A laser in-situ welding method and system for SiC particle-reinforced aluminum matrix composites and its modeling.

Abstract

This invention belongs to the field of laser in-situ welding technology and discloses a laser in-situ welding method for SiC particle-reinforced aluminum matrix composites and its modeling method. The method includes: establishing a laser heat source model considering the differences in optical properties of the molten particle surface; establishing a multiphase flow model based on magnetohydrodynamics; and developing a particle migration-heat transfer model based on Discrete Element Model (DEM). The method describes the particle contact force and deformation relationship based on Hertzian contact theory, obtains the contact thermal conductivity of SiC particles using experimental methods, and uses the Discrete Element Model (DEM) method to achieve dynamic tracking of contact and heat transfer; and integrates multi-energy field multiphase coupling modeling of the molten pool, keyhole, and particles. This invention provides a more accurate description of welding thermal behavior: the numerical simulation model established in this invention considers for the first time the differences in optical behavior such as laser absorption, scattering, and reflection between the fluid and the SiC particle surface, making the characterization of energy transport behavior and temperature evolution during the welding process more accurate.

Description

Technical Field

[0001] This invention belongs to, but is not limited to, the field of laser in-situ welding technology, and particularly relates to a laser in-situ welding method for SiC particle-reinforced aluminum matrix composites and its modeling method. Background Technology

[0002] SiC particle-reinforced aluminum matrix composites (hereinafter referred to as SiCp / Al) combine the lightweight and thermal conductivity of aluminum with the high hardness / strength and high-temperature stability of SiC, resulting in superior performance in mechanical, thermal, and corrosion aspects. They are a crucial component of load-bearing structures for high-speed aerospace vehicles. Welding is a critical process in SiCp / Al manufacturing, with complex weld structures and lengths reaching several meters. The welding process easily forms brittle phases, leading to the destruction of the functionally graded structure, placing stringent demands on welding technology in terms of both quality and efficiency. With the continuous maturation of technology and the gradual reduction in costs, fiber laser technology has begun to be applied to SiCp / Al welding manufacturing. However, under the action of a high-energy laser beam, SiC and Al melt / vaporize, forming a molten pool and keyhole, causing: ① SiC particle burn-off and loss at the joint; ② SiC phase segregation at the joint; ③ Chemical reaction between SiC and Al, forming brittle carbides. Ultimately, this leads to a significant reduction in the mechanical properties of SiCp / Al joints. For a long time, researchers have reduced SiC particle decomposition and the formation of brittle phases by optimizing process parameters such as splicing gap, laser power, speed, and scanning trajectory / frequency, as well as adding alloying elements (such as Zr and Ti), thus improving the problem of uneven SiC distribution in the joint. However, studies have confirmed that simply controlling welding process parameters has very limited impact on particle content / distribution and brittle phase suppression; alloying control methods easily introduce new brittle phases. Therefore, how to achieve precise control of joint particle content / distribution and brittle phase suppression is a bottleneck problem that urgently needs to be solved in SiCp / Al laser welding. At the same time, accurately observing the keyhole oscillation, molten pool flow, and particle migration behaviors during SiCp / Al laser welding is crucial for controlling the welding process and obtaining high-quality joints; however, due to the limitations of observation methods, accurately obtaining these characteristics is very difficult. With the development of computational fluid dynamics and discrete element methods, it has become possible to characterize and analyze the evolution of the molten pool, keyhole, and particles in SiCp / Al laser welding through numerical simulation. However, the thermo-mechanical interaction between the fluid phase Al and the discrete phase SiC particles in the SiCp / Al laser welding process is very intense, making it more difficult to solve the multiphase coupling problem. Currently, there is a lack of relevant numerical simulation models, resulting in a lack of theoretical guidance for the control of the SiCp / Al laser welding process.

[0003] In view of this, this invention first proposes a novel laser in-situ welding method for SiCp / Al composites based on the synergistic regulation of electromagnetic field-wire-powder co-feeding. This method reduces the melting of the base material while replenishing missing SiC particles at the joint through wire-powder co-feeding; and it achieves flexible and controllable particle migration behavior by regulating the stress state of SiC through electromagnetic force. This method aims to solve the three major challenges / problems mentioned above: ① SiC particle burn-off and loss at the joint, ② SiC phase segregation at the joint, and ③ the formation of brittle phases through chemical reaction between SiC and Al. Based on this, this invention further constructs a numerical simulation method for SiCp / Al composite laser in-situ welding based on the synergistic regulation of electromagnetic field-wire-powder co-feeding, achieving accurate characterization of the molten pool, keyhole, and the thermo-mechanical behavior of SiC particles. The novel method and model proposed in this invention will be applicable to laser welding or laser additive manufacturing of other composite materials. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a laser in-situ welding method for SiC particle-reinforced aluminum matrix composites and its modeling method.

[0005] This invention is achieved as follows: a laser in-situ welding method for SiC particle-reinforced aluminum matrix composites, the method comprising:

[0006] S1: Taking a typical SiCp / Al butt welding as an example, before welding, a certain gap needs to be reserved between the SiCp / Al test plates to be welded. The beam scanning direction is along the +x direction, and the powder feeding head and wire feeding head are placed in the -x direction and +x direction of the beam, respectively. That is, the powder enters the molten pool through the tail of the molten pool, and the welding wire enters the molten pool through the keyhole of the molten pool. The positive and negative terminals of the DC power supply are connected in the y direction of the SiCp / Al plate, so that the electric field direction is distributed along the y axis. At the same time, the N and S poles of the electromagnet are arranged near the x direction of the SiCp / Al plate, so that the magnetic field direction is distributed along the x axis.

[0007] S2: During the welding process, on the one hand, similar to laser brazing, the object heated by the beam is the welding wire. The connection of SiCp / Al test plates is achieved when the welding wire is completely melted and the base material is only slightly melted. The SiC powder is injected from the tail of the molten pool to avoid direct laser radiation. This wire-powder co-feeding method not only replenishes the SiCp content of the joint but also greatly suppresses the melting of SiC and the occurrence of adverse chemical reactions. On the other hand, if it is found that SiCp in the molten pool tends to agglomerate at the bottom of the molten pool under specific process parameters, the applied magnetic field and electric field are along the +z and +x directions, respectively. At this time, the molten pool is subjected to a downward Lorentz force, which increases the buoyancy of the particles and causes them to migrate upward. If it is found that SiC particles tend to agglomerate on the surface of the molten pool, the applied magnetic field and electric field are along the +z and -x directions, respectively. At this time, the molten pool is subjected to an upward Lorentz force, which reduces the buoyancy of the particles and causes them to migrate downward.

