Modeling method for laser and material interaction process in additive manufacturing

Abstract

The invention provides a modeling method for a laser and material interaction process in additive manufacturing, and the method comprises the steps: delimiting a computational domain space, carrying out the grid division, and completing the initialization of a model; the defocusing amount and the laser spot radius on the surface of the base material are calculated; the method comprises the following steps: dispersing a laser beam into a plurality of sub-beams, and distributing initial energy for each sub-beam; performing index traversal on each sub-beam, and endowing the energy of the sub-beam to a solid particle and fluid surface area grid on a beam path; based on the energy and reflection state of the sub-beams, the melting state of the solid particles and the fluid is judged, and the surface appearance of the molten pool is tracked; and storing all computational domain information as boundary conditions of the next time step, and repeating the steps until modeling is completed. Energy input of laser to a complex and dynamic molten pool in the additive manufacturing process is accurately simulated, and the accuracy of quality prediction, evaluation and optimization of metal additive manufacturing parts can be improved.

Description

Technical Field

[0001] The present invention relates to the field of additive manufacturing, and in particular to a modeling method for the interaction process between laser and material in additive manufacturing. Background Art

[0002] Additive manufacturing is an important manufacturing method relative to subtractive manufacturing and isotropic manufacturing, and metal additive manufacturing is an important branch of additive manufacturing technology. The main technical route of metal additive manufacturing is to melt and solidify powder or wire, and stack layer by layer into a preset three-dimensional model. The characteristics of this technical route determine that metal additive technology has great advantages in manufacturing parts with various complex structures and complex working conditions. In recent years, metal additive manufacturing technology has been widely used in aerospace, biomedicine, and automobile manufacturing due to its unique advantages.

[0003] Guided by the current application needs of metal additive manufacturing technology, the quality of parts produced by this technology still has many shortcomings, so it is extremely urgent to improve the quality of metal additive manufacturing parts. In recent years, simulation methods have been widely used in quality prediction, evaluation and optimization of metal additive manufacturing parts. This method is considered to be one of the most economical and effective methods to improve the quality of metal additive manufacturing parts.

[0004] At present, the simulation models for metal additive manufacturing mainly include continuum models, computational fluid dynamics (CFD) models, and computational fluid dynamics-discrete element method (CFD-DEM) models. These models have one biggest commonality, that is, the entire model has only one "independent variable" namely heat input, and the rest are dependent variables. Therefore, the accuracy of the interaction modeling between laser and material is related to the accuracy of the entire model.

[0005] At present, the heat source models for metal additive manufacturing mainly include Gaussian heat source model, double ellipse heat source model and ray tracing method. Among them, Gaussian heat source model and double ellipse heat source model are fitted heat source models with high calculation efficiency, but they have no physical basis and lack authenticity; while the existing ray tracing method can simulate the process of laser reflection heating between substrates, but it cannot be used with solid particles in discrete element method, and cannot simulate the energy density loss caused by the deviation of the processing plane from the laser focal plane.

[0006] The simulation of the millimeter-level melt pool is achieved by setting various boundary conditions. The discrete element method used only obtains the initial powder state and cannot capture the powder state during the process. The multiple reflection model also only reflects between fluids. This type of model cannot study the impact of powder movement on the additive manufacturing process, and is particularly difficult to simulate powder-feeding additive manufacturing processes such as laser cladding. Summary of the invention

[0007] The present invention proposes a modeling method for the laser-material interaction process in additive manufacturing to solve the technical problem of inaccurate energy transmission modeling in existing additive manufacturing models.

[0008] In order to solve the above technical problems, the present invention provides a modeling method for the interaction process between laser and material in additive manufacturing, comprising the following steps: Step S1: Delimiting the computational domain space based on the additive manufacturing processing range, and completing model initialization after meshing the domain space; Step S2: obtaining the initial laser emission position, the laser focus position and the substrate position, and calculating the defocus amount and the laser spot radius on the substrate surface; Step S3: Discretize the laser beam into a plurality of sub-beams, obtain the position and direction information of each sub-beam, and allocate initial energy to each sub-beam according to the laser energy distribution type, the defocus amount and the distance of the sub-beam relative to the laser focus; Step S4: indexing and traversing each of the sub-beams, and imparting the energy of the sub-beams to the solid particles and the fluid surface area grid on the beam path according to the real-time position coordinate information; the sub-beams are continuously reflected between the solid particles or the fluid surface area grid or between the two; Step S5: judging the melting state of solid particles and fluid based on the energy and reflection state of the sub-beam, and tracking the surface morphology of the molten pool; Step S6: Store all computational domain information as the boundary conditions for the next time step, and repeat steps S2 to S5 until the modeling is completed.

