Molten pool dynamics prediction method in aluminum alloy laser welding process

Abstract

The invention discloses a molten pool dynamics prediction method in an aluminum alloy laser welding process, which comprises the following steps of: S1, establishing a physical model in a swinging laser welding process, and establishing three control equations to obtain mass, momentum and energy source items to be solved; s2, establishing a multi-reflection model of a laser beam on a gas-liquid interface, and simulating quality and energy source items generated in processing reflection; s3, establishing an evaporation-condensation model, and simulating an energy source item caused by phase change; s4, capturing and reconstructing a gas-liquid interface by adopting THINC-LS, and coupling the source items into a control equation; and S5, a gas-liquid two-phase fluid grid model is constructed and divided, and a control equation is discretized and iteratively solved. According to the method, reasonable physical and mathematical models are constructed, numerical simulation is conducted on molten pool dynamics in the laser beam vibration-assisted laser welding process, heat transfer and flow behaviors of a welding molten pool are accurately reproduced, the mechanism and the influence rule of light beam swing parameters are disclosed, and therefore quantitative prediction of welding joint forming is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of numerical simulation of advanced laser welding processes, and in particular relates to a method for predicting molten pool dynamics in an aluminum alloy laser welding process in a clockwise circular oscillation mode of a laser beam. Background Art

[0002] Laser deep penetration welding shows great potential in processing aluminum alloy, a material with high reflectivity and high thermal conductivity. Its advantages include high welding efficiency, small heat-affected zone, and fine grain size. In recent years, aluminum alloy laser welding technology has gradually been applied in the aerospace and automotive industries, and has successfully solved the connection problem of large structural parts with a thickness of less than 5 mm.

[0003] For aluminum alloy medium and thick plate components with a thickness of more than 5mm, there is still a large gap between their forming and actual production standards due to the influence of the physical properties of the material and the process conditions. First, there is a violent liquid metal convection near the surface of the molten pool during the welding process, and the dynamic stability of the molten pool is poor, resulting in serious defects such as welding spatter; during the laser deep melting welding process, the laser beam forms a keyhole in the high-temperature molten pool formed on the surface of the material. When the welding process parameters are too large or too small, the keyhole may become unstable, causing it to collapse, thereby forming pores. The formation of pores not only affects the density of the weld, but also reduces the mechanical properties of the welded joint, and may even cause the weld to fail.

[0004] Laser beam vibration-assisted laser welding technology is based on the development of laser welding technology. It introduces a swinging laser beam (non-linear) to optimize the dynamic behavior of the molten pool and solve some challenges in traditional laser welding. Its flexibility, high efficiency and cost-effectiveness give it significant advantages in improving welding quality and efficiency, and it has shown broad prospects in various industrial applications. In recent years, laser beam vibration-assisted laser welding technology has attracted a lot of attention from scholars. However, due to the large number of processing parameters, strong interactions, and poor real-time dynamic response in the swinging laser welding process, it is difficult to accurately and quantitatively describe the mechanism and influence of the beam swing parameters using experimental testing methods.

[0005] In the prior art, the heat flux simulation of aluminum alloy laser welding in the clockwise circular swing mode of the laser beam mainly has the following problems: ① The simplified treatment of complex physical phenomena in the model (such as turbulence, evaporation and plasma effects in the molten pool) may cause the simulation results to be inconsistent with the actual situation; ② The temperature dependence of the material's thermophysical properties and the coupling relationship with the actual process conditions are difficult to accurately characterize, resulting in insufficient accuracy of the simulation in predicting the weld microstructure and welding defects; ③ The existing models usually use Gaussian distribution or double ellipsoid model to describe the heating effect of the laser beam on the molten pool during the swinging process, which fails to accurately reflect the interaction between the laser and the material at different positions and angles (including reflection, refraction, and absorption). Summary of the invention

[0006] In view of the above-mentioned defects, the present invention provides a method for predicting the molten pool dynamics in the aluminum alloy laser welding process. By constructing a reasonable physical and mathematical model, the molten pool dynamics in the laser beam vibration-assisted laser welding process is numerically simulated, the heat transfer and flow behavior of the welding molten pool are accurately reproduced, and the mechanism and influence of the beam swing parameters are revealed, thereby achieving quantitative prediction of the welding joint formation.

