Regulation and control method for anisotropic mechanical properties of molten formed metal of laser powder bed

Abstract

The invention discloses a method for regulating and controlling anisotropic mechanical properties of molten formed metal of a laser powder bed, and belongs to the technical field of additive manufacturing. The method comprises the following steps: constructing a data set related to laser power, powder laying thickness, scanning speed and molten pool size; the mapping relation between the molten pool size and anisotropy is determined; constructing an anisotropic crystal plasticity theory framework based on the molten pool morphology; anisotropy data of the target macrostructure is obtained, and the anisotropy mechanical property of the component under the target forming scheme is calculated; and laser powder bed melting forming parameters of the target macrostructure are optimized. According to the method, support can be provided for anisotropy regulation and control and forming parameter selection of a forming structure by combining crystal plasticity finite element simulation under a small number of experiments according to the anisotropy characteristics of molten metal of the laser powder bed.

Description

Technical Field

[0001] This invention belongs to the field of additive manufacturing technology, specifically relating to a method for controlling the anisotropic mechanical properties of metals formed by laser powder bed fusion. Background Technology

[0002] Laser Powder Bed Fusion (LPBF), as a core technology in metal additive manufacturing, combines the processing of special metals with integrated forming, and has broad application prospects in the aerospace field. This technology uses a high-energy laser beam as a heat source to manufacture target components by sweeping layer by layer through a powder bed. However, the selection of forming parameters makes it difficult to predict the anisotropic mechanical behavior of the formed components, limiting the application of this technology. Anisotropy is an indicator for evaluating the physical and chemical properties of materials in different directions. For materials formed by LPBF, the level of anisotropy is directly controlled by the microstructure, which is closely related to the selected forming parameters. The variable microstructure makes it difficult to predict the level of anisotropy of the formed material, potentially leading to failure risks. Currently, there is a lack of suitable anisotropic mechanical prediction models and control methods for LPBF materials.

[0003] Currently, research on optimizing LPBF molding quality mainly focuses on process parameter control, microstructure simulation, and composition-process-structure coupling. Although existing technologies have improved LPBF molding quality at different levels, they still have the following limitations: There is a lack of accurate predictive models for anisotropic mechanical behavior: existing methods are mostly based on macroscopic experiments or microstructure simulations, which cannot quantify and predict the anisotropic mechanical properties of molded parts under different process parameters (such as the differences in tensile strength and yield strength in different directions).

[0004] The crystal plasticity model is disconnected from the LPBF process: Although the traditional crystal plasticity theory can describe the deformation behavior of materials, it does not incorporate the unique morphological features of the LPBF melt pool (such as melt pool boundary density and fine grain boundary distribution), resulting in insufficient prediction accuracy of the model for LPBF forming materials.

[0005] Highly dependent on experimental calibration: Existing control methods require a large number of trial and error experiments to optimize process parameters, which is costly and time-consuming, making it difficult to meet the rapid design needs of high-performance components.

[0006] Therefore, developing a crystal plasticity theory that takes into account the microstructural characteristics of laser powder bed fusion molding materials is an effective way to improve the prediction accuracy of anisotropic mechanical behavior. Summary of the Invention

[0007] The technical problem to be solved: To overcome the shortcomings of existing technologies, this invention provides a method for controlling the anisotropic mechanical properties of metals formed by laser powder bed fusion (LPBF). This method directly integrates the molten pool morphology with the theoretical framework of anisotropic crystal plasticity, and uses a molten pool size parameter correction model to predict and control the anisotropic mechanical properties, thereby achieving accurate prediction and active control of the anisotropic mechanical properties of LPBF formed metals.