[0008] S3: After welding, on the one hand, the wire and powder are fed together to ensure that the metal wire is completely melted and fills the gap between SiCp and Al, while the base material is only slightly melted. This greatly reduces the burn-off or melting of SiCp in the base material and inhibits the formation of brittle phases in the joint. At the same time, the SiCp is injected from the tail of the molten pool, which allows for precise control of the SiCp content in the joint, making it almost equal to that in the base material. On the other hand, based on the areas where SiCp in the joint is prone to agglomeration, the target solidification position of the particles is determined. Then, the magnitude and direction of the electromagnetic field and the Lorentz force generated are designed in a targeted manner to control the migration behavior of the particles in the molten pool, making the SiCp distribution in the joint almost equal to that in the base material.

[0009] Another objective of this invention is to provide a modeling method for laser in-situ welding of SiC particle-reinforced aluminum matrix composites based on the aforementioned SiC particle-reinforced aluminum matrix composite laser in-situ welding method. This method specifically includes:

[0010] S21: Establish a laser heat source model that considers the differences in optical properties of the particulate melt surface;

[0011] S22: Establish a multiphase flow model based on magnetohydrodynamics; using equipment such as a conductivity meter and a vibrating sample magnetometer (VSM), combined with material thermophysical parameters, obtain key parameters such as conductivity and permeability as they change with temperature. Introduce the Lorentz force of the electric / magnetic field as a source term into the momentum conservation equation, and the Joule heating of the electric field as a source term into the energy conservation equation. Couple the calculation of multiple physical fields such as temperature field, flow field, electric field, and magnetic field inside the molten pool. Further combine the Euler-Euler two-fluid method to comprehensively consider physical processes such as melting / solidification, evaporation / condensation, and electric / magnetic conduction, as well as mechanical factors such as Lorentz force, gravity, surface tension, recoil pressure, and drag caused by SiC particles, to establish a multiphase flow model of the molten pool-keyhole under the action of an electromagnetic field. Among them, the electric field and magnetic field need to be constructed first. The conductivity is calculated as shown in the following formula:

[0012]

[0013] In the formula, σ is the total conductivity, σ s The solid conductivity of aluminum alloy, σ L T represents the liquid conductivity of aluminum alloy. L T is the liquidus temperature of aluminum alloy. s Here is the solidus temperature of the aluminum alloy. The electric and magnetic fields in the fluid phase are calculated using the following formulas:

[0014]

[0015] In the formula, J is the total current density, and σ is the material conductivity. Let J be the electric potential, J1 be the steady-state transport current, u be the velocity of the liquid metal flow, and B be the magnetic field strength. The Lorentz force and its method of introducing the continuity conservation equation are expressed by the following formula:

[0016]

[0017] In the formula, F l Where P is the Lorentz force, P is the fluid pressure, and μ is the fluid viscosity. It is the gravity vector. This represents vectors of other forces, including drag force, thermal buoyancy, recoil pressure, surface tension, Lorentz force, and the drag force of SiC particles on the fluid phase. Furthermore, the solid-liquid phase transition problem in the fluid phase can be described using a melting-solidification model.

[0018]

[0019] In the formula, ρ s With ρ l C represents the density of the solid phase and the density of the liquid phase, respectively. s With C l T represents the specific heat per unit volume of the solid and liquid phases, respectively. l The temperature representing the solidus and liquidus, h sl Represents the latent heat of fusion. The tangential stress τ exerted by steam on the gas-liquid interface, such as the keyhole wall, is... vap With normal stress P sta This can be expressed simultaneously in the following ways:

[0020]

[0021] In the formula, and ρ represents the two velocity components of steam in the tangential and normal directions, respectively. g Re represents the vapor density, and Re is the Reynolds number;

[0022] S23: Develop a particle migration-heat transfer model based on Discrete Element Model (DEM). The model describes the particle contact force and deformation relationship based on Hertzian contact theory, obtains the contact thermal conductivity of SiC particles using experimental methods, and dynamically tracks contact and heat transfer using the DEM method. The force state, position coordinates, rotation, and transient temperature of each particle can be calculated using the following formulas:

[0023]

[0024] In the formula, R, θ p and T p It represents the radius position vector, angular displacement, and temperature of the SiC particles, m p I p and cp These represent the mass, moment of inertia, and specific heat of the particle, respectively. and These represent the normal force, tangential force, intermolecular cohesive force, and heat transfer between two particles, respectively. and Q F→P This represents the drag force and heat transfer of the fluid on the SiC particles;

[0025] S24: Integrated modeling of multi-energy field multiphase coupling between molten pool, keyhole, and particles.

[0026] Furthermore, S21 specifically includes:

[0027] (1) Calculate key parameters such as the geometric configuration of the Gaussian beam; using a high-power laser beam quality analyzer, measure key parameters such as the waist radius, Rayleigh length, far-field divergence angle, and energy density of the Gaussian beam at the test points, and calculate the spatial distribution function of the Gaussian light field. The shape of the beam is approximately a hyperbolic distribution, and the cross-sectional radius r of the beam along the Z direction is... z It can be represented as:

[0028]

[0029] In the formula, z f r f These are the Z-coordinate and radius of the focal plane, respectively. r Let be the Rayleigh length of the beam, and let its radii be respectively. With r f The distance between them. The heat flux q at any coordinate (x, y, z) along the beam propagation path. h (x,y,z) can be represented by the following formula:

[0030]

[0031] In the formula, Q is the incident laser power;

[0032] (2) Beam discretization: The Box-Muller transform is applied to construct photon emission points at the beam waist section that conform to a random Gaussian distribution. Based on the characteristics of the Gaussian beam's single-leaf hyperboloid, an equally probabilistic random selection function is constructed to calculate the initial energy, spatial position, and incident direction vector of each sub-beam. The equation of the straight generatrix of the single-leaf hyperboloid can be expressed by the following formula:

[0033]

[0034] In the formula, x0 is the x-coordinate of the generated point, y0 is the y-coordinate of the generated point, z0 is 0 by default, and a and b are the intersection points of this hyperboloid at z=0 with the x and y axes, respectively. The energy of each sub-beam is assigned according to a certain Gaussian distribution, and the energy formula is as follows:

[0035]

[0036] In the formula, q tg Q represents the energy allocated to each discrete sub-beam. g R represents the total energy of the sub-beam, k is the energy distribution coefficient, x0 and y0 are the coordinates of the focal plane, and R is the total energy of the sub-beam. g The radius of the sub-beam;