[0007] A method for predicting molten pool dynamics in aluminum alloy laser welding process is based on aluminum alloy beam swing laser welding to analyze molten pool heat transfer, flow and phase change behavior, and is characterized by comprising the following steps:

[0008] Step 1, establish a physical model of the swing laser welding process, and establish the control equations of the three-dimensional incompressible heat-flow model: mass conservation equation, momentum conservation equation and energy conservation equation, and obtain the mass source term, momentum source term and energy source term to be solved; Step 2, establish a multiple reflection model of the laser beam at the gas-liquid interface to simulate the momentum and energy source terms generated in the processing reflection; Step 3, establish the energy source term caused by the evaporation-condensation phase change, simulate the mass and energy source terms generated by the gas-liquid two-phase phase change, and couple the momentum source term, mass source term and energy source term into the control equation in step 1; Step 4, use THINC-LS to capture and reconstruct the gas-liquid interface to determine the interface; Step 5, construct a gas-liquid two-phase fluid mesh model based on the Hypermesh software pre-processing module and perform meshing, and then solve it based on the commercial fluid mechanics simulation software ANSYSFluent: define initial conditions and boundary conditions, load material thermophysical performance parameters and welding process parameters, use the finite volume method to discretize the control equations, and use the PISO algorithm to iteratively solve.

[0009] Preferably, in step 1, based on the mathematical model of the beam swing trajectory and combined with the characteristics of the laser welding process, an assumption is made on the dynamic physical model of the laser welding process in the clockwise circular laser beam swing mode, and the physical model is as follows: a laser beam composed of a finite number of beams is pointed vertically to the workpiece surface, the spot size is fixed, and the sub-beam follows multiple mirror reflections at the liquid-gas interface.

[0010] Preferably, the physical model is simplified: the physical model does not consider the shielding effect of the shielding gas flow on the laser energy, and the inverse bremsstrahlung absorption effect is ignored; the gas-liquid conversion phenomenon follows the Lee model; the mixture of metal vapor and shielding gas is simplified to a pure argon phase; the plume heating effect around the keyhole opening is considered by using an additional heat source; and the friction effect caused by the plume eruption is ignored.

[0011] Preferably, in step 1, the clockwise circular laser beam swing affects the distribution and superposition of the laser by changing the beam position. The distribution of the laser energy along the x-axis and the y-axis conforms to the two-dimensional Gaussian distribution on the cross section. The mathematical expression of the laser energy is:

[0012]

[0013] Rayleigh scattering and Fresnel absorption of the source term reflected in the energy conservation equation;

[0014] The trajectory equation of the beam center (x(t), y(t)) in Cartesian coordinate form is:

[0015]

[0016] In the formula, k0, P(t), d, x, y, x(t), y(t), v f , A, and f represent energy absorption coefficient, laser power, beam diameter, abscissa of any position on the workpiece surface, ordinate of any position on the workpiece surface, abscissa of the beam motion trajectory, ordinate of the beam motion trajectory, feed speed, swing amplitude, and swing frequency, respectively.