[0008] The technical solution of this invention is: a method for controlling the anisotropic mechanical properties of metals formed by laser powder bed melting, the specific steps of which are as follows: Construct a process parameter-molten pool size mapping dataset: Obtain the length, width, and height dimensions of the molten pool under different combinations of process parameters such as laser power, scanning speed, and powder coating thickness through experiments or simulations, and form a dataset; Establish the mapping relationship between molten pool size and anisotropy: Through macroscopic mechanical experiments and microscopic structural observations, determine the mapping relationship between the length, width, and height dimensions of the molten pool and the anisotropic mechanical properties of the material; Constructing a theoretical framework for the plasticity of anisotropic crystals based on melt pool size: The influence of molten pool size on anisotropic mechanical behavior is quantified into two types of factors: the influence of fine grain boundaries at the molten pool boundary on solid solution slip and dislocation evolution, and the density of the molten pool boundary per unit distance. Based on these two types of factors, a modified model for solid solution strengthening and dislocation density evolution in crystal plasticity theory is established, and a constitutive relation incorporating molten pool size characteristics is established, thus completing the construction of the crystal plasticity theory framework. Predicting the anisotropic properties of the target component: A set of LPBF forming parameters is preset for the target macroscopic component. The corresponding melt pool size is queried from the dataset and input into the crystal plasticity theory framework for finite element simulation. The predicted mechanical properties of the component in each direction are calculated. Optimize molding process parameters: Compare the predicted mechanical properties of the component in each direction with the target performance requirements, iteratively adjust the preset molding parameters and repeat the simulation calculation until the predicted performance meets the requirements, thereby determining the optimal LPBF molding process parameters.

[0009] A further technical solution of the present invention is that the dataset also includes mapping data of material type and printing angle, which is used to characterize the relationship between the molten pool morphology and the construction direction. A further technical solution of the present invention is: the macroscopic mechanical experiment includes sampling along different directions for tensile testing, and the microstructure observation includes measuring the molten pool size and grain morphology using a metallographic microscope or a scanning electron microscope.

[0010] A further technical solution of the present invention is as follows: the specific way to introduce the density of the molten pool boundary within a unit distance into the solid solution slip strengthening model is to calculate the actual density of the molten pool boundary within a unit length, and use this density value to correct the calculation coefficient of slip resistance in the solid solution slip strengthening model; The specific method for introducing the influence of fine grain boundaries at the molten pool boundary on solid solution slip and dislocation evolution into the dislocation density evolution model is as follows: the grain size of the fine grain boundaries at the molten pool boundary is determined through microscopic observation, and the calculation parameters of the dislocation slip free path in the dislocation density evolution model are corrected by the grain size.

[0011] A further technical solution of the present invention is: the modified model for solid solution strengthening is specifically as follows: The modified model for solid solution strengthening is the solid solution slip resistance of the crystal lattice. The expression is as follows:

[0012] in, It is the basic sliding resistance of the sliding surface. The influence of molten pool morphology on anisotropic solid solution slip resistance; anisotropic slip resistance Used to characterize the differences in slip resistance caused by grain boundary density at the edge of the molten pool in different directions. It is expressed as:

[0013] in, It is the reduction factor for slip resistance. It is the length of the molten pool. It is the width of the molten pool. It is the slip resistance when the grain boundary density is highest at the edge of the molten pool per unit length; This indicates the angle between the laser sweeping direction and the load application direction.

[0014] A further technical solution of the present invention is: the dislocation density evolution correction model includes an edge dislocation density evolution model, and the expression of the edge dislocation density evolution model is as follows:

[0015] in, It is a slip system The nominal freedom process, For slip system edge dislocation density, For slip system screw dislocation density; For slip system slip ratio; These are Burgers vector values. It is the maximum slip length between dislocations within the slip plane. It is the minimum length required for two edge dislocations to annihilate; Maximum slip length and minimum annihilation length The expression is as follows:

[0016] in, It is the shear modulus; It is a slip system Solving for shear stress; These are anisotropic mechanical behavior material parameters used to characterize the influence of fine grains at the edge of the molten pool on dislocation slip annihilation in different directions. Their expression is as follows:

[0017] in, It is the basic annihilation coefficient. These are parameters representing the influence of fine grain boundaries in different directions on dislocation slip annihilation. It is the length of the molten pool. It is the width of the molten pool.

[0018] A further technical solution of the present invention is: the dislocation density evolution correction model further includes a screw dislocation density evolution model, the expression of which is as follows:

[0019] in, It is the dislocation climb rate, and its expression is:

[0020] in, It is the self-diffusion coefficient. It is the activation volume of dislocation climbing. It is the Boltzmann constant. It's temperature. It is activation energy.

[0021] A further technical solution of the present invention is: the selection basis for the preset set of LPBF forming parameters for the target macroscopic component includes the usage scenario requirements of the target macroscopic structure and the material characteristics of the forming metal; if the target macroscopic structure is a load-bearing component in the aerospace field, the preset forming parameters should prioritize the mechanical performance stability under high temperature environment, and correspondingly select a higher initial value of laser power and a thinner initial value of powder thickness.