[0037] (3) Considering the progressive search ray tracing method for fluid-solid heterogeneous interfaces. Taking into account the differences in the reflection, scattering, and absorption mechanisms of the laser beam by SiC particles and fluids, a progressive search ray tracing method is used to solve the laser energy transport behavior in highly time-varying welding wires, particles, molten pools, and keyhole walls. Specifically, it is necessary to determine the phase, gas-liquid interface, or SiC particle that intersects with each discrete sub-ray beam. We divide the entire computational domain into grids, find the cell containing the origin of the ray beam, and define the detection radius of the particle as R. det The center coordinates (x, y, z) of each particle in the grid and the characteristic index i of the detected particle. (x,y,z),par As shown in the following formula:

[0038]

[0039] In the formula, i (x,y,z),ray These are the original characteristic parameters of the sub-ray in this coordinate cell. If the beam intersects the surface of the particle, the following equation should be satisfied:

[0040]

[0041] In the formula, M Let d be the transformation matrix of the sub-ray origin relative to the world coordinate system. ray,i This is the distance between the origin of the sub-ray beam and the intersection point of the particle. r c Let be the location of the particle intersection point in world space. Conversely, if the above equation is not satisfied, the light is absorbed by the surface of the gas-liquid interface; the energy absorption phenomenon of sub-rays at the gas-liquid interface and particle surface is described by Fresnel reflection theory, as shown in the following equation:

[0042]

[0043] In the formula, R is... Fluid / Particle The ratio of light beam absorption by the keyhole wall and the particle. ε is the angle between the incident beam and the wall normal, and ε is the absorption coefficient related to the beam type / material properties. Reflected beam x r It can be expressed by the following formula:

[0044] x r=x i -2(x i ·n)(8)

[0045] When the energy of the reflected light is less than 1% of the energy of the original light, the energy transfer is considered complete.

[0046] Furthermore, S24 specifically includes:

[0047] (1) Initialization of wire-powder-plate under electromagnetic field: Based on Biot-Sava's law, the external magnetic field generated by the DC fixed magnet is calculated according to the current intensity and the coil; based on Maxwell's theory of electromagnetic induction and generalized Ohm's law, the magnetic induction intensity and current density inside the test plate are solved; the particle content / distribution state of SiCp / Al test plate is obtained by microstructure characterization, the effective area of ​​powder flow on the test plate is calculated, and the boundary conditions such as the initialization of electromagnetic field, welding wire-powder-test plate are set; among them, the heat boundary adjustment can be expressed by the following formula:

[0048]

[0049] In the formula, q L It is the energy input of the laser, q plume It is the heat flux from the steam plume, Q P→F This represents the change in thermal energy of the molten pool volume due to the injection of particles. q cov q rad q evap These represent heat losses caused by convection, radiation, and evaporation in the fluid, respectively. The momentum boundary conditions in the normal and tangential directions of the interface can be expressed by the following formulas:

[0050]

[0051] In the formula, and Representing the normal and tangential velocities of the fluid; γ and R s P represents the surface tension coefficient and the surface radius of curvature, respectively; P→F and τ P→F These represent the normal and tangential stresses of the SiC particles on the liquid phase, respectively. The effective area of ​​the powder flow on the SiCp / Al plate can be expressed by the following formula:

[0052]

[0053] In the formula, V p V represents the velocity of the particle. g ν represents the carrier gas velocity, θ is the powder flow divergence angle, ν is the dynamic viscosity of the gas flow, and L is the distance of the powder flow from the surface of the test plate.

[0054] (2) Integrated solution strategy for fluid-structure interaction: Based on the continuity of fluid-structure velocity and the balance of pressure / shear force, the interface conditions of SiC particles / melt are accurately calculated. The response of relaxation method, Newton-Raphson method, algebraic multigrid method and other methods to the fluid-structure interaction parameters are comprehensively analyzed to achieve integrated iterative solution of multi-physics field (electric / magnetic field) and multiphase (molten pool-keyhole-droplet-particle). Based on the MPI multi-node communication mechanism, the parallel program development is completed. Among them, after one iteration of the DEM module, the coordinates, velocity, temperature and other data of the particle are updated. The fluid drag force of SiC particles is calculated using the data extracted by the fluid grid element in the previous CFD module. And calories Q F→P As shown in the following formula:

[0055]

[0056] In the formula, It is the convective heat transfer coefficient between SiC and the fluid. μ F These represent the flow velocity, particle velocity, and fluid phase viscosity of a fluid mesh cell containing particles, respectively. A P R is the surface area of ​​the SiC particles. eP The Reynolds number of a single particle is represented; then the DEM data is input into the CFD module to update the fluid velocity and temperature fields. The effect of particles on the fluid can be seen through the resistance of SiC to the fluid in the element mesh. Energy exchange Q with the fluid P→F Describe:

[0057]

[0058] In the formula, V mesh is the volume of the mesh in the computational domain, and j represents the total number of particles in the mesh; repeat the above steps to complete the iterative solution of DEM-CFD fluid-structure interaction.

[0059] Another object of the present invention is to provide a computer device, the computer device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the modeling method for laser in-situ welding of SiC particle-reinforced aluminum matrix composites.

[0060] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the modeling method for laser in-situ welding of SiC particle-reinforced aluminum matrix composites.

[0061] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0062] First, while fiber lasers provide an effective means for SiCp / Al welding, they face three major challenges: ① SiC particle burn-off and loss at the joint, ② SiC phase segregation at the joint, and ③ the formation of brittle phases through chemical reactions between SiC and Al. Furthermore, the current lack of multiphase coupled numerical simulation models for SiCp / Al laser welding leads to a lack of theoretical guidance for process control, making it difficult to obtain high-quality joints. To address these issues, this invention first proposes a novel in-situ laser welding method for SiCp / Al composites based on the synergistic control of electromagnetic field and wire-powder co-feeding, solving these three challenges. Based on this, a numerical simulation method for in-situ laser welding of SiCp / Al composites based on the synergistic control of electromagnetic field and wire-powder co-feeding is further constructed. The novel method and established numerical simulation model proposed in this invention have the following advantages:

[0063] (1) Advantages of a novel laser in-situ welding method for SiCp / Al composites based on the synergistic regulation of electromagnetic field-wire powder co-feeding:

[0064] 1. Solved the scientific problem of simultaneously suppressing brittle phases and replenishing SiC phases: Compared with traditional welding methods that only use wire feeding or powder feeding, wire and powder co-feeding allows for the simultaneous reduction of base metal melting and replenishment of missing SiC phases in the joint, effectively solving the problem that traditional laser welding cannot simultaneously meet the requirements of low SiC melting in the base metal and sufficient melting of the Al matrix in the base metal.