[0017] Preferably, in step 1, the laser beam generates mass, energy and momentum source terms in the multiple reflection process. The three conservation equations considering the energy and momentum source terms are as follows:

[0018] The mass conservation equation:

[0019]

[0020] Where ρ is the fluid density, is the velocity field, t is the time;

[0021] Momentum conservation equation:

[0022]

[0023] Where p is pressure, η l is the fluid viscosity, is the momentum source term. The right side of the momentum source term equal sign from left to right is: gravity, buoyancy, mushy zone resistance, surface tension, and recoil pressure;

[0024] is the gravitational acceleration, β is the thermal expansion coefficient, T is the temperature, T l is the liquidus temperature, K0 is the permeability coefficient, α l is the liquid volume fraction, c is a constant coefficient, is the initial velocity field;

[0025] Energy conservation equation:

[0026]

[0027] h=C p T+α l L m

[0028] S h =Q Fa -Q evap +Q cond

[0029]

[0030] Where h is the mixing enthalpy of solid-liquid phase change, k is the thermal conductivity, S h is the energy source term, C p is the specific heat capacity, Q Fa is the absorbed laser energy, Q evap is the evaporation loss energy, Q cond Release energy for condensation; Q Rs is the Rayleigh scattering energy, Q Fa is the Fresnel energy absorption, α Rs and α Fa are the Rayleigh scattering and Fresnel absorption coefficients, respectively, q t-1,n is the laser energy density before the tth reflection, nb and nr are the number of sub-beams and the number of multiple reflections, θ are the unit vector of the incident beam, the unit normal vector of the free interface, and the incident angle of the beam.

[0031] Preferably, in step 3, the gas-liquid phase transition conforms to the Lee model, and the mass transfer in the gas-liquid system is controlled by the vapor transport equation:

[0032]

[0033] Among them, α v , v , They are: gas phase volume fraction, gas phase density, gas phase velocity; They are: the mass transfer rate per unit volume per unit time caused by evaporation and condensation; when the liquid phase temperature is greater than the saturation temperature, it is an evaporation process, otherwise it is a condensation process. The evaporation rates in the two cases are:

[0034]

[0035] The energy source term expression is:

[0036]

[0037] Among them, L lv and L cond Equal in magnitude and opposite in sign.

[0038] Preferably, in step 4, the interface tracking and reconstruction process involves coupling with the evaporation-condensation model and the momentum conservation equation, and the specific algorithm flow is: initialize the THINC function and the LS function before the iteration starts; in each iteration process, determine the interface position at each time step by alternately updating the interface position, and calculate the interface normal vector and curvature; calculate the mass transfer and heat exchange during the phase change process according to the Lee model, and update the VOF value and phase change rate; solve the momentum conservation equation according to the updated VOF value and interface position, update the velocity field and pressure field, and use the interface curvature κ calculated by the LS function as part of the interface tension term, and introduce it into the momentum conservation equation.

[0039] As a preferred method, the THINC function uses the hyperbolic tangent function to fit the discontinuous solution of the interface 0-1, and the LS function is the distance from any point x in space to the interface. The signed distance function of is:

[0040] THINC:

[0041] LS:

[0042] Where β is a grid-dependent constant that controls the width of the discontinuity / interface thickness;

[0043] The free interface is represented by φ(x, t) = 0 or H(x, t) = 0.5;

[0044] Assuming that the motion of the interface is completely dominated by convection, the equations of motion for the THINC function and the LS function are:

[0045]

[0046] Preferably, in step 5, the standard form of the control equation is discretized by using the finite volume method, and the standard form is:

[0047]

[0048] Among them, φ is the variable to be determined, x i is the coordinate distance, u i is the velocity field, Γ k is the generalized diffusion coefficient, S φ is the source term; in the equation is a non-steady-state term, is the diffusion term and is the convection term.

[0049] As a preferred method, the finite volume method is used to discretize the standard transport equation in time and space, using the second-order fully implicit discretization format First-order upwind format Central Difference Scheme Unsteady-state, convection and diffusion terms are handled, and source terms are linearized deal with.

[0050] The beneficial effects of the present invention are:

[0051] (1) The present invention achieves high-precision heat flow simulation of aluminum alloy laser welding process in clockwise circular swing mode by introducing accurate heat source model and dynamically coupled temperature field and flow field analysis. It can not only simulate the energy distribution and flow behavior in the molten pool more accurately, but also significantly improve the prediction accuracy of welding quality. By optimizing process parameters and reducing welding defects, the strength and reliability of welded joints can be significantly improved.