[0022] A further technical solution of the present invention is that the iterative adjustment of the preset molding parameters is performed using an optimization algorithm, including gradient descent or genetic algorithm, to automatically and efficiently search for the optimal process parameter window that meets the target performance. A method for manufacturing a metal component by laser powder bed fusion molding includes: The optimal LPBF forming process parameters were determined using the method for controlling the anisotropic mechanical properties of metals oriented towards laser powder bed fusion forming. Based on the optimal LPBF forming process parameters, the target metal component is manufactured using a laser powder bed melting device, and the component has the expected anisotropic mechanical properties.

[0023] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method.

[0024] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0025] Beneficial effects The beneficial effects of this invention are as follows: By using the Mechanical Threshold Stress flow model and the dislocation density basis hardening model, we can effectively simulate the anisotropic mechanical behavior of laser powder bed molten materials under both room temperature and high temperature environments. By modifying the model parameters in the Mechanical Threshold Stress flow model and the dislocation density basis hardening model, this calculation method can achieve high prediction accuracy for the anisotropic mechanical behavior of materials with different microstructural characteristics.

[0026] This invention constructs an anisotropic crystal plasticity theoretical framework that integrates the morphological characteristics of the molten pool, and directly correlates process parameters (laser power, scanning speed, etc.) with microscopic mechanical mechanisms (dislocation slip, solid solution strengthening) through the size of the molten pool (length, width, height). This enables quantitative calculation and simulation of macroscopic anisotropic behavior (such as yield strength and tensile strength in different directions), significantly improving the accuracy and reliability of predictions.

[0027] Traditional methods for predicting the mechanical behavior of laser powder bed molten materials typically require mechanical experiments to provide a calibration benchmark for the prediction model under the given forming parameters. However, this invention introduces a modified model related to the microstructure of the molten pool into the framework of crystal plasticity theory, achieving high prediction accuracy even without experimental conditions. This is because the optimized model effectively captures the deformation modes of laser powder bed molten materials with different microstructures, reducing reliance on experimental calibration and thus enabling accurate predictions even in the absence of experimental data. Attached Figure Description

[0028] Figure 1 This is a flowchart of the method for controlling the anisotropic mechanical properties of metals formed by laser powder bed melting, as described in this invention. Figure 2 This is a schematic diagram illustrating the angular definition of the molten pool morphology and load direction as described in this invention; Figure 3 This is a comparison chart of the finite element simulation results and experimental results of crystal plasticity described in this invention. Detailed Implementation

[0029] The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0030] Currently, research on optimizing the molding quality of LPBF mainly focuses on process parameter control, microstructure simulation, or composition-process-structure coupling. For example: The existing technology CN115740498B proposes a three-element coupling control method for optimizing the forming quality of selective laser melting. By combining process simulation, composition optimization and structural design, it improves the comprehensive performance of magnesium alloy parts. However, this method relies on a large number of experimental verifications and has not established a quantitative prediction model for anisotropic mechanical behavior.

[0031] The prior art CN119114967A discloses a three-dimensional manufacturing method for metal grains based on dual-laser powder bed melting. It controls the grain morphology through dual-laser collaborative scanning to achieve regional customization of part performance. However, the focus is on grain structure optimization and does not involve mechanism modeling and prediction of anisotropic mechanical properties.

[0032] The existing technology CN118313197A provides a simulation method for determining the printing process of single-crystal austenitic stainless steel. It uses the finite element method and the phase field method to simulate the evolution of microstructure, which helps to understand the single crystal formation mechanism. However, it does not extend to the quantitative analysis of anisotropic mechanical behavior, and the model does not consider the direct influence of the molten pool morphology on the mechanical properties.