[0065] 2. Truly achieves flexible and controllable SiCp distribution: Traditional methods of applying only electric or magnetic fields have limited control over the stress state of the molten pool. However, the directional Lorentz force generated by the electromagnetic composite field can significantly change the stress state of the molten pool. At the same time, based on the regions where SiCp in the joint is prone to agglomeration, the target solidification position of the particles can be determined. Then, the magnitude and direction of the electromagnetic field and the directional Lorentz force it generates can be designed in a targeted manner, truly achieving flexible and controllable SiCp distribution in the joint, thereby solving the agglomeration problem.

[0066] 3. Higher welding efficiency while ensuring joint quality: The new in-situ laser welding method for SiCp / Al composites based on electromagnetic field-wire powder co-feeding synergistic control proposed in this invention can simultaneously solve three major challenges during the welding process: ① SiC particle burn-off and loss in the joint, ② SiC phase segregation in the joint, and ③ chemical reaction between SiC and Al to form brittle phases. No additional pre-weld or post-weld treatment is required, which significantly improves welding efficiency while ensuring welding quality.

[0067] (2) Advantages of the numerical simulation model for in-situ laser welding of SiCp / Al composites based on the coordinated control of electromagnetic field and wire powder co-feeding:

[0068] 1. More accurate description of welding thermal behavior: The numerical simulation model established in this invention will, for the first time, consider the differences in optical behavior such as laser absorption, scattering, and reflection between the fluid and the surface of SiC particles, making the characterization of energy transport behavior and temperature evolution behavior during the welding process more accurate.

[0069] 2. More accurate capture of welding mechanical behavior: The numerical simulation model established in this invention is the first to consider the changes in electrical conductivity and magnetic permeability of different regions during the welding process over time. Then, by calculating the evolution of the electromagnetic composite field and the resulting Lorentz force, the stress state of SiC particles, molten pool, and keyhole is captured more accurately.

[0070] 3. Reduced costs and improved efficiency: Compared with traditional methods that rely on extensive experiments to guide process development / control, the numerical simulation model established in this invention significantly reduces both time and economic costs. Compared to other numerical simulation models, the model established in this invention achieves integrated solution of the magnetohydrodynamic model and the fluid-structure interaction model, significantly improving computational efficiency.

[0071] Secondly, the technical solution of this invention fills a technological gap in the industry both domestically and internationally: it proposes a novel laser in-situ welding method based on the synergistic control of electromagnetic field-wire-powder co-feeding, effectively solving the problem of the inability to simultaneously suppress brittle phases and replenish SiC particles in traditional laser welding, achieving flexible and controllable SiCp particle distribution in the joint; simultaneously, the directional Lorentz force generated by the electromagnetic composite field significantly improves the stress state of the molten pool and the problem of particle agglomeration. Combined with precise modeling of welding thermal and mechanical behavior, this invention establishes a more physically realistic numerical simulation model, significantly reducing experimental costs and improving welding efficiency and joint quality. Attached Figure Description

[0072] Figure 1 This is a flowchart of the laser in-situ welding method for SiC particle-reinforced aluminum matrix composites provided in this embodiment of the invention;

[0073] Figure 2 This invention provides a modeling method for laser in-situ welding of SiC particle-reinforced aluminum matrix composites.

[0074] Figure 3 The present invention provides a method for loading electric / magnetic fields before welding, a method for co-feeding wire powder, and a pre-set SiCp / Al test plate splicing gap.

[0075] Figure 4The present invention provides a method for controlling the content / distribution of SiC particles and adverse chemical reactions during the welding process by wire powder co-feeding and electromagnetic field: (a) the principle of controlling the SiC particle content by wire powder co-feeding and the principle of inhibiting SiC particle burn-off / melting and adverse chemical reactions; (b) the principle of controlling particle migration behavior during the welding process by electromagnetic composite field.

[0076] Figure 5 The following is an embodiment of the present invention: the control effect of SiCp / Al laser in-situ welding based on electromagnetic field-wire powder co-feeding synergistic control: (a) schematic diagram of SiCp / Al test plate joint formation after control; (b) actual macroscopic formation of joint cross section and SiC particle content / distribution before and after control.

[0077] Figure 6 The laser heat source model considering the differences in optical properties of the surface of particulate melt provided in this embodiment of the invention includes: (a) heat source morphology and energy distribution of different cross sections; (b) progressive search ray tracing model considering the fluid-solid heterogeneous interface.

[0078] Figure 7 The multiphase flow model based on magnetohydrodynamics provided in this embodiment of the invention is as follows: (a) Molten pool morphology at 0 ms without electromagnetic field loading; (b) Molten pool morphology at 0 ms with electromagnetic field loading; (c) Magnitude and direction of molten pool current at 0 ms with electromagnetic field loading; (d) Magnitude and direction of Lorentz force in molten pool at 0 ms with electromagnetic field loading; (e) Molten pool morphology at 20 ms without electromagnetic field loading; (f) Molten pool morphology at 20 ms with electromagnetic field loading; (g) Magnitude and direction of molten pool current at 20 ms with electromagnetic field loading; (h) Magnitude and direction of Lorentz force in molten pool at 20 ms with electromagnetic field loading.

[0079] Figure 8 This invention provides a particle migration-heat transfer model based on DEM to simulate the dynamic migration and temperature evolution behavior of SiC particles during the welding process.

[0080] Figure 9 This is the initialization model of the electromagnetic field-welding wire-powder-SiCp / Al test plate provided in the embodiments of the present invention;

[0081] Figure 10 This invention provides the following embodiments of SiCp / Al laser welding process based on electromagnetic field-wire-powder co-feeding synergistic control, including the dynamic and heat transfer behavior of particles and fluid: (a) temperature distribution of SiC particles and welding wire on the molten pool surface; (b) flow field and velocity of SiC particles on the molten pool surface; (c) beam distribution, flow field / temperature field, and SiC particle temperature / velocity in the longitudinal section of the molten pool; and (d) beam distribution, flow field / temperature field, and SiC particle temperature / velocity in the cross section of the molten pool.

[0082] Figure 11 Comparative analysis of the distribution of SiCp particle volume fraction along the width of the fusion zone;

[0083] Figure 12 Comparative analysis of the volume fraction distribution of SiCp particles along the depth direction of the fusion zone. Detailed Implementation

[0084] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0085] This welding system achieves efficient in-situ laser welding of SiC particle-reinforced aluminum matrix composites through the coordinated operation of a laser generator, powder feeder, wire feeder, electromagnetic field generator, and control unit. The laser generator provides a high-power laser to melt the welding wire and form a molten pool; the powder feeder and wire feeder precisely deliver SiC powder and welding wire into the molten pool, respectively; the electromagnetic field generator dynamically regulates the electric and magnetic fields within the molten pool to control particle migration and distribution; and the control unit monitors the welding status in real time and provides feedback to adjust key parameters, ensuring welding quality and efficiency.