[0052] (2) The present invention constructs a reasonable physical and mathematical model to numerically simulate the molten pool dynamics during laser beam vibration-assisted laser welding, which can accurately reproduce the heat transfer and flow behavior of the welding molten pool, reveal the mechanism and influence of the beam swing parameters, thereby achieving quantitative prediction of the welding joint formation, and scientifically guiding the optimization and customization of the beam vibration-assisted laser welding process parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below.

[0054] Figure 1 It is a model framework and algorithm implementation flow chart of the swing laser welding molten pool dynamics simulation model of an embodiment of the present invention;

[0055] Figure 2 1. It is a schematic diagram comparing the calculation result of the molten pool morphology and the cross-sectional morphology of the weld according to an embodiment of the present invention;

[0056] Figure 3 It is a schematic diagram of the calculation results of the temperature field and phase field of aluminum alloy oscillating laser welding under the parameters of oscillation amplitude f=200 Hz and amplitude A=1.2 mm according to an embodiment of the present invention;

[0057] Figure 4 It is a schematic diagram of the calculation results of the temperature field and phase field of aluminum alloy oscillating laser welding under the parameters of oscillation amplitude f=250Hz and amplitude A=1.2mm according to an embodiment of the present invention;

[0058] Figure 5It is a schematic diagram of the calculation results of the temperature field and phase field of aluminum alloy oscillating laser welding under the parameters of oscillation amplitude f=200 Hz and amplitude A=1.5 mm according to an embodiment of the present invention;

[0059] Figure 6 It is a diagram of simulation calculation results of the molten pool velocity field according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] like Figures 1 to 6 As shown, the embodiment of the present invention provides a method for predicting the molten pool dynamics in the aluminum alloy laser welding process, which mainly implements two parts:

[0062] ① Accurately simulate beam energy distribution: Construct a beam tracing heat source model, discretize the laser beam into multiple rays, track the reflection, refraction and absorption process of each ray on the material surface, and calculate its energy distribution at each point. As the beam swings clockwise, the model updates the incident angle and position of each ray in real time to accurately predict the dynamic distribution of heat in the molten pool.

[0063] ② Comprehensive simulation of multiple physical fields: The laser welding process involves the comprehensive effects of multiple physical fields such as heat conduction, fluid flow, phase change (melting, evaporation), etc. Multiple reflections and evaporation-condensation phase change are important physical behaviors of the welding molten pool, and their models determine the calculation accuracy. Multiple reflections are used to calculate and capture the gas-liquid interface, and this process does not generate source terms; evaporation-condensation phase change generates mass and energy source terms. This patent aims to solve how to effectively integrate these physical phenomena into a unified simulation framework, thereby improving the overall accuracy and reliability of the simulation.

[0064] Specifically, the steps include:

[0065] Step 1: Establish a mathematical model of the beam swing trajectory. Combined with the characteristics of the laser welding process, make reasonable assumptions and appropriately simplify the dynamic physical model of the laser welding process in the clockwise swing mode of the beam; establish the fluid domain 6061-T6 and gas domain plasma material model according to relevant literature; determine the clockwise circular laser beam swing welding process, including: laser power P, beam diameter d, welding speed v f , swing frequency f, swing amplitude A, etc., and write a subroutine.

[0066] The simplifications of the physical model include: the liquid phase is an incompressible viscous Newton fluid, and only laminar motion is considered; the laser beam composed of a finite number of beams is pointed vertically to the workpiece surface, the spot size is fixed, and the sub-beams follow multiple mirror reflections at the liquid-gas interface; the shielding effect of the shielding gas flow on the laser energy is not considered, and the inverse bremsstrahlung absorption effect is negligible; the mixture of metal vapor and shielding gas is simplified to a pure argon phase; the plume heating effect around the keyhole opening is considered by using an additional heat source; and the friction effect caused by the plume eruption is negligible.