[0009] Preferably, in step S2, the laser spot radius on the substrate surface is R b The calculation method is: ; ; In the formula, R f represents the laser spot radius in the focal plane; L Indicates the amount of defocus; L r represents the Rayleigh length; M 2 represents the laser quality factor; λ Indicates the laser wavelength.

[0010] Preferably, step S3 comprises the following steps: discretizing the laser beam into a plurality of sub-beams, setting the laser energy distribution type based on the laser type; performing energy distribution for all the sub-beams based on the laser energy distribution type and summing them, and calibrating based on the following formula; if not in compliance, multiplying the energy of all the sub-beams by the corresponding adjustment factor until compliance is achieved: ; In the formula, represents the total laser energy; n represents the number of sub-beams; Represents the energy of the sub-beam.

[0011] Preferably, the fluid surface area grid in step S4 is determined by a grid fluid fraction.

[0012] Preferably, step S4 comprises: Step S41: selecting a sub-beam, and based on the beam path of the sub-beam, traversing all solid particles and surface meshes to determine the solid particles or surface meshes that the sub-beam passes through; Step S42: according to the determination result of step S41, the energy of the sub-beam is transferred to the corresponding solid particles or surface grids according to the absorption rate; Step S43: calculating the exit point and exit vector of the sub-beam after it encounters a solid particle or a surface grid, and updating the remaining energy of the sub-beam; Step S44: repeating steps S41 to S43, and looping through all sub-beams until all the sub-beams do not pass through any solid particles or surface meshes.

[0013] Preferably, in step S41, the solid particles passed by the sub-beam are determined by the following method: all solid particles are traversed, and based on the distance from the coordinate point of the solid particle to the sub-beam, if the distance is less than the radius of the solid particle, the grids between the exit point of the sub-beam and the solid particle are traversed for verification to determine whether there is a surface grid or a grid filled with fluid, and if so, the sub-beam has not passed through the solid particle, otherwise it has passed through.

[0014] Preferably, in step S41, the surface mesh passed by the sub-beam is determined by the following method: all surface meshes are traversed, and according to the surface mesh coordinates, the surface mesh fluid fraction and the interface normal vector in the mesh, the interface equation is obtained by reconstructing the interface using the piecewise linear method PLIC, and then the intersection coordinates of the vector of the sub-beam and the interface equation are calculated; if the intersection coordinates are located within the surface mesh and there are no solid particles between the exit point of the sub-beam and the intersection coordinates, then the sub-beam passes through the surface mesh; otherwise, the sub-beam does not pass through the surface mesh.

[0015] Preferably, when there are several surface grids meeting the determination condition, the surface grid closest to the laser emission point is selected as the surface grid for capturing the sub-beam.

[0016] Preferably, step S5 comprises: Step S51: after energy is imparted to each of the sub-beams in step S4, the temperature rise and fall of each solid particle and all the fluids are calculated to determine whether the temperature of the solid particle reaches the solidus line of the material. If so, the solid particle is converted into a fluid, and whether the fluid is melted is determined according to the fluid temperature; Step S52: setting the time step, solving the Navier-Stokes NS equations and the energy equation to obtain the state information of the molten pool, and using the fluid volume VOF method to track the surface morphology of the molten pool.