[0086] The high-power laser generated by the laser generator is concentrated on the welding area, melting the welding wire and forming a molten pool in the joint gap. During the formation of the molten pool, the laser heating simultaneously induces a keyhole effect, promoting localized melting and stirring of the material. The welding wire enters the molten pool through the keyhole, filling the joint gap and replenishing the metal composition of the base material, ensuring the strength and performance of the welded joint.

[0087] The powder feeding device injects SiC powder into the tail of the molten pool through a powder feeding head, avoiding direct exposure to laser radiation and thus reducing powder burn-off rate and adverse chemical reactions. The powder feeding gas path and airflow control device ensure precise control of the powder delivery rate and injection angle, allowing SiC particles to enter the molten pool uniformly. The injection of particles replenishes the SiC content of the weld joint, ensuring its consistency with the base material.

[0088] The electromagnetic field generator controls the distribution behavior of SiC particles in the molten pool by applying electric and magnetic fields. When the particles are concentrated at the bottom of the molten pool, the electric field is along the positive x-axis and the magnetic field is along the positive z-axis, increasing the upward buoyancy of the particles due to the Lorentz force. When the particles are concentrated at the surface of the molten pool, the electric field is along the negative x-axis, while the magnetic field remains along the positive z-axis, reducing the buoyancy and causing the particles to migrate downwards. This dynamic control mechanism ensures that the distribution of SiC particles within the joint is consistent with that of the base material.

[0089] The sensor module monitors the temperature field, flow field, and particle distribution of the molten pool in real time, transmitting the data to the feedback control module of the control unit. Based on the monitoring data, the feedback control module dynamically adjusts the laser power, powder feed rate, wire feed rate, and electromagnetic field strength to optimize key parameters during the welding process, ensuring the stability and accuracy of the welding process.

[0090] The control unit's algorithm optimization module, based on a multiphysics coupling model, predicts the temperature field, flow field, and particle distribution within the molten pool, and adjusts parameters in conjunction with real-time monitoring data. Through the optimized welding scheme, the SiC particles within the joint are uniformly distributed and their properties are close to those of the base material. Welding defects are significantly reduced, ensuring that the welding quality meets engineering application requirements.

[0091] like Figure 1 As shown, this embodiment of the invention provides a laser in-situ welding method for SiC particle-reinforced aluminum matrix composites, the method comprising:

[0092] S1: Taking a typical SiCp / Al butt welding as an example, before welding, a certain gap needs to be reserved between the SiCp / Al test plates to be welded. The beam scanning direction is along the +x direction, and the powder feeding head and wire feeding head are placed in the -x and +x directions of the beam, respectively. That is, the powder enters the molten pool through the tail of the molten pool, and the welding wire enters the molten pool through the keyhole of the molten pool. The positive and negative terminals of the DC power supply are connected in the y direction of the SiCp / Al plate, so that the electric field direction is distributed along the y-axis. At the same time, the N and S poles of the electromagnet are arranged near the x direction of the SiCp / Al plate, so that the magnetic field direction is distributed along the x-axis. Figure 3 As shown.

[0093] S2: During the welding process, on the one hand, similar to laser brazing, the object heated by the beam is the welding wire. The connection of the SiCp / Al test plate is achieved when the welding wire is completely melted and the base material is only slightly melted. SiC powder is injected from the tail of the molten pool to avoid direct laser radiation. This wire-powder co-feeding method replenishes the SiCp content of the joint while greatly suppressing SiC melting and adverse chemical reactions. On the other hand, if under specific process parameters it is found that SiCp in the molten pool tends to agglomerate at the bottom, the applied magnetic and electric fields are along the +z and +x directions respectively. At this time, the molten pool experiences a downward Lorentz force, increasing the buoyancy of the particles and causing them to migrate upwards. If it is found that SiC particles tend to agglomerate on the surface of the molten pool, the applied magnetic and electric fields are along the +z and -x directions respectively. At this time, the molten pool experiences an upward Lorentz force, reducing the buoyancy of the particles and causing them to migrate downwards. Figure 4 As shown.

[0094] S3: After welding, on the one hand, the co-feeding of wire and powder promotes the complete melting of the metal wire to fill the SiCp / Al joint gap, while the base material only slightly melts. This greatly reduces the burn-off or melting of SiCp in the base material and inhibits the formation of brittle phases in the joint. Simultaneously, the injection of SiCp from the tail of the molten pool allows for precise control of the SiCp content in the joint, making it nearly equal to that in the base material. On the other hand, based on the areas where SiCp in the joint is prone to agglomeration, the target solidification location of the particles is determined. Then, the magnitude and direction of the electromagnetic field and the resulting Lorentz force are specifically designed to directionally control the migration behavior of the particles in the molten pool, making the SiCp distribution in the joint nearly equal to that in the base material. For example... Figure 5 As shown.

[0095] like Figure 2 As shown, this embodiment of the invention provides a modeling method for laser in-situ welding of SiC particle-reinforced aluminum matrix composites based on the aforementioned SiC particle-reinforced aluminum matrix composite laser in-situ welding method. This method specifically includes:

[0096] S21: Establish a laser heat source model that considers the differences in optical properties of the particulate melt surface;

[0097] S22: Establish a multiphase flow model based on magnetohydrodynamics; using equipment such as a conductivity meter and a vibrating sample magnetometer (VSM), combined with material thermophysical parameters, obtain key parameters such as conductivity and permeability as they change with temperature. Introduce the Lorentz force of the electric / magnetic field as a source term into the momentum conservation equation, and the Joule heating of the electric field as a source term into the energy conservation equation. Couple the calculation of multiple physical fields such as temperature field, flow field, electric field, and magnetic field inside the molten pool. Further combine the Euler-Euler two-fluid method to comprehensively consider physical processes such as melting / solidification, evaporation / condensation, and electric / magnetic conduction, as well as mechanical factors such as Lorentz force, gravity, surface tension, recoil pressure, and drag caused by SiC particles, to establish a multiphase flow model of the molten pool-keyhole under the action of an electromagnetic field. Among them, the electric field and magnetic field need to be constructed first. The conductivity is calculated as shown in the following formula:

[0098]

[0099] In the formula, σ is the total conductivity, σ s The solid conductivity of aluminum alloy, σ L T represents the liquid conductivity of aluminum alloy. L T is the liquidus temperature of aluminum alloy. s Here is the solidus temperature of the aluminum alloy. The electric and magnetic fields in the fluid phase are calculated using the following formulas:

[0100]

[0101] In the formula, J is the total current density, and σ is the material conductivity. Let J be the electric potential, J1 be the steady-state transport current, u be the velocity of the liquid metal flow, and B be the magnetic field strength. The Lorentz force and its method of introducing the continuity conservation equation are expressed by the following formula:

[0102]

[0103] In the formula, F l Where P is the Lorentz force, P is the fluid pressure, and μ is the fluid viscosity. It is the gravity vector. This represents vectors of other forces, including drag force, thermal buoyancy, recoil pressure, surface tension, Lorentz force, and the drag force of SiC particles on the fluid phase. Furthermore, the solid-liquid phase transition problem in the fluid phase can be described using a melting-solidification model.