[0067] The mathematical expression of laser energy that conforms to Gaussian distribution is:

[0068]

[0069] The trajectory equation of the beam center (x(t), y(t)) is (in Cartesian coordinate form):

[0070]

[0071] In this embodiment, the spot radius is 0.24 mm, and the welding process parameters of the experiment and simulation are shown in Table 1.

[0072] Table 1 Swing welding process parameters

[0073]

[0074] Thermophysical properties of 6061-T6 aluminum alloy and protective gas (Argon) are shown in Table 2:

[0075] Table 2 Thermophysical performance parameter values ​​of 6061-T6 and gas phase

[0076]

[0077]

[0078] The number of sub-laser beams is determined based on the diameter d of the laser beam and the grid size dx / dy is 36. The multiple reflection process generates mass, energy and momentum source terms. Among them, the mass source term includes: mass transfer in the evaporation and condensation process; the energy source term includes: Rayleigh scattering, Fresnel absorption, phase change heat; the momentum source term includes: recoil pressure, Marangoni force, buoyancy, hydrostatic pressure, etc. The three conservation equations considering energy and momentum source terms are as follows:

[0079] The mass conservation equation:

[0080]

[0081] Momentum conservation equation:

[0082]

[0083] Energy conservation equation:

[0084]

[0085] h=C p T+α l L m

[0086] S h =Q Fa -Q evap +Q cond

[0087]

[0088] S2: Establish a multiple reflection model (MRM) of the laser beam at the gas-liquid interface, determine the mass and energy source terms in the energy conservation and momentum conservation equations of the machining process, and write a subroutine.

[0089] S3: Establish the energy source term caused by the evaporation-condensation phase change, and simulate the source term generated by the gas-liquid two-phase phase change involved in the evaporation-condensation process. The gas-liquid conversion phenomenon follows the Lee model. In this embodiment, we set the relaxation time of evaporation and condensation to 0.05. The calculation results of the Lee model will further adjust the interface position and update the momentum and energy field.

[0090] S4: Establish a model for capturing and reconstructing the free interface of the gas-liquid two-phase flow process (THINC-LS) and write a subroutine. THINC-LS is used to capture and reconstruct the gas-liquid interface, and the energy and momentum source terms are coupled into the control equations in step 1. The interface tracking and reconstruction process involves coupling with the evaporation condensation model and the Navier-Stokes equations (momentum conservation). The specific algorithm flow is as follows: initialize the THINC function and LS function before the iteration starts; in each iteration process, the interface position is updated alternately to determine the interface position at each time step, and the interface normal vector and curvature are calculated; calculate the mass transfer and heat exchange during the phase change process according to the Lee model, and update the VOF value and phase change rate; solve the Navier-Stokes equations according to the updated VOF value and interface position, update the velocity field and pressure field, and use the interface curvature κ calculated by the LS function as part of the interface tension term, which is introduced into the Navier-Stokes equations.

[0091] S5: Based on the Hypermesh software pre-processing module, a gas-liquid two-phase fluid mesh model is constructed and meshed, initial conditions and boundary conditions are defined, material thermophysical performance parameters and welding process parameters are loaded, the control equation is discretized using the finite volume method, and the PISO algorithm is used for iterative solution. Specifically,

[0092] The fluid mesh is established based on the commercial software Hypermesh. This process includes creating a computational domain, generating a mesh, marking boundary conditions, and finally exporting a mesh file. The computational domain size is 6.64*6.64*6.8mm 3 , divide the computational domain into two layers, the upper layer is 0.8 mm thick, representing the gas phase, the unit size is 80 μm, and the number of grids is 585565; create a group and name it wall, mark and assign all wall grids, create a group and name it outlet, mark and assign all outlet grids; export the grid model after the above operations to an .msh format file that can be recognized by ANSYS Fluent.