[0017] Preferably, in step S1, when initializing the model, the powder for the laser cladding process is fed in a powder feeding manner, and the solid particle powder is sprayed from four directions to the focus of the laser on the intended deposition plane; the position information of the solid particle powder is calculated according to gravity and the drag of the protective gas; in step S4, when the energy of the sub-beam is assigned to the solid particles on the beam path and the fluid surface area grid, the ratio of the laser energy density on the horizontal plane where the solid particle powder is located and the laser energy density on the intended deposition plane is calculated to obtain the attenuation factor, and the original energy of the sub-beam is multiplied by the attenuation factor and the absorption rate before being assigned to the solid particle powder. The beneficial effects of the present invention include at least: the present invention realizes the laser reflection simulation between the solid particles and the fluid grid, solves the problem of inaccurate energy transfer modeling in the additive manufacturing CFD-DEM fully coupled model; considers the influence of the laser defocus amount, which helps to improve the accuracy of multi-layer additive manufacturing simulation; regards the powder as a movable solid particle before melting, breaks through the limitation that the powder cannot move in the traditional CFD-DEM model, and provides model support for the study of powder movement in the additive manufacturing process. It can accurately simulate the energy input of the laser to the complex and dynamic molten pool during the additive manufacturing process, which helps to improve the accuracy of quality prediction, evaluation and optimization of metal additive manufacturing parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of a method flow chart of an embodiment of the present invention; Figure 2 The laser discretization and laser energy distribution diagram of an embodiment of the present invention; Figure 3 This is a calculation diagram of the emission point and emission vector of the laser after reflection according to an embodiment of the present invention; Figure 4 This is a test diagram of laser reflection energy according to an embodiment of the present invention; Figure 5It is a simulation result diagram of solid particles, fluid, and solid particles converted into fluid after laser application in an embodiment of the present invention; Figure 6 A simulation diagram of powder in laser cladding according to an embodiment of the present invention; Figure 7 Schematic diagram of powder defocusing in laser cladding according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings 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 belong to the protection scope of the present invention.

[0020] Example 1 like Figure 1 As shown, an embodiment of the present invention provides a modeling method for the laser-material interaction process in additive manufacturing, comprising the following steps: Step S1: Delimit the computational domain space based on the additive manufacturing processing range, and complete the model initialization after meshing the domain space.

[0021] The model is initialized by combining material thermophysical parameters, process parameters, scanning strategy and powder distribution. The powder distribution is simulated by discrete element method according to the additive manufacturing process type, and the powder distribution form is determined according to the additive manufacturing process type; for example, the powder of the laser cladding process is powder feeding type, and the powder is sprayed to the laser focus by the powder feeding nozzle; for example, the laser cladding process is selected as powder spreading type, and the powder is evenly spread on the surface of the substrate by a scraper.

[0022] Specifically, a substrate model is established in the rectangular computational domain, material parameters and initial conditions are assigned, and then the computational domain is discretized using a hexahedral grid; the height of the computational domain above the substrate should be no less than 1 mm; and the substrate is initialized as a fluid.

[0023] In this embodiment, a discrete element model of the powder bed is established according to the size and shape of the powder particles and the thickness of the powder bed in the experiment; in the discrete element model, the thickness of the powder bed is controlled by the distance between the substrate and the bottom of the scraper, and the size of the powder particles is controlled by the particle size distribution of the experimental powder; the thickness of the powder bed is 40μm, and the powder size distribution is D10=17.3μm, D50=34.1μm, D90=55.2μm, where the particle size parameters represent 10%, 50%, and 90% of the particle sizes within the measured size values, and the powder particles are initialized as solid particles.

[0024] Step S2: Obtain the initial laser emission position, laser focal position and substrate position, and calculate the defocus amount and the laser spot radius on the substrate surface.

[0025] The defocus value is the distance between the laser focal plane and the plane. The defocus value has a sign. The positive sign or "+" indicates that the laser focal plane is above the intended deposition plane, and the negative sign or "-" indicates that the laser focal plane is below the intended deposition plane. The laser spot radius of the intended deposition plane is R b The laser spot radius in the focal plane R and defocus L calculate: ; ; In the formula, R f represents the laser spot radius in the focal plane; L Indicates the amount of defocus; L r represents the Rayleigh length; M 2 represents the laser quality factor; λ Indicates the laser wavelength.

[0026] Step S3: Discretize the laser beam into several sub-beams, obtain the position and direction information of each sub-beam, and allocate initial energy to each sub-beam according to the laser energy distribution type, defocus amount and the distance of the sub-beam relative to the laser focus.

[0027] Specifically, the distance between the laser focal plane and the intended deposition plane is calculated, the defocus amount and the laser spot radius on the intended deposition plane are determined, and the laser is discretized into a number of sub-beams according to the spot radius. In this embodiment, only the melt path of the first layer of printing is simulated, so the laser spot radius on the intended deposition plane is equal to the laser spot radius on the laser focal plane, which is specifically 40 μm. Figure 2 As shown, the laser is evenly discretized into 200*200 sub-beams.

[0028] In this embodiment, the laser energy distribution type may be Gaussian distribution, flat-bottom distribution, or elliptical distribution, which is specifically selected according to the laser type. The present invention does not limit this, and Gaussian distribution is used for illustration below.

[0029] In this embodiment, the laser energy distribution conforms to the Gaussian distribution, and the distribution is: ; Wherein, A is the laser absorption rate, P is the laser power, and r is the distance from the sub-beam to the laser center. In this embodiment, A is 0.3, P is 290W, and the energy of all sub-beams is distributed and summed to compare whether they meet the requirements. If they do not meet the requirements, the energy of all sub-beams is multiplied by the corresponding adjustment factor until they meet the requirements: ; In the formula, represents the total laser energy; n represents the number of sub-beams; Represents the energy of the sub-beam.

[0030] Exemplarily, in this embodiment, the initial laser emission position should be above the calculation domain, and there should be no fluid or solid particles above the laser emission position.

[0031] In this embodiment, the fluid is divided into solid fluid and liquid fluid, which are controlled by a computational fluid dynamics (CFD) model. The solid particles are rigid bodies and will not deform, and are controlled by a discrete element model.

[0032] Step S4: Index and traverse each sub-beam, and according to the real-time position coordinate information, impart the energy of the sub-beam to the solid particles and the fluid surface area grid on the beam path; the sub-beam is continuously reflected on the solid particles or the fluid surface area grid or between the two.

[0033] Specifically, the steps include: Step S41: First, find the fluid surface grid according to the grid fluid score, obtain the surface grid coordinate information, surface grid fluid score information and grid interface normal vector information, obtain the coordinate information and diameter information of all solid particles, and store the above information in an array.

[0034] Step S42: select a sub-beam, traverse all solid particles, and determine whether the sub-beam passes through the solid particle based on the distance from the solid particle coordinate point to the sub-beam. If the sub-beam passes through the solid particle, traverse the grid between the sub-beam exit point and the solid particle for verification to determine whether there is a surface grid or a grid filled with fluid. If so, the sub-beam does not pass through the solid particle, otherwise it passes through.

[0035] Step S43: If the sub-beam does not pass through the solid particles, all surface grids are traversed, and the interface equation is obtained by reconstructing the interface using the piecewise linear method PLIC method according to the surface grid coordinates, the surface grid fluid fraction and the interface normal vector within the grid. Then, the coordinates of the intersection of the sub-beam vector and the interface equation are calculated. If the coordinates of the intersection are within the grid, the sub-beam passes through the grid.

[0036] In this embodiment, the piecewise linear method PLIC interface reconstruction method is used to calculate the reflection point and reflection vector of the laser sub-beam, thereby improving the accuracy of the laser reflection model.

[0037] Step S44, according to step S42 to step S43, the energy of the sub-beam is transferred to the corresponding solid particles or surface grids according to the specific absorption rate. In this embodiment, the absorption rate is calculated by the Fresnel equation, and then the exit point and the exit vector of the sub-beam after the sub-beam encounters the solid particle or the surface grid are calculated, and the remaining energy of the sub-beam is updated. The exit vector calculation method after the sub-beam is reflected is as follows: Figure 3 shown.

[0038] Step S45, repeating S42 to S44 until the sub-beam does not pass through any solid particles or surface grids, or until the remaining energy of the sub-beam is low, that is, less than a set threshold. In this embodiment, when the energy of the sub-beam is lower than 10% of the initial energy of the sub-beam, the repetition of S42 to S44 can be stopped:

[0039] In the formula, Represents a sub-beam i reflection n The energy after that, sub-beam i The initial energy.

[0040] In this embodiment, Figure 4 As shown, in order to save calculation time, the remaining energy after laser reflection was tested, and it was determined that in this material, the remaining energy after the laser was reflected twice can be ignored.

[0041] Step S46: Use the OpenMP loop parallel algorithm to traverse all sub-beams and repeat steps S42 to S45.

[0042] In this embodiment, the judgment criterion for whether the sub-beam passes through the solid particle in step S42 and step S43 is that the distance from the center point of the solid particle to the sub-beam vector is less than the radius of the solid particle; if the sub-beam passes through the solid particle, the coordinates of the intersection of the sub-beam and the surface of the solid particle are calculated, and then the direction vector of the sub-beam after reflection is obtained according to the law of reflection of light; the reflection direction vector of the sub-beam after passing through the surface grid is also calculated according to the law of reflection of light.

[0043] Since there may be multiple qualified surface grids in the method for determining whether a sub-beam passes through a surface grid, in an embodiment of the present invention, the surface grid closest to the laser emission point is selected from multiple qualified surface grids as the surface grid for capturing the sub-beam.

