as follows:

[0072]

[0073] in, is the dimensionless form of T(z), W is the interface width, τ0 is the relaxation time parameter, which links W and τ0 through the coupling parameter λ, eliminating the interface dynamic parameters under arbitrary temperature and orientation conditions;

[0074]

[0075] The solute concentration field is expressed by introducing the dimensionless supersaturation field U:

[0076]

[0077] Among them, k is the solute distribution coefficient, c is the solute solubility distribution, c ∞ is the equilibrium solubility in the liquid phase away from the solid-liquid interface;

[0078] (4) Calculating the phase field model, introducing the dendrite growth rate and temperature gradient calculated in step (2) into the phase field model in step (3), introducing the nucleation model, solving the above nucleation model with the finite difference method, and calculating the macro-micro coupled phase field model.

[0079] Example 2

[0080] A phase field dynamics-based CET transformation simulation method in a lightweight automotive magnesium alloy welding molten pool comprises the following steps:

[0081] (1) Initialization of simulation conditions: The model is initialized by constructing the real thermodynamic data of the alloy according to the thermodynamic calculation software. That is, the alloy phase diagram generated by Pandat software is used to calculate the solute distribution coefficient k and liquidus slope m of the alloy. According to the thermodynamic database of Pandat phase diagram software, the parameters required for the alloy phase field are obtained. Then, the conditions are simplified, such as defining the temperature field equation, order parameter, and solute concentration field equation, and the model is constructed according to the parameters of the welding pool solidification process. To ensure the computability and simplicity of the model, the following three assumptions are made in the process of model construction: ① Assume that the shape of the welding pool keeps changing during the laser welding process; ② Ignore the influence of liquid flow inside the welding pool on the temperature and solute distribution; ③ The temperature in the welding pool is distributed linearly in a gradient;

[0082] Taking Mg-6wt%Gd as an example, the parameters obtained by Pandat phase diagram software are shown in Table 1:

[0083] Table 1 Simulation parameters of Mg-6wt%Gd obtained by Pandat phase diagram software

[0084] parameter Logo Numerical Melting point of magnesium <![CDATA[T m ]]> 921K Liquidus slope m <![CDATA[3.0Kwt% -1 ]]> Solute partition coefficient k 0.35 Initial concentration <![CDATA[C0]]> 6.0wt.% Solute diffusion coefficient D 1400 Gibbs-Thomson coefficient Γ 0.37K

[0085] In the process of constructing the model, the order parameter is introduced, and the change of the order parameter represents the movement process of the solid-liquid interface;

[0086] Before simulation calculation, each grid in the calculation area is assigned an initial value;

[0087] (2) Construct a macroscopic model. The molten pool of traditional arc welding can be regarded as a combination of two semi-ellipsoids. During the welding process, the solidification area of ​​the molten pool is a quarter ellipse. Based on the above assumptions, a macroscopic heat transfer and growth rate model is established. The equation of the semi-ellipsoid in the solidification state is:

[0088]

[0089] Among them, l a is the length of the second half of the molten pool, l b is the depth of the weld pool, the x-axis is the forward direction of welding, and the y-axis is the vertical direction;

[0090] Assuming that the angle between the crystallization direction and the welding direction at any point on the fusion line is θ, during the laser welding process, the welding pool moves at a constant speed following the laser, while the advancement speed of the solid / liquid interface V s (t) is consistent with the welding speed in the normal direction of the solid / liquid interface and is expressed as:

[0091] V s (t) = Vcosθ;

[0092] (3) A phase field model was constructed. Based on the Ginzburg-Landau theory, a mathematical model suitable for simulating the CET transition in the welding pool was established. To improve the computational efficiency, the interface width of the diffusion interface was defined as several orders of magnitude multiples of the actual interface thickness. The influence of the latent heat of crystallization was ignored, and the temperature field control equation was defined as:

[0093]

[0094] Where T(Z,t) is the temperature field distribution, Z is the coordinate parallel to the dendrite growth direction, t is the solidification time, T0=T(Z 0,0 ) is the reference temperature, G(t) is the temperature gradient that varies with time, and Vp(t) is the interface advancement velocity that varies with time.

[0095] G is the maximum temperature gradient of the solid-liquid interface during the crystallization process of the welding pool, and its expression is:

[0096]

[0097] Where t is the solidification time, T c is the temperature at the center of the weld pool, T s is the crystallization temperature, x(t), y(t) are the positions of the solid / liquid interface relative to the center of the molten pool;

[0098] In order to more accurately describe the evolution process of columnar crystals to equiaxed crystals and make the model more precise, it is necessary to add a nucleation model, which is expressed as follows:

[0099]

[0100]

[0101] Where s is the degree of supercooling, ρ max is the maximum nucleation density, s σ is the standard deviation of supercooling, s ρ is the degree of supercooling of nucleation.

[0102] An order parameter ξ is introduced into the established model. During the solidification process, ξ = 1 represents the solid phase, and ξ = -1 represents the liquid phase. ξ is a continuous function whose value continuously changes from -1 to 1. The solute concentration of the solute field is expressed by a supersaturation field U:

[0103]

[0104] Where U is a supersaturated field, k is the solute distribution coefficient, c is the solute solubility distribution, c ∞ It is the equilibrium solubility in the liquid phase away from the solid-liquid interface.

[0105] The phase field equation including the phase field parameter ξ is as follows:

[0106]

[0107] in, is the dimensionless form of T(z), W is the interface width, τ0 is the relaxation time parameter, which links W and τ0 through the coupling parameter λ, eliminating the interface dynamic parameters under arbitrary temperature and orientation conditions; the expression of τ0 is as follows:

[0108] τ0=a2λW 2 / D

[0109]

[0110] Where d0 is the chemical capillary length, Γ is the Gibbs-Thomson coefficient, and a1 and a2 are constants. a1 is 0.8839, and a2 is 0.6267.

[0111] The solute field equation established is as follows:

[0112]

[0113] Where D is the diffusion coefficient of the solute in the liquid phase.

[0114] (4) Calculate the phase field model. The solidification of the welding pool is a dynamic process. In order to ensure the reliability of the simulation results, the temperature gradient and dendrite growth rate are introduced into the model, and the macro-micro coupled phase field model is calculated to obtain the simulation results of the CET transformation of the welding pool microstructure. Specifically, it includes the following steps: First, the temperature gradient and dendrite growth rate calculated in step (2) are brought into the phase field model in step (3) for simulation, and the introduced non-uniform nucleation model is solved; the solute field calculation results, temperature field and growth rate results are calculated in step (3), and the phase field parameter changes are solved; the above calculation process will be performed once at each time step until the calculation is completed. Finally, a computer program is written based on the above coupled phase field model to obtain and derive the CET transformation results. Among them, the molten pool morphology in this embodiment is as follows Figure 1 As shown, the temperature field of the molten pool is Figure 2 As shown in the figure, the CET transformation simulation results in the Mg-6wt%Gd alloy molten pool are as follows: Figure 3 The CET transformation simulation method of the present invention well reveals the variation law of the alloy's microstructure, and provides theoretical support and scientific basis for improving the mechanical properties of welds.

[0115] The present invention helps to optimize the welding process of magnesium alloys in the shell, bracket and other aspects during the manufacture of lightweight automobiles, improve the mechanical properties of the welds, and promote the industrial development process of lightweight automobiles.

[0116] The numerical simulation method provided by the present invention can dynamically reproduce the change process of columnar crystals to equiaxed crystals during the welding process of alloys, especially magnesium alloys, which helps to deepen the understanding of the evolution process of alloy welding microstructure and lays the foundation for the study of microstructure evolution and optimization of welding process.