[0093] Import the .msh mesh file into the ANSYS Fluent solver, select single precision in the startup window, check whether the mesh is imported correctly, and ensure that the wall and outlet boundary conditions are correctly marked; load the S1, S2, and S4 subroutines; set the initial temperature, velocity, and pressure, and select Standard Initialization for initialization; set the boundary conditions of the wall, define it as an adiabatic wall or specify boundary conditions such as temperature and velocity, set the boundary conditions of the outlet, define it as a pressure outlet, and specify the outlet pressure value; use FVM to discretize the standard form of the three major conservation equations (mass conservation equation, momentum conservation equation, and energy conservation equation), and use the PISO algorithm to decouple the pressure-velocity calculation; set the residual to 10 -6 .

[0094] In this embodiment, the calculation results of the molten pool contour are extracted and compared with the actual weld cross-sectional morphology to verify the rationality of the coupling model and analyze the influence mechanism of the oscillation frequency and amplitude on the heat transfer flow and phase interface evolution behavior of the molten pool.

[0095] The cross-sectional morphology of the weld is extracted and compared with the molten pool profile obtained by simulation.

[0096] Figure 1For comparison results on the same scale, it can be seen that the calculated weld shape characteristics and dimensions are in good agreement with the actual results. The weld width deviation ranges from 2.0% to 4.2%, and the maximum penetration deviation ranges from 2.2% to 2.8%. These data provide relatively sufficient verification for the rationality and accuracy of the simulation using the proposed numerical model, and the errors are largely attributed to the assumptions and simplifications of the physical field and material parameters.

[0097] Figure 1 The 6061-T6 swing welding temperature and phase interface distribution obtained by simulation based on the model of the present invention are shown in the figure below. The simulation results of process parameters #1, #2, and #3 correspond to Figure 3-Figure 5 .

[0098] It can be seen that as the oscillation cycle increases, the total heat input increases, and the molten width and depth increase and tend to stabilize. Unlike the "nail-shaped" molten pool of conventional laser welding, the weld morphology of oscillating laser welding changes significantly: the molten width of the oscillating welding molten pool increases, the molten depth decreases, and the aspect ratio decreases; the molten pool dynamics of oscillating laser welding is more complex and dynamic. Due to the oscillation of the laser beam, the temperature distribution in the molten pool is more uniform, and the flow of liquid metal is more strongly driven, forming complex flow patterns such as eddy currents and circulating flows. At the same time, oscillating laser welding enhances the convection effect of the molten pool, which helps to optimize the weld morphology, reduce defects, and improve the uniformity and mechanical properties of the weld.

[0099] contrast Figure 3 and Figure 4 , it can be found that in the process of swing laser welding, the increase of swing frequency can significantly affect the morphology of the molten pool. A higher swing frequency can improve the shape of the molten pool, making it more symmetrical and smooth. This is because more frequent swinging helps to evenly distribute heat and improve the flow inside the molten pool, thereby reducing the irregular shape and surface defects of the molten pool. In addition, in swing laser welding, an increase in swing frequency usually leads to a decrease in the size of the molten pool. A higher swing frequency allows the laser beam to cover the molten pool area more frequently per unit time, thereby improving the heat distribution efficiency of the molten pool and promoting rapid cooling within the molten pool. This effect helps to control the size of the molten pool, making it more compact and stable. The increase in swing frequency has a significant effect on the molten pool dynamics. As the swing frequency increases, the temperature field and flow field of the molten pool change. A higher frequency can improve the mixing effect of the molten pool, improve the symmetry and uniformity of the molten pool, and help reduce defects in the weld, such as pores and inclusions. At the same time, high-frequency swinging can promote heat convection in the molten pool, making the temperature distribution of the molten pool more uniform, thereby improving the mechanical properties of the welded joint.