[0044] It should be noted that the order of judging whether the sub-beam passes through the surface grid or solid particles in steps S42 to S43 can be swapped. It is possible to first judge the solid particles and then check whether there is a surface grid or a grid filled with fluid blocking it, and then judge whether it passes through the fluid. It is also possible to first judge the surface grid and then check whether there is a solid particle blocking it and then judge whether it passes through the solid particles.

[0045] Step S5: judging the melting state of solid particles and fluid based on the energy and reflection state of the sub-beam, and tracking the surface morphology of the molten pool; Specifically, after the energy distribution of all sub-beams is completed, the temperature rise and fall of each solid particle and all fluids are calculated to determine whether the temperature of the solid particles reaches the solidus line of the material. If it reaches the solid phase, the solid particles are converted into fluids, and the fluid temperature is used to determine whether the fluid is melted. Then, the time step is set, the Navier-Stokes NS equations and the energy equation are solved to obtain the state information of the molten pool, and the fluid volume VOF method is used to track the surface morphology of the molten pool.

[0046] Step S6: Store all computational domain information as the boundary conditions for the next time step, and repeat steps S2 to S5 until the modeling is completed.

[0047] Specifically, Figure 5 As shown in the figure, taking the selective laser melting process as an example, the substrate and powder particles are heated normally. The substrate temperature melts after reaching the solidus, and the new morphology is calculated by the fluid control equation and the VOF equation. Before the powder temperature reaches the solidus, the solid particle morphology is maintained and controlled by the particle motion control equation. After reaching the solidus, it is converted into a fluid with fluid characteristics and is controlled by the NS equation and the energy equation.

[0048] Example 2 This embodiment is based on the steps of Embodiment 1, and improves and supplements the powder distribution part thereof.

[0049] The difference is that the powder is no longer laid by a scraper but by a nozzle; the powder spraying angle will change with the change of the height of the cladding layer; the energy allocated to the powder by the sub-beam is related to the height of the powder.

[0050] The application of high-fidelity modeling methods for the laser-material interaction process in additive manufacturing to the simulation of laser cladding process includes: like Figure 6 As shown, powder is sprayed from four directions to the focus of the laser on the intended deposition plane. Several characteristic parameters of the nozzle laying powder are determined based on the data in the experiment: powder spraying speed, powder spraying amount, powder size, and powder spraying angle.

[0051] The position information of the powder is calculated according to gravity and the drag force of the shielding gas. Exemplarily, the relationship between the shielding gas and the powder is a one-way coupling. In particular, the one-way coupling refers to the shielding gas transferring momentum to the powder.

[0052] like Figure 7 As shown, when the sub-beam is allocated to the powder energy, the height of the powder is taken into consideration; the distance from the powder to the laser focal plane is calculated to obtain the spot radius of the laser on the horizontal plane where the powder is located, and then the ratio of the laser energy density on the plane to be deposited is calculated to obtain the attenuation factor, and the original energy of the sub-beam is multiplied by the attenuation factor and the absorption rate before being allocated to the powder.

[0053] By adopting the solution of this embodiment, the influence of the powder position on the laser-material interaction is calculated more accurately, which is beneficial to the simulation of additive manufacturing processes with complex powder distribution and high melt channel height.

[0054] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. Only the preferred embodiments of the present invention are expressed. The description is more specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. As long as there is no contradiction in the combination of these technical features, they should be considered as the scope recorded in this specification.

[0055] It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these modifications and improvements all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A modeling method for the interaction process between laser and material in additive manufacturing, characterized by: The following steps are involved: Step S1: Delimiting the computational domain space based on the additive manufacturing processing range, and completing model initialization after meshing the domain space; Step S2: obtaining the initial laser emission position, the laser focus position and the substrate position, and calculating the defocus amount and the laser spot radius on the substrate surface; Step S3: Discretize the laser beam into a plurality of sub-beams, obtain the position and direction information of each sub-beam, and allocate initial energy to each sub-beam according to the laser energy distribution type, the defocus amount and the distance of the sub-beam relative to the laser focus; Step S4: indexing and traversing each of the sub-beams, and imparting the energy of the sub-beams to the solid particles and the fluid surface area grid on the beam path according to the real-time position coordinate information; the sub-beams are continuously reflected between the solid particles or the fluid surface area grid or between the two; Step S5: judging the melting state of solid particles and fluid based on the energy and reflection state of the sub-beam, and tracking the surface morphology of the molten pool; Step S6: Store all computational domain information as the boundary conditions for the next time step, and repeat steps S2 to S5 until the modeling is completed.