[0117] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics, characterized by: The steps include: (1) Initialization of simulation conditions: First, the model is initialized by constructing the real thermodynamic data of the alloy according to the thermodynamic calculation software. Then, the conditions are simplified and the model is constructed according to the parameters of the welding pool solidification process. (2) Construct a macroscopic model, assuming that the solidification area of ​​the weld pool is one-quarter of the ellipse, and establish a macroscopic heat transfer and growth model based on this assumption; (3) Construct a phase field model. Based on the Ginzburg-Landau theory, a phase field model is established to simulate the CET transformation in the welding pool. A nucleation model is introduced to describe the evolution process of columnar crystals to equiaxed crystals. Its expression is: ； ； in, is the supercooling, is the maximum nucleation density, is the standard deviation of subcooling, is the degree of supercooling of nucleation; when When the crystal form changes from columnar crystal to equiaxed crystal, a random number is introduced as a constraint to determine the nucleation site. If When the value is greater than the random number, nucleation occurs, wherein the random number is between 0 and 1; the finite difference method is used to solve it after applying boundary conditions; Introducing order parameters to characterize physical states ,in, represents the liquid phase, represents the solid phase, Continuously changes between solid and liquid phases; contains order parameters The phase field equation is as follows: ； in, yes After dimensionless processing, W is the interface width, , is the relaxation time parameter, W and By coupling parameters By linking them together, the interface dynamic parameters under arbitrary temperature and orientation conditions are eliminated; ； The solute concentration field is expressed by introducing the dimensionless supersaturation field U: ； Among them, k is the solute distribution coefficient, c is the solute solubility distribution, is the equilibrium solubility in the liquid phase away from the solid-liquid interface; (4) Calculate the phase field model. Introduce the dendrite growth rate and temperature gradient calculated in step (2) into the above phase field model, then introduce the nucleation model, solve the above nucleation model using the finite difference method, and calculate the macro-micro coupled phase field model.

2. The CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics according to claim 1 is characterized in that: In step (1), the following assumptions are made in the process of building the model: ① Assume that the shape of the weld pool does not change during the laser welding process; ② Ignore the effect of liquid flow inside the welding pool on temperature and solute distribution; ③ The temperature in the welding pool is distributed linearly with a gradient.

3. The CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics according to claim 2 is characterized in that: In step (1), the alloy phase diagram generated by the Pandat phase diagram software is used to calculate the solute distribution coefficient k and the liquidus slope m of the alloy; based on the thermodynamic database of the Pandat phase diagram software, the parameters required for the alloy phase field are obtained.

4. The CET transformation simulation method in a lightweight magnesium alloy welding pool for automobiles based on phase field dynamics according to any one of claims 1 to 3, characterized in that: In step (1), the simplified conditions include defining the temperature field equation, order parameter, and solute concentration field equation.

5. The CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics according to claim 1 is characterized in that: In step (2), the equation of the semi-ellipse of the solidification area of ​​the welding pool is: ； in, The length of the second half of the molten pool, is the melt pool depth, The forward direction of axis welding, the y-axis is the vertical direction; Assume that the angle between the crystallization direction and the welding direction at any point on the fusion line is During the laser welding process, the molten pool moves at a constant speed following the laser, while the advancement speed of the solid / liquid interface The welding speed is consistent with the normal direction speed at the solid / liquid interface and is expressed as: ； Where V is the welding speed.

6. The CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics according to claim 1 is characterized in that: In step (3), the interface width of the diffusion interface is defined as several orders of magnitude multiples of the actual interface thickness in the phase field model. At the same time, the influence of the latent heat of crystallization is ignored, and the welding pool temperature field T(z) equation is defined as: ； Where z is the coordinate parallel to the dendrite growth direction, is the temperature of the reference point, is the solute concentration in the liquid phase, is the length of the solidification interval, is the dimensionless temperature, is the liquidus slope, G is the maximum temperature gradient of the solid / liquid interface, and its expression is: ； Where t is the solidification time, is the temperature at the center of the weld pool, is the crystallization temperature, is the position of the solid / liquid interface relative to the center of the molten pool.

7. Application of the CET transformation simulation method in a lightweight automotive magnesium alloy welding molten pool based on phase field dynamics according to any one of claims 1 to 3, characterized in that: This phase field dynamics-based CET transformation simulation method in the molten pool of lightweight automotive magnesium alloy welding is used to simulate the welding of lightweight automotive magnesium alloys.

8. The application of the CET transformation simulation method in the welding pool of lightweight magnesium alloy for automobiles based on phase field dynamics according to claim 7 is characterized in that: This simulation method is used to simulate the evolution of columnar crystals to equiaxed crystals during the welding process of lightweight automotive magnesium alloys.

Images