[0104]

[0105] In the formula, ρ s With ρ l C represents the density of the solid phase and the density of the liquid phase, respectively. s With C l T represents the specific heat per unit volume of the solid and liquid phases, respectively. l The temperature representing the solidus and liquidus, h sl Represents the latent heat of fusion. The tangential stress τ exerted by steam on the gas-liquid interface, such as the keyhole wall, is... vap With normal stress P sta This can be expressed simultaneously in the following ways:

[0106]

[0107] In the formula, and ρ represents the two velocity components of steam in the tangential and normal directions, respectively. g Re represents the vapor density, and Re is the Reynolds number. The electric field distribution, magnetic field distribution, and Lorentz force distribution of the multiphase flow model based on magnetohydrodynamics constructed using S22 at different time steps differ from the molten pool morphology under the unloaded electromagnetic field condition as follows: Figure 7 As shown.

[0108] S23: Develop a particle migration-heat transfer model based on Discrete Element Model (DEM). The model describes the particle contact force and deformation relationship based on Hertzian contact theory, obtains the contact thermal conductivity of SiC particles using experimental methods, and dynamically tracks contact and heat transfer using the DEM method. The force state, position coordinates, rotation, and transient temperature of each particle can be calculated using the following formulas:

[0109]

[0110] In the formula, R, θp and T p It represents the radius position vector, angular displacement, and temperature of the SiC particles, m p I p and c p These represent the mass, moment of inertia, and specific heat of the particle, respectively. and These represent the normal force, tangential force, intermolecular cohesive force, and heat transfer between two particles, respectively. and Q F→P The drag force and heat transfer of the fluid on SiC particles; the migration and temperature evolution behavior of the SiC particles constructed using the above S23 during the welding process are as follows: Figure 8 As shown.

[0111] S24: Integrated modeling of multi-energy field multiphase coupling between molten pool, keyhole, and particles.

[0112] Furthermore, S21 specifically includes:

[0113] (1) Calculate key parameters such as the geometric configuration of the Gaussian beam; using a high-power laser beam quality analyzer, measure key parameters such as the waist radius, Rayleigh length, far-field divergence angle, and energy density of the Gaussian beam at the test points, and calculate the spatial distribution function of the Gaussian light field. The shape of the beam is approximately a hyperbolic distribution, and the cross-sectional radius r of the beam along the Z direction is... z It can be represented as:

[0114]

[0115] In the formula, z f r f These are the Z-coordinate and radius of the focal plane, respectively. r Let be the Rayleigh length of the beam, and let its radii be respectively. With r f The distance between them. The heat flux q at any coordinate (x, y, z) along the beam propagation path. h (x,y,z) can be represented by the following formula:

[0116]

[0117] In the formula, Q is the incident laser power; the Gaussian beam reconstructed using the above sub-step (1) and its energy distribution across different cross-sections are as follows: Figure 6 As shown in (a).

[0118] (2) Beam discretization: The Box-Muller transform is applied to construct photon emission points at the beam waist section that conform to a random Gaussian distribution. Based on the characteristics of the Gaussian beam's single-leaf hyperboloid, an equally probabilistic random selection function is constructed to calculate the initial energy, spatial position, and incident direction vector of each sub-beam. The equation of the straight generatrix of the single-leaf hyperboloid can be expressed by the following formula:

[0119]

[0120] In the formula, x0 is the x-coordinate of the generated point, y0 is the y-coordinate of the generated point, z0 is 0 by default, and a and b are the intersection points of this hyperboloid at z=0 with the x and y axes, respectively. The energy of each sub-beam is assigned according to a certain Gaussian distribution, and the energy formula is as follows:

[0121]

[0122] In the formula, q tg Q represents the energy allocated to each discrete sub-beam. g R represents the total energy of the sub-beam, k is the energy distribution coefficient, x0 and y0 are the coordinates of the focal plane, and R is the total energy of the sub-beam. g The radius of the sub-beam;

[0123] (3) Considering the progressive search ray tracing method for fluid-solid heterogeneous interfaces. Taking into account the differences in the reflection, scattering, and absorption mechanisms of the laser beam by SiC particles and fluids, a progressive search ray tracing method is used to solve the laser energy transport behavior in highly time-varying welding wires, particles, molten pools, and keyhole walls. Specifically, it is necessary to determine the phase, gas-liquid interface, or SiC particle that intersects with each discrete sub-ray beam. We divide the entire computational domain into grids, find the cell containing the origin of the ray beam, and define the detection radius of the particle as R. det The center coordinates (x, y, z) of each particle in the grid and the characteristic index i of the detected particle. (x,y,z),par As shown in the following formula:

[0124]

[0125] In the formula, i (x,y,z),ray These are the original characteristic parameters of the sub-ray in this coordinate cell. If the beam intersects the surface of the particle, the following equation should be satisfied:

[0126]

[0127] In the formula, M Let d be the transformation matrix of the sub-ray origin relative to the world coordinate system. ray,i This is the distance between the origin of the sub-ray beam and the intersection point of the particle. r c Let be the location of the particle intersection point in world space. Conversely, if the above equation is not satisfied, the light is absorbed by the surface of the gas-liquid interface; the energy absorption phenomenon of sub-rays at the gas-liquid interface and particle surface is described by Fresnel reflection theory, as shown in the following equation:

[0128]

[0129] In the formula, R is... Fluid / Particle The ratio of light beam absorption by the keyhole wall and the particle. ε is the angle between the incident beam and the wall normal, and ε is the absorption coefficient related to the beam type / material properties. Reflected beam x r It can be expressed by the following formula:

[0130] x r =x i -2(x i ·n) (8)

[0131] When the energy of the reflected ray is less than 1% of the energy of the original ray, the energy transfer is considered complete. The ray tracing model constructed using sub-step 1.3 above is as follows: Figure 6 As shown in (b).

[0132] Furthermore, S24 specifically includes:

[0133] (1) Initialization of wire-powder-plate under electromagnetic field: Based on Biot-Sava's law, the external magnetic field generated by the DC fixed magnet is calculated according to the current intensity and the coil; based on Maxwell's theory of electromagnetic induction and generalized Ohm's law, the magnetic induction intensity and current density inside the test plate are solved; the particle content / distribution state of SiCp / Al test plate is obtained by microstructure characterization, the effective area of ​​powder flow on the test plate is calculated, and the boundary conditions such as the initialization of electromagnetic field, welding wire-powder-test plate are set; among them, the heat boundary adjustment can be expressed by the following formula:

[0134]

[0135] In the formula, q L It is the energy input of the laser, q plume It is the heat flux from the steam plume, Q P→F This represents the change in thermal energy of the molten pool volume due to the injection of particles. q cov q rad q evap These represent heat losses caused by convection, radiation, and evaporation in the fluid, respectively. The momentum boundary conditions in the normal and tangential directions of the interface can be expressed by the following formulas:

[0136]

[0137] In the formula, and Representing the normal and tangential velocities of the fluid; γ and R s P represents the surface tension coefficient and the surface radius of curvature, respectively; P→F and τ P→F These represent the normal and tangential stresses of the SiC particles on the liquid phase, respectively. The effective area of ​​the powder flow on the SiCp / Al plate can be expressed by the following formula:

[0138]

[0139] In the formula, V p V represents the velocity of the particle. g Here, θ represents the carrier gas velocity, ν is the powder flow divergence angle, ν is the dynamic viscosity of the gas flow, and L is the distance between the powder flow and the test plate surface; the initialization model of the electromagnetic field-welding wire-powder-SiCp / Al test plate built using sub-step S24 is as follows: Figure 9 As shown.

[0140] (2) Integrated solution strategy for fluid-structure interaction: Based on the continuity of fluid-structure velocity and the balance of pressure / shear force, the interface conditions of SiC particles / melt are accurately calculated. The response of relaxation method, Newton-Raphson method, algebraic multigrid method and other methods to the fluid-structure interaction parameters are comprehensively analyzed to achieve integrated iterative solution of multi-physics field (electric / magnetic field) and multiphase (molten pool-keyhole-droplet-particle). Based on the MPI multi-node communication mechanism, the parallel program development is completed. Among them, after one iteration of the DEM module, the coordinates, velocity, temperature and other data of the particle are updated. The fluid drag force of SiC particles is calculated using the data extracted by the fluid grid element in the previous CFD module. And calories Q F→P As shown in the following formula:

[0141]

[0142] In the formula, It is the convective heat transfer coefficient between SiC and the fluid. μ F These represent the flow velocity, particle velocity, and fluid phase viscosity of a fluid mesh cell containing particles, respectively. A P R is the surface area of ​​the SiC particles. eP The Reynolds number of a single particle is represented; then the DEM data is input into the CFD module to update the fluid velocity and temperature fields. The effect of particles on the fluid can be seen through the resistance of SiC to the fluid in the element mesh. Energy exchange Q with the fluid P→F Describe:

[0143]

[0144] In the formula, Vmesh is the volume of the mesh in the computational domain, and j represents the total number of particles within the mesh; repeat the above steps to complete the iterative solution of DEM-CFD fluid-structure interaction. In the SiCp / Al laser welding process based on the synergistic control of electromagnetic field-wire-powder co-feeding, the dynamic and heat transfer behaviors of the particles and fluid are as follows: Figure 10 As shown.

[0145] Figure 11 and Figure 12 The results show the effects of a novel laser in-situ welding method for SiCp / Al composites based on electromagnetic field-wire-powder co-feeding synergistic control on particle volume fraction in both the width and depth directions. The red line represents the experimental results without an electromagnetic field, the red bars represent the numerical simulation results of SiCp / Al composite laser in-situ welding without an electromagnetic field, the blue line represents the experimental results with an electromagnetic field, and the blue bars represent the simulation results based on electromagnetic field-wire-powder co-feeding synergistic control with an electromagnetic field. In both processes with and without an electromagnetic field, the particle volume fraction decreases along the depth direction of the fusion zone and initially decreases then increases along the width direction. However, with the addition of an electromagnetic field, the gradient distribution of particles agglomerating at the upper part and left and right boundaries of the fusion zone is significantly weakened, and the uniformity of distribution is significantly improved, sufficiently demonstrating the superiority of this invention.

[0146] Example 1: Butt welding of small-sized SiC particle-reinforced aluminum matrix composites

[0147] 1) Experimental materials and setup

[0148] Base material: SiCp / Al composite board with a thickness of 3mm, a particle reinforcement ratio of 10%, and an average diameter of 2μm for SiC particles.

[0149] Welding wire: Al-Si alloy welding wire with a diameter of 1.2mm is used.

[0150] Powder feeding material: SiC powder, with a particle diameter of 2μm, consistent with the particle diameter of the parent material.

[0151] Equipment settings: Laser power is set to 4kW, wire feed rate is 1.5m / min, powder feed rate is 10g / min, and welding speed is 10mm / s.

[0152] Electromagnetic field parameters: electric field strength is 50V / cm, magnetic field strength is 200mT, and the directions are along the y-axis (electric field) and x-axis (magnetic field).

[0153] 2) Welding process

[0154] A 0.5mm gap is reserved between the joints. The wire and powder are fed together. The welding wire is fed into the molten pool through the keyhole, and the SiC powder is injected from the tail of the molten pool.

[0155] The laser heats the welding wire, forming a keyhole and a molten pool, while the base material only slightly melts; the temperature of the molten pool is monitored in real time and the laser power is adjusted to maintain stability.

[0156] The electric and magnetic fields work together to control the floating and sinking behavior of the particles, ensuring a uniform distribution of the particles in the molten pool.

[0157] After welding, the molten pool solidifies by natural cooling.

[0158] 3) Welding effect

[0159] The SiC particles in the welded joint are uniformly distributed, with the particle content consistent with that of the base material, and there is no obvious segregation.

[0160] The tensile strength of the joint reaches 95% of that of the base material, which is significantly better than traditional welding methods.

[0161] Example 2: Welding of large-size SiC particle-reinforced aluminum matrix composites

[0162] 1) Experimental materials and setup

[0163] Base material: 10mm thick SiCp / Al composite board with a particle reinforcement ratio of 20% and an average SiC particle diameter of 10μm.

[0164] Welding wire: Al-Mg alloy welding wire, 1.6mm in diameter.

[0165] Powder feeding material: SiC powder, with a particle diameter of 10μm, consistent with the parent material particles.

[0166] Equipment settings: Laser power is set to 6kW, wire feed rate is 2.0m / min, powder feed rate is 20g / min, and welding speed is 8mm / s.

[0167] Electromagnetic field parameters: electric field strength is 80V / cm, magnetic field strength is 300mT, and the directions are along the y-axis (electric field) and z-axis (magnetic field).

[0168] 2) Welding process

[0169] The seam gap is set at 1mm, and a double-layer welding method is used. During the first layer of welding, the bottom of the seam is filled and the direction of the electromagnetic field is adjusted to make the particles migrate upward; during the second layer of welding, the surface of the seam is filled and the particles are controlled to be evenly distributed.

[0170] Laser directly heats the welding wire, creating a keyhole effect in the molten pool. By monitoring and adjusting the powder and wire feeding rates in real time, the injection amount and distribution of particles are optimized.

[0171] The direction and intensity of the electric and magnetic fields are dynamically adjusted to prevent particles from agglomerating at the bottom or surface of the molten pool.

[0172] 3) Welding effect

[0173] The particle content in the joint area is consistent with that of the base material, and the distribution is uniform, with no obvious segregation or porosity defects.

[0174] The tensile strength and ductility of the welded joint reach 92% and 88% of the base material, respectively, making it suitable for industrial production.

[0175] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A laser in-situ welding method for SiC particle-reinforced aluminum matrix composites, characterized in that, The method includes the following steps: (1) Before welding, a gap is reserved for the joint of the SiCp / Al test plate. The beam scanning direction is along the +x direction. The powder feeding head and the wire feeding head are placed in the -x direction and +x direction of the beam, respectively, so that the powder enters the molten pool from the tail of the molten pool and the welding wire enters the molten pool through the keyhole of the molten pool. At the same time, based on the Biot-Sava law, the external magnetic field generated by the DC fixed magnet is calculated according to the current intensity and the coil. Based on Maxwell's theory of electromagnetic induction and the generalized Ohm's law, the magnetic induction intensity and current density inside the test plate are solved. The particle content / distribution state of the SiCp / Al test plate is obtained by microstructure characterization. The effective area of ​​the powder flow on the test plate is calculated, and the initial boundary conditions of the electromagnetic field, welding wire-powder-test plate are set. A laser heat source model considering the differences in optical properties of the granular melt surface was established. A high-power laser beam quality analyzer was used to test the waist radius, Rayleigh length, far-field divergence angle, and energy density of the Gaussian beam. The spatial distribution function of the Gaussian light field was calculated. The Box-Muller transform was applied to construct the photon emission points of the beam waist section that conform to the random Gaussian distribution. Based on the single-leaf hyperboloid characteristics of the Gaussian beam, a probabilistic random selection function was constructed. The initial energy, spatial position, and incident direction vector of each sub-beam were calculated. Combined with the progressive search ray tracing method, the differences in the reflection, scattering, and absorption mechanisms of the beam by SiC particles and fluids were comprehensively considered to solve the laser energy transport behavior in the highly time-varying welding wire, particles, molten pool, and keyhole wall. (2) Apply electric and magnetic fields to the welding area, so that the electric field direction is distributed along the y-axis and the magnetic field direction is distributed along the x-axis. Establish a multiphase flow model based on magnetohydrodynamics. Use a conductivity meter and a vibrating sample magnetometer to obtain the conductivity and permeability as a function of temperature, combined with the material's thermophysical parameters. Introduce the electric / magnetic Lorentz force as a source term into the momentum conservation equation and the electric field Joule heat as a source term into the energy conservation equation. Couple the calculation of the temperature field, flow field, electric field, and magnetic field inside the molten pool. Combine the Euler-Euler two-fluid method to comprehensively consider the physical processes of melting / solidification, evaporation / condensation, electric / magnetic conduction, as well as the mechanical factors of Lorentz force, gravity, surface tension, recoil pressure, and drag force caused by SiC particles. Based on the real-time characterization of SiC particle distribution in the molten pool using the above model, the direction and magnitude of the electromagnetic field are dynamically adjusted. When SiC particles are concentrated at the bottom of the molten pool, the magnetic field direction is aligned with the positive z-axis and the electric field direction is aligned with the positive x-axis, increasing the upward Lorentz force on the particles. When particles are concentrated at the surface of the molten pool, the magnetic field direction is aligned with the positive z-axis and the electric field direction is aligned with the negative x-axis, reducing the buoyancy of the particles and achieving uniform particle distribution. (3) The SiC particle content of the joint is supplemented by the co-feeding technology of wire powder, and a particle migration-heat transfer model based on DEM is developed. The particle contact force and deformation relationship are described based on Hertz contact theory. The contact thermal conductivity of SiC particles is obtained by combining experimental methods. The dynamic tracking of contact and heat transfer is realized by using the discrete element DEM method, and the stress state, position coordinates, rotation and transient temperature of SiC particles are quantified. Based on the quantitative data output by the above model, the laser power and process parameters are optimized to complete the welding when the base material is only slightly melted. The wire-powder co-feeding technology is used to fill the gap of the joint by melting the welding wire, while avoiding direct exposure to laser radiation during the process of injecting the powder into the tail of the molten pool, thereby reducing the burning loss and chemical reaction of the powder. (4) By integrating the multi-energy field and multi-phase coupling model of molten pool-keyhole-particle, the interface conditions of SiC particles / melt are accurately solved based on the continuity of fluid-solid velocity and the balance of pressure / shear force. The response of relaxation method, Newton-Raphson method and algebraic multigrid method to fluid-solid bidirectional coupling parameters is comprehensively analyzed. The integrated iterative solution of electric / magnetic multi-physics field and molten pool-keyhole-droplet-particle multi-phase is realized, and the distribution of SiC particles in the weld after welding is accurately predicted.

2. The laser in-situ welding method as described in claim 1, characterized in that, During the welding process, the migration behavior of particles is controlled by applying an electromagnetic field, and the strength and direction of the electromagnetic field are designed according to the target distribution position of the joint particles so that the distribution of joint particles is almost consistent with the distribution of base material particles.

3. The laser in-situ welding method as described in claim 1, characterized in that, By dynamically monitoring the temperature and flow fields of the molten pool, the laser power, powder feeding rate, and wire feeding rate are optimized in real time to ensure stable molten pool temperature and reduce welding defects.

4. The laser in-situ welding method as described in claim 1, characterized in that, After welding, the residual effect of the electromagnetic field is used to maintain the stability of the particle distribution in the molten pool, and the molten pool is solidified by natural cooling.

5. The laser in-situ welding method as described in claim 1, characterized in that, This method is applicable to aluminum-based composite materials with different SiC particle reinforcement ratios. By adjusting the electromagnetic field strength and laser parameters, particle matching and strength balance between the welded joint and the base material can be achieved.

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