[0033] To address the aforementioned problems, this invention provides a method for controlling the anisotropic mechanical properties of metals formed by laser powder bed fusion, the specific steps of which are as follows: Step 1: Construct a process parameter-molten pool size mapping dataset: Through experiments or simulations, obtain data on the length, width, and height of the molten pool under different combinations of process parameters such as laser power, scanning speed, and powder thickness, and form a dataset; Step 2: Establish the mapping relationship between molten pool size and anisotropy: Through macroscopic mechanical experiments and microscopic structural observations, determine the mapping relationship between the length, width, and height dimensions of the molten pool and the anisotropic mechanical properties of the material; Step 3: Constructing a theoretical framework for anisotropic crystal plasticity based on melt pool size: The influence of molten pool size on anisotropic mechanical behavior is quantified into two types of factors: the influence of fine grain boundaries at the molten pool boundary on solid solution slip and dislocation evolution, and the density of the molten pool boundary per unit distance. Based on these two types of factors, a modified model for solid solution strengthening and dislocation density evolution in crystal plasticity theory is established, and a constitutive relation incorporating molten pool size characteristics is established, thus completing the construction of the crystal plasticity theory framework. Step 4: Predict the anisotropic properties of the target component: Preset a set of LPBF forming parameters for the target macroscopic component, query the corresponding melt pool size from the dataset, and input it into the crystal plasticity theory framework for finite element simulation to calculate the predicted mechanical properties of the component in each direction. Step 5: Optimize molding process parameters: Compare the predicted mechanical properties of the component in each direction with the target performance requirements, iteratively adjust the preset molding parameters and repeat the simulation calculation until the predicted performance meets the requirements, thereby determining the optimal LPBF molding process parameters.

[0034] The above technical solution will be further explained below with reference to the accompanying drawings: In one embodiment, refer to Figure 1 As shown, this embodiment provides a method for controlling the anisotropic mechanical properties of metals formed by laser powder bed melting, specifically including the following steps: Step 1: Construct a dataset related to laser power, powder thickness, scanning speed, and molten pool size: The dataset includes data on the mapping relationship between different combinations of manufacturing parameters and molten pool size. Specifically, it includes datasets related to the molten pool morphology and size for various component parameter combinations that may affect the molten pool morphology and size, such as different materials, laser power, powder thickness, scanning speed, and printing angle, in order to find relevant data on the molten pool morphology and size under this combination of parameters.

[0035] Step 2: Establish the mapping relationship between molten pool size and anisotropy: By combining macroscopic tensile testing and microscopic observation, the dimensions of the molten pool in the length, width, and height, as well as its anisotropy, were established. Specifically, for various materials, a small number of tensile tests were conducted to obtain the mechanical behavior of the specimens in each direction. Microscopic morphology observation experiments were then used to establish the morphological and dimensional characteristics of the molten pool, including its length, width, and height, and to establish the mapping relationship between the molten pool morphology and dimensions and its anisotropic mechanical behavior.

[0036] Step 3: Construct a theoretical framework for anisotropic crystal plasticity based on melt pool morphology: Based on the response relationship between the three-dimensional distribution state of the molten pool (length, width, and height) and anisotropic mechanical behavior, the influence of the molten pool boundary on crystal deformation and dislocation slip is established, and a correction model for solid solution strengthening and dislocation density evolution is established. By simplifying the influence of the molten pool morphology on anisotropic mechanical behavior into two categories, namely (1) the influence of fine grain boundaries of the molten pool on solid solution slip and dislocation evolution and (2) the density of the molten pool boundary per unit distance, the influence of the molten pool morphology is introduced into the solid solution slip strengthening model and the dislocation density evolution model, respectively. Through the response relationship between the three-dimensional distribution state of the molten pool (length, width, and height) and anisotropic mechanical behavior in step two, the model parameters of the long-width plane, long-height plane, and wide-height plane are corrected, and the construction of the anisotropic crystal plasticity theoretical framework based on the molten pool morphology is completed. Specifically, the anisotropic crystal plasticity theory model is based on the continuum theory, as follows: , in, It is the total deformation gradient, which can be decomposed into the elastic component. and plastic parts The deformation velocity gradient in the current state can be expressed as: , in, The elastic deformation velocity gradient, This represents the rate gradient of plastic deformation caused by dislocation slip. and These are the elastic deformation rate tensor and the plastic deformation rate tensor, respectively. and These represent the elastic spin tensor and the plastic spin tensor, respectively. The plastic deformation rate gradient... It can be expressed as: , in, To activate the total number of slip systems, For slip system slip ratio, and They are respectively slip systems The unit vectors of the normal to the deformed slip surface and the slip direction. Considering the contribution of mechanical twins to the deformation, the plastic deformation rate gradient can be expressed as: , in, It is a twin system Volume fraction of twins. and They are twin systems The unit normal vector of the slip surface and the unit vector of the slip direction. The first term on the right-hand side of the equation represents the effect of dislocations on the plastic deformation rate gradient, and the second term represents the effect of twins on the plastic deformation rate gradient.

[0037] Based on the Orowan mechanism of dislocation slip and the thermal activation theory, the flow model can be expressed as: , