CFD-DEM strong-coupled micro-selective laser powder bed melting high-fidelity numerical calculation method

Abstract

The invention discloses a micro-laser selective melting numerical calculation method based on a laser-powder particle-molten drop-steam coupling effect. Belongs to the technical field of additive manufacturing simulation. According to the method, momentum and energy of metal powder particles are calculated through a discrete element method (DEM); metal steam and environment gas are calculated by adding a steam model on a gas-liquid interface, and momentum and energy of a liquid phase and a gas phase are calculated by adopting a fluid dynamics (CFD) method; information such as volume fraction, momentum and energy is transmitted between the DEM and the CFD through a bidirectional coupling equation. Therefore, a multi-phase and multi-physical-field coupled molten pool high-fidelity numerical model is established, and intra-phase and inter-phase interaction and thermally-induced phase change including melting, vaporization and solidification are achieved. And an effective means is provided for accurately predicting defects such as splashing, denudation and pores of the molten pool.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of additive manufacturing, and belongs to a micro-selective laser powder bed fusion high-fidelity numerical calculation method involving CFD-DEM strong coupling. BACKGROUND

[0002] Laser powder bed fusion (LPBF) is an additive manufacturing process based on selective melting of metal powder by high-energy laser beam, which is accompanied by complex heat and mass transfer behavior, phase change reaction and spatter and erosion and other metallurgical physical phenomena. With the ability to form high-precision and high-performance parts, this technology has become a research hotspot in the field of advanced manufacturing. However, the processing feature size of conventional LPBF (c-LPBF) is usually limited to about 300 µm, which is difficult to meet the manufacturing needs of micro-structure parts.

[0003] In contrast, micro-LPBF (µ-LPBF) exhibits significant advantages in high-precision manufacturing of micro-structures by using ultra-fine powder with a particle size of less than 25 µm, a precise laser focusing system with a spot diameter of less than 40 µm, and a thin layer powder laying strategy with a layer thickness of less than 15 µm.

[0004] Existing research on µ-LPBF process mainly focuses on process parameter optimization, microstructure regulation and mechanical property improvement, while the research on molten pool dynamics is still in the blank. For example, the temperature, velocity, pressure and other variables of the molten pool are difficult to measure by experimental means. The introduction of simulation provides a new method to solve this problem.

[0005] However, there is currently a lack of simulation of µ-LPBF, and the formation mechanism of defects such as spatter, erosion, spheroidization and porosity at the mesoscale in this process is still unclear. These defects have a great influence on the formability and performance of parts. In existing simulation models, the multi-phase coupling interaction of powder particles, vapor and molten pool melt is ignored, or only weak coupling between solid particles and molten pool fluid is achieved, which cannot achieve high-precision calculation of molten pool dynamics behavior during the forming process. Effective prediction cannot be made for calculations that need to consider multi-phase coupling. SUMMARY

[0006] The purpose of the present application is to overcome the shortcomings of the prior art and provide a CFD-DEM strong coupling micro-selective laser powder bed fusion high-fidelity numerical calculation method. To solve the problem that the µ-LPBF melting spatter and erosion behavior is difficult to simulate and difficult to accurately calculate in the prior art.

[0007] To achieve the above object, the application adopts the following technical solutions to achieve the above object: A CFD-DEM strong coupling micro-selection laser powder bed melting high-fidelity numerical calculation method, comprising the following steps: S1, a CFD-DEM coupled calculation domain is constructed, and metal powder particles are added in the calculation domain; S2, the calculation domain is initialized; S3, in the DEM model, the metal powder particles are tracked, the acting force between the metal powder particles is obtained, the linear heat conduction transmission energy between the metal powder particles and the fluid under the laser heat source is obtained, and then the volume fraction of the metal powder particles in the calculation domain and the momentum and energy of the metal powder particles to the fluid phase are obtained; the fluid includes a liquid phase and a gas; S4, a vapor model is added to the gas-liquid interface in the CFD model, a liquid mass loss equation considering the recoil pressure is added to the vapor model; a heat source model and a fluid momentum source model are set in the CFD model, and heat loss is considered in the heat source model; the volume fraction of the metal powder particles and the momentum and energy of the metal powder particles to the fluid phase obtained in S2 are combined to calculate the volume fraction of the fluid in the calculation domain and the momentum and energy of the fluid phase to the metal powder particle phase; S5, the volume fraction of the fluid and the momentum and energy of the fluid phase to the metal powder particle phase in S4 are applied to S3, and the alternating iteration process in S3 and S4 is repeated until a set time is reached.

[0008] Further improvement of the application is: Preferably, in S1, after the CFD-DEM coupled calculation domain is constructed, the calculation domain is meshed, and the meshes of the molten pool region and the vapor region in the calculation domain are encrypted.

[0009] Preferably, the heat source in S3 and S4 is a Gaussian laser beam, and the Gaussian laser beam includes multiple reflections and absorptions of light rays by the laser wall.

[0010] Preferably, in S3, the acting force of the metal powder particles includes drag force, gravity and contact force.

[0011] Preferably, in S3, the equation of linear heat conduction transmission energy is: (1) In the formula, , and respectively represent laser-induced heat, powder heat conduction and fluid-induced heat; and respectively represent the particle thermal conductivity and the particle geometric mean value; is the distance between the center of gravity of the particle and the center of the laser spot.

[0012] Preferably, in S3, the momentum and energy of the metal powder particles to the fluid phase is formulated as: (2) where, represents the momentum of the particle phase acting on the fluid phase, F d is the drag force, and are the time step of the CFD and DEM solvers, respectively; is the number of particles; Q F-P represents the accumulated particle energy in the cell; solve the action of the particle phase to the fluid phase in each time step, calculate the momentum and energy equations.

[0013] Preferably, in S4, the vapor model is: (3) where, is the positive net flux of elements on the gas-liquid interface, , , T and represent the atomic mass, Boltzmann constant, surface temperature and evaporation coefficient, respectively, is the saturated vapor pressure; the liquid phase mass loss equation is: (4) where, α F1 , p F1 , p F2 and represent the liquid volume fraction, liquid density, gas density and mass loss, p0, L v , , T , T v and R u represent the ambient gas pressure, latent heat of vaporization, molar mass, temperature, gas evaporation point and universal gas constant, respectively.

[0014] Preferably, in S4, the heat loss includes convective heat transfer, radiation heat dissipation and vapor shielding.

[0015] Preferably, in S4, the fluid momentum source model includes gravity, surface tension, Marangoni flow and fluid flow resistance.

[0016] Preferably, in S4, the momentum and energy process equation of the fluid phase to the metal powder particle phase is: (11) wherein, C d is the drag coefficient, Re p is the Reynolds number of the particle, h p-F is the heat convection coefficient, is the Prandtl number of the fluid phase, is the particle surface area.

[0017] Compared with the prior art, the present application has the following beneficial effects: The application discloses a micro-selective laser powder bed fusion numerical calculation method of laser-powder particle-melt pool-vapor coupling. Through two-way strong coupling of computational fluid dynamics (CFD) and discrete element method (DEM), a high-fidelity numerical model of a melt pool coupled with multiple phases and multiple physical fields is established, interaction between phases and heat-induced phase change are realized, including melting, vaporization and solidification. The interaction of temperature, velocity, pressure, position and other information in the calculation domain is realized, thereby improving the accuracy of simulation. The method introduces a vapor model in the CFD model, considers the effect of environmental gas and vapor on metal particles and droplets, makes the simulation more realistic, and obtains gas-solid-liquid temperature field, velocity field, pressure field and other information. The method simulates the mesoscale of laser-powder particle-droplet-vapor interaction in the micro-selective laser powder bed fusion process, accurately predicts spatter, erosion, porosity and other phenomena, and achieves the purpose of improving the formability and performance of parts. Further, adaptive mesh is used to encrypt the mesh of the melt pool area, which reduces the calculation amount and improves the calculation efficiency under the premise of ensuring the calculation accuracy.

[0018] Further, the process parameters used in the model can be realized by micro-selective laser powder bed fusion, so the model is suitable for any micro-selective laser powder bed fusion construction mode and has a wide range of applications. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a CFD-DEM strong coupling simulation method flow chart of the application; Figure 2 is a schematic view of adaptive mesh division of a calculation domain; Figure 3 is a metal powder particle powder layer; Figure 4 is the calculation result of the interaction between laser-powder particle-droplet-vapor in the embodiment. DETAILED DESCRIPTION

[0020] Hereinafter, the terms "first", "second", "third", "fourth" are used only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", "third", "fourth" can explicitly or implicitly include one or more of the features.

[0021] The method for shooting provided by the embodiments of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, notebook computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), and the like. The embodiments of the present application do not make any limitation on the specific type of the terminal device.

[0022] It should be noted that the terms "first", "second", and the like in the specification and drawings of the present application are used to distinguish similar objects, and do not necessarily indicate or imply a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0023] The application discloses a CFD-DEM strong coupling micro-selection zone laser powder bed melting simulation method, comprising the following steps: S1, a calculation domain of CFD-DEM coupling is constructed, the calculation domain is divided into a substrate layer, a gas layer and a powder layer, the powder layer is laid on the substrate layer, and the gas layer is above the substrate layer, since the powder layer itself is in the gas layer, only the substrate layer and the gas layer in the calculation domain are meshed (actually including meshing of the powder layer). The gas is composed of protective gas and vapor, based on which the vapor area is in the gas layer, and the powder on the substrate layer and part of the substrate form a molten pool area after melting; the grids in the molten pool area and the vapor area in the calculation domain are densified, and an adaptive grid technology is used near the gas-liquid interface to improve the calculation efficiency; further, the grid density of the phase change area is smaller than that of the vapor area, and the grid size of the vapor area is smaller than that of the molten pool area. Based on the above setting, three phases are considered in the calculation domain of the application, which are gas phase, molten pool liquid phase and solid phase; the solid phase includes the un-melted powder layer and the metal powder particles suspended in the gas layer, which are mainly simulated and calculated by the DEM model. The gas phase and the molten pool liquid phase form a fluid, which is mainly simulated and calculated by the CFD model.

[0024] In one specific example, referring to Figure 2 , four grid densification sizes are used: the basic size of the grid is 5 µm, the minimum grid size at the gas-liquid interface after densification in the phase change area is 1 µm, and the transition area between the two is 1.5 µm, 2.5 µm.

[0025] In one specific example, discrete spherical particles with a normal distribution of powder sizes are injected into the gas layer, the powder particles are set to be 316L stainless steel, the average particle size of the powder is set to be 10 µm, and the powder layer thickness is set to be 10 µm; the powder laying powder layer model is shown in Figure 3 .

[0026] S2, in order to accurately simulate the behavior of metal powder particles, further adding metal powder particles in the gas layer, and setting the initial conditions such as temperature, pressure in the calculation domain, initializing the calculation domain, and setting the time as the initial time t0. For example, the initial temperature is set to be 300K, the initial pressure is set to be vacuum, and other settings are all zero, so as to fit the real experimental conditions.