[0100] contrast Figure 3 and Figure 5, it can be found that in wobble laser welding, an increase in the swing amplitude leads to an expansion of the molten pool size. A larger amplitude allows the laser beam to cover a wider area during welding, thereby increasing the diameter and area of ​​the molten pool. This enlargement effect helps to increase the heat input and melting range of the molten pool, improving the fusion and filling effect of the weld. In wobble laser welding, an increase in the swing amplitude can significantly affect the dynamics of the molten pool. A larger amplitude leads to a larger range of movement of the laser beam on the surface of the molten pool, thereby enhancing the convection and mixing effects within the molten pool. This enhanced mixing action helps to evenly distribute heat and reduce temperature gradients in the molten pool, improving the fluidity and heat transfer of the molten pool.

[0101] Figure 6 The simulation results of the velocity field under process parameters #1 show that the velocity field of the molten pool in swing laser welding shows a more uniform flow characteristic compared with conventional laser welding. In conventional laser welding, the fixed laser beam causes the velocity field of the molten pool to be concentrated in the center of the weld, and the flow is uneven; swing laser welding brings periodic changes and additional disturbances through the circular swing of the laser beam, which helps to enhance the overall convection effect of the molten pool and improve the mixing inside the molten pool, thereby making the velocity field more uniform, reducing the temperature difference between the center and edge of the molten pool, and improving the density and consistency of the welded joint.

[0102] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for predicting the molten pool dynamics during aluminum alloy laser welding, based on the aluminum alloy beam swing laser welding, carries out the analysis of the molten pool heat transfer, flow and phase change behavior, characterized in that: The following steps are involved: Step 1, establish a physical model of the swing laser welding process, and establish the control equations of the three-dimensional incompressible heat-flow model: mass conservation equation, momentum conservation equation and energy conservation equation, and obtain the mass source term, momentum source term and energy source term to be solved; Step 2, establish a multiple reflection model of the laser beam at the gas-liquid interface to simulate the momentum and energy source terms generated in the processing reflection; Step 3, establish the energy source term caused by the evaporation-condensation phase change, simulate the mass and energy source terms generated by the gas-liquid two-phase phase change, and couple the momentum source term, mass source term and energy source term into the control equation in step 1; Step 4, capture and reconstruct the gas-liquid interface using THINC-LS to determine the interface; Step 5, based on the Hypermesh software pre-processing module, a gas-liquid two-phase fluid mesh model is constructed and meshed, and then the solution is performed based on the commercial fluid mechanics simulation software ANSYS Fluent: initial conditions and boundary conditions are defined, material thermophysical performance parameters and welding process parameters are loaded, the control equations are discretized using the finite volume method, and the PISO algorithm is used for iterative solution.

2. The method according to claim 1, characterized in that In step 1, based on the mathematical model of the beam swing trajectory and combined with the characteristics of the laser welding process, an assumption is made on the dynamic physical model of the laser welding process in the clockwise circular laser beam swing mode. The physical model is: a laser beam composed of a finite number of beams is pointed vertically to the workpiece surface, the spot size is fixed, and the sub-beam follows multiple mirror reflections at the liquid-gas interface.

3. The method according to claim 1, characterized in that The physical model is simplified: the shielding effect of the shielding gas flow on the laser energy is not considered in the physical model, and the inverse bremsstrahlung absorption effect is ignored; the gas-liquid conversion phenomenon follows the Lee model; the mixture of metal vapor and shielding gas is simplified to a pure argon phase; the plume heating effect around the keyhole opening is considered by using an additional heat source; and the friction effect caused by the plume eruption is ignored.

4. The method according to claim 1, characterized in that: In step 1, the clockwise circular laser beam swing affects the distribution and superposition of the laser by changing the beam position. The distribution of laser energy along the x-axis and y-axis conforms to the two-dimensional Gaussian distribution on the cross section. The mathematical expression of laser energy is: Rayleigh scattering and Fresnel absorption of the source term reflected in the energy conservation equation; The trajectory equation of the beam center (x(t), y(t)) in Cartesian coordinate form is: In the formula, k0, P(t), d, x, y, x(t), y(t), v f , A, and f represent energy absorption coefficient, laser power, beam diameter, abscissa of any position on the workpiece surface, ordinate of any position on the workpiece surface, abscissa of the beam motion trajectory, ordinate of the beam motion trajectory, feed speed, swing amplitude, and swing frequency, respectively.