2. The modeling method of the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: In step S2, the laser spot radius on the substrate surface is R b The calculation method is: ； ； In the formula, R f represents the laser spot radius in the focal plane; L Indicates the amount of defocus; L r represents the Rayleigh length; M 2 represents the laser quality factor; λ Indicates the laser wavelength.

3. The modeling method for the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: Step S3 includes the following steps: discretizing the laser beam into a plurality of sub-beams, setting the laser energy distribution type based on the laser type; performing energy distribution for all the sub-beams based on the laser energy distribution type and summing them, and calibrating based on the following formula; if not in compliance, multiplying the energy of all the sub-beams by the corresponding adjustment factor until compliance is achieved: ； In the formula, represents the total laser energy; n represents the number of sub-beams; Represents the energy of the sub-beam.

4. The modeling method for the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: In step S4, the fluid surface area grid is determined by the grid fluid fraction.

5. The modeling method for the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: Step S4 includes: Step S41: selecting a sub-beam, and based on the beam path of the sub-beam, traversing all solid particles and surface meshes to determine the solid particles or surface meshes that the sub-beam passes through; Step S42: according to the determination result of step S41, the energy of the sub-beam is transferred to the corresponding solid particles or surface grids according to the absorption rate; Step S43: calculating the exit point and exit vector of the sub-beam after it encounters a solid particle or a surface grid, and updating the remaining energy of the sub-beam; Step S44: repeating steps S41 to S43, and looping through all sub-beams until all the sub-beams do not pass through any solid particles or surface meshes.

6. The modeling method for the laser-material interaction process in additive manufacturing according to claim 5, characterized in that: In step S41, the solid particles passed by the sub-beam are determined by the following method: all solid particles are traversed, and based on the distance from the coordinate point of the solid particle to the sub-beam, if the distance is less than the radius of the solid particle, the grids between the exit point of the sub-beam and the solid particle are traversed for verification to determine whether there is a surface grid or a grid filled with fluid. If so, the sub-beam has not passed through the solid particle, otherwise it has passed through.

7. The modeling method for the laser-material interaction process in additive manufacturing according to claim 5, characterized in that: In step S41, the surface mesh passed by the sub-beam is determined by the following method: all surface meshes are traversed, and according to the surface mesh coordinates, the surface mesh fluid fraction and the interface normal vector in the mesh, the interface equation is obtained by reconstructing the interface using the piecewise linear method PLIC, and then the intersection coordinates of the vector of the sub-beam and the interface equation are calculated. If the intersection coordinates are located within the surface mesh and there are no solid particles between the exit point of the sub-beam and the intersection coordinates, then the sub-beam passes through the surface mesh; otherwise, the sub-beam does not pass through the surface mesh.

8. The modeling method for the laser-material interaction process in additive manufacturing according to claim 7, characterized in that: When there are several surface grids that meet the determination condition, the surface grid closest to the laser emission point is selected as the surface grid for capturing the sub-beam.

9. The modeling method for the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: Step S5 includes: Step S51: after energy is imparted to each of the sub-beams in step S4, the temperature rise and fall of each solid particle and all the fluids are calculated to determine whether the temperature of the solid particle reaches the solidus line of the material. If so, the solid particle is converted into a fluid, and whether the fluid is melted is determined according to the fluid temperature; Step S52: Set the time step, solve the Navier-Stokes NS equations and the energy equation to obtain the state information of the molten pool, and use the fluid volume VOF method to track the surface morphology of the molten pool.

10. The modeling method of the laser-material interaction process in additive manufacturing according to claim 1, characterized in that: In step S1, when initializing the model, the powder of the laser cladding process is fed by powder feeding, and the solid particle powder is sprayed from four directions to the focus of the laser on the intended deposition plane; the position information of the solid particle powder is calculated according to gravity and the drag of the shielding gas; in step S4, when the energy of the sub-beam is assigned to the solid particles and the fluid surface area grid on the beam path, the ratio of the laser energy density on the horizontal plane where the solid particle powder is located to the laser energy density on the intended deposition plane is calculated to obtain the attenuation factor, and the original energy of the sub-beam is multiplied by the attenuation factor and the absorption rate before being assigned to the solid particle powder.

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