[0027] S3, in the calculation domain, the energy conservation equation and the momentum conservation equation between phases are constructed based on the DEM and CFD methods, the temperature field, the velocity field and the pressure field between the vapor-powder particles-molten droplets are obtained by solving the equations, so as to accurately simulate the melting and solidification of the molten pool and the vaporization phenomenon. The CFD-DEM two-way coupling algorithm uses data interaction in the same system, and the DEM model and the CFD model identify the free surface by transferring volume fraction information. The metal powder particles are added in the grid, and the ratio of the actual grid volume occupied by the fluid phase to the total grid volume is set to be α F , then the volume fraction of the particle phase is 1-α F ; specifically comprising the following steps: S301, establishing a DEM model, calculating the particle domain; 1) judging whether the temperature of the particle phase reaches the melting point; If the melting point is reached, the particle phase in the grid is converted into a fluid phase and the original particle is deleted, otherwise it is retained. 2) According to the discrete element method, the displacement, rotation and energy of the metal powder particles are tracked; the forces acting on the metal powder particles including drag force, gravity and contact force are obtained; the Hertz-Mindlin model is used to calculate the contact force between particles, and the drag force is obtained by CFD model.

[0028] After adding all the forces, the momentum information of the metal powder particles is obtained.

[0029] 3) A Gaussian laser beam is loaded on the metal powder particles as a heat source, and a heat source model as shown in equation (6) is set; the heat source acts on the metal powder particles and the substrate at the same time, and the addition position can change with time, which is a movable Gaussian laser surface heat source. The heat source includes multiple reflections of laser light by the hole wall and absorption of laser energy by the powder.

[0030] The laser heat source is applied to the powder particles, and energy is transferred according to the linear heat conduction between particles and particles, and between particles and fluid; the energy equation is represented as: (1) In the formula, , and respectively represent laser-induced heat, powder heat conduction and fluid-induced heat; , c p and respectively represent the normal resistance, Young's modulus, particle thermal conductivity and particle geometric mean; , A ap , P and ω respectively are the distance between the particle center of gravity and the center of the laser spot, the laser absorption rate, the laser power and the effective Gaussian laser spot radius; and are the temperatures of powder particles A and B respectively.

[0031] 4) Update the information of particle position, temperature, velocity, etc.

[0032] S302, coupling the volume fraction, momentum information and energy information of the discrete metal powder particles in the DEM domain to the CFD domain.

[0033] (2) where, represents the momentum of the particle phase acting on the fluid phase, F d is the drag force, and are the time steps of the CFD and DEM solvers, respectively. is the number of particle particles; Q F-P represents the accumulated particle energy in the cell. Solve the effect of the particle phase on the fluid phase in each time step, calculate the momentum and energy equations. S303, CFD model setting and flow field calculation, including: 1) Add a vapor model on the gas-liquid interface; the gas is composed of protective gas and vapor, and the vapor model considers the back pressure caused by gas evaporation, and the phase change between gas and liquid is completed above the critical temperature at the metal evaporation point; Add a vapor model on the gas-liquid interface; (3) where, is the positive net element flux on the gas-liquid interface, , , T and represent the atomic mass, Boltzmann constant, surface temperature and evaporation coefficient, respectively; the saturated vapor pressure is obtained from the Clausius-Clapeyron equation, which establishes a quantitative relationship between the change of saturated vapor pressure with temperature.

[0034] Based on the vapor model, the fluid mass loss equation considering the back pressure is as follows: (4) where, α F1 , p F1 , p F2 and represent the liquid volume fraction, liquid density, gas density and mass loss, and the mixed density formula is p F =α F1 p F1 +α F2 p F2 p0, L v , , T , T vand R u represent the environmental gas pressure, latent heat of vaporization, molar mass, temperature, gas evaporation point and universal gas constant, respectively.

[0035] The gas follows the ideal gas equation, and the gas mass transfer is represented by the VOF method, which is expressed as follows: (5) where, represents the liquid fluid velocity, liquid and gas volume fractions. represent the gas volume fraction, pressure, specific gas constant, respectively.

[0036] In order to accurately simulate the evolution of the generated metal vapor and the environmental gas, the gas phase is composed of argon gas and metal vapor, and the mass fraction of the metal vapor is represented by ψ i (i = 1, 2); therefore, the thermophysical properties of the gas phase, such as viscosity, thermal conductivity, density and specific heat, etc., change with the mass fraction of the metal particle powder. Since the velocity of the vapor and the liquid is too large, the Knudsen layer is used here to represent the slip boundary between the two.

[0037] 2) Set up the heat source model.

[0038] (6) where, represents the laser heat, represents the specific heat of the fluid. The heat source used in the present application is a Gaussian laser heat source, which considers the reflection and absorption of the laser on the wall of the molten pool The formula is as follows: (7) represents the transient laser absorption rate, which is related to the laser incidence angle θ and the material emissivity ε .

[0039] The laser incident on the substrate will cause heat loss, including convective heat transfer, radiation heat dissipation, vapor shielding. The formula is: (8) represents the laser heat loss, represents the convective heat transfer, radiation heat dissipation, vapor shielding heat loss, respectively. Among them, ε represent the reference temperature, latent heat of vaporization, convective heat transfer coefficient, Stefan-Boltzmann constant, material emissivity, respectively.

[0040] 3) Set up the fluid momentum source model.

[0041] Momentum source is expressed as: (9) where, , is the surface tension, Marangoni flow and fluid flow resistance. Carman-Kozeny model is used to calculate the flow resistance in the Mushy zone (Mushy), and to inhibit the liquid flow under the condition based on the modified Metzner model.

[0042] 4) Calculate the momentum, energy equation; Based on the above steam model, heat source model and fluid momentum source, the momentum, energy expression in the fluid domain is obtained as: (10) where, and indicate the momentum and heat transfer from particles to fluid, which is obtained by the above formula (2); is the other source term induced by the fluid; wherein, H , , is the specific enthalpy, fluid thermal conductivity and unit matrix, through which the velocity field, temperature field and pressure field in the CFD domain are obtained, and the velocity field, temperature field, pressure field and other data are updated, and the volume fraction, momentum and energy information of the fluid are further obtained by the following formula to transfer to the DEM domain; Fluid phase to particle phase: (11) where, C d is the drag coefficient, which is usually approximated as: d = 24 / Re p ;Re p is the Reynolds number of the particle, which is expressed as = ; h p-F is the heat convection coefficient, which is based on the Ranz-Marshall correction, is the Prandtl number of the fluid phase, is the particle surface area; the force of the fluid phase on the particle, which causes splashing, erosion and other phenomena, as shown in Figure 4 .

[0043] In the above momentum and energy information circulation process of the particle phase and the fluid phase, the in formula (1) is derived from formula (11), the and in formula (2) are derived from formula (11), and the The source is derived from equation (2).

[0044] The above steps are repeated until the simulation converges or a specified time step is reached. The post-processed results are shown in FIG. 6. Figure 4 As shown in FIG. 6, the model is suitable for Al-based, Ti-based, high-temperature alloy, and other metals.

[0045] Embodiments Referring to Figure 4 FIG. 6 shows a schematic diagram of the multiphase and multiphysics simulation results of 316L stainless steel microselective laser powder bed fusion. The scanning rate is 1000 mm / s, and the power is 50 W. The calculation area is 0.3 × 0.2 × 0.4 mm, and the substrate and gas height are 200 μm, respectively. After the laser is loaded on the substrate, the powder and the substrate begin to melt, and after reaching the evaporation point, the metal vapor erupts on the pool wall. As the light spot moves, the back end of the pool begins to solidify. The interaction between the vapor-powder particles-pool is shown in the figure, the powder particles are affected by the back pressure of the metal vapor and sputter outwards, while the powder near the melt track is affected by the gas drag force and moves into the pool. The gas in front of the pool is not excited, and the powder bed does not change. The model simulates the complex interaction between laser-powder particles-pool-vapor through CFD-DEM bidirectional coupling, so as to predict the complex spatter behavior of gas-solid-liquid multiphase interaction.

[0046] The present application is described in reference to flowchart and / or block diagram of the method, device (system), and computer program product according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the flow Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks.

[0047] These computer program instructions can also be stored in a computer-readable memory that can guide the computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including instruction devices, which implement the flow Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks.

[0048] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0049] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, rather than limit the technical solutions of the present application. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A high fidelity numerical calculation method of CFD-DEM strongly coupled micro-selection zone laser powder bed fusion, characterized in that, The method comprises the following steps: S1, constructing a CFD-DEM coupled calculation domain, and adding metal powder particles in the calculation domain; S2, initializing the calculation domain; S3, in the DEM model, tracking the metal powder particles, obtaining the interaction force between the metal powder particles, obtaining the linear heat conduction transmission energy between the metal powder particles and the fluid under the laser heat source, and further obtaining the volume fraction of the metal powder particles in the calculation domain, and the momentum and energy of the metal powder particles to the fluid phase; the fluid includes a liquid phase and a gas; S4, adding a vapor model to the gas-liquid interface in the CFD model, the vapor model adding a liquid phase mass loss equation considering back pressure; setting a heat source model and a fluid momentum source model in the CFD model, the heat source model considering heat loss; combining the volume fraction of the metal powder particles and the momentum and energy of the metal powder particles to the fluid phase obtained in S2, to calculate the volume fraction of the fluid in the calculation domain, and the momentum and energy of the fluid phase to the metal powder particle phase; S5, applying the volume fraction of the fluid and the momentum and energy of the fluid phase to the metal powder particle phase in S4 to S3, repeating the alternating iteration process in S3 and S4 until a set time is reached.

2. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S1, after constructing the CFD-DEM coupled calculation domain, the calculation domain is meshed, and the meshes of the molten pool region and the vapor region in the calculation domain are encrypted.

3. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, The heat source in S3 and S4 is a Gaussian laser beam, which includes multiple reflections and absorptions of laser wall to light.

4. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S3, the interaction force of the metal powder particles includes drag force, gravity and contact force.

5. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S3, the equation of linear heat conduction transmission energy is: （1） wherein, , and represent laser-induced heat, powder heat conduction and fluid-induced heat, respectively; and represent particle thermal conductivity and particle geometric mean, respectively; is the distance between the particle barycenter and the laser spot center.

6. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S3, the formula of the momentum and energy of the metal powder particles to the fluid phase is: （2） where, represents the momentum of the particle phase acting on the fluid phase, F d is the drag force, and are the time steps of the CFD and DEM solvers, respectively; is the number of particle particles; Q F-P represents the accumulated particle energy in a cell; solve the action of the particle phase on the fluid phase within each time step, calculate the momentum, energy equation.

7. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S4, the vapor model is: （3） wherein, is the positive net elemental flux at the gas-liquid interface, , , T and represent the atomic mass, the Boltzmann constant, the surface temperature and the evaporation coefficient, respectively, is the saturated vapor pressure; The liquid phase mass loss equation is: （4） where, α F1 , ρ F1 , ρ F2 and represent liquid volume fraction, liquid density, gas density and mass loss, p0, L v , , T , T v and R u represent ambient gas pressure, latent heat of vaporization, molar mass, temperature, gas evaporation point and universal gas constant, respectively.

8. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S4, the heat loss includes convective heat transfer, radiation heat dissipation and vapor shielding.

9. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S4, the fluid momentum source model includes gravity, surface tension, Marangoni flow and fluid flow resistance.

10. The CFD-DEM strongly coupled microselective laser powder bed fusion high fidelity numerical calculation method according to claim 1, characterized in that, In S4, the process equation of the momentum and energy of the fluid phase to the metal powder particle phase is: （11） wherein C d C is the drag coefficient, Re p Re is the Reynolds number of the particles, h p-F h is the heat convection coefficient, Pr is the Prandtl number of the fluid phase, A is the particle surface area.

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