5. The method according to claim 1, characterized in that In step 1, the laser beam generates mass, energy and momentum source terms in the multiple reflection process. The three conservation equations considering the energy and momentum source terms are as follows: The mass conservation equation: Where ρ is the fluid density, is the velocity field, t is the time; Momentum conservation equation: Where p is pressure, η l is the fluid viscosity, is the momentum source term. The right side of the momentum source term equal sign from left to right is: gravity, buoyancy, mushy zone resistance, surface tension, and recoil pressure; is the gravitational acceleration, β is the thermal expansion coefficient, T is the temperature, T l is the liquidus temperature, K0 is the permeability coefficient, α l is the liquid volume fraction, c is a constant coefficient, is the initial velocity field; Energy conservation equation: h=C p T+α l L m S h =Q Fa -Q evap +Q cond Where h is the mixing enthalpy of solid-liquid phase change, k is the thermal conductivity, S h is the energy source term, C p is the specific heat capacity, Q Fa is the absorbed laser energy, Q evap is the evaporation loss energy, Q cond Release energy for condensation; Q Rs is the Rayleigh scattering energy, Q Fa is the Fresnel energy absorption, α Rs and α Fa are Rayleigh scattering and Fresnel absorption coefficient, respectively, q t-1,n is the laser energy density before the tth reflection, nb and nr are the number of sub-beams and the number of multiple reflections, θ are the incident beam unit vector, the unit normal vector of the free interface, and the beam incident angle.

6. The method according to claim 1, characterized in that In step 3, the gas-liquid phase transition conforms to the Lee model, and the mass transfer in the gas-liquid system is controlled by the vapor transport equation: Among them, α v , v , They are: gas phase volume fraction, gas phase density, gas phase velocity; They are: the mass transfer rate per unit volume per unit time caused by evaporation and condensation; when the liquid phase temperature is greater than the saturation temperature, it is an evaporation process, otherwise it is a condensation process. The evaporation rates in the two cases are: The energy source term expression is: Among them, L lv and L cond Equal in magnitude and opposite in sign.

7. The method according to claim 1, characterized in that In step 4, the interface tracking and reconstruction process involves coupling with the evaporation-condensation model and the momentum conservation equation. The specific algorithm flow is as follows: initialize the THINC function and LS function before the iteration starts; in each iteration process, determine the interface position at each time step by alternately updating the interface position, and calculate the interface normal vector and curvature; calculate the mass transfer and heat exchange during the phase change process according to the Lee model, and update the VOF value and phase change rate; solve the momentum conservation equation according to the updated VOF value and interface position, update the velocity field and pressure field, and use the interface curvature k calculated by the LS function as part of the interface tension term and introduce it into the momentum conservation equation.

8. The method according to claim 7, characterized in that THINC function uses hyperbolic tangent function to fit the interface 0-1 The discontinuous solution of LS function is the distance from any point x in space to the interface. The signed distance function of is: THINK: LS: Where β is a grid-dependent constant that controls the width of the discontinuity / interface thickness; The free interface is represented by φ(x, t) = 0 or H(x, t) = 0.5; Assuming that the motion of the interface is completely dominated by convection, the equations of motion for the THINC function and the LS function are:

9. The method according to any one of claims 1 to 8, characterized in that: In step 5, the standard form of the control equation is discretized using the finite volume method, and the standard form is: Among them, φ is the variable to be determined, x i is the coordinate distance, u i is the velocity field, Γ k is the generalized diffusion coefficient, S φ is the source term; in the equation is a non-steady-state term, is the diffusion term and is the convection term.

10. The method according to claim 9, characterized in that The finite volume method is used to discretize the standard transport equation in time and space, using the second-order fully implicit discretization scheme First-order upwind format Central Difference Scheme Unsteady-state, convection and diffusion terms are handled, and source terms are linearized deal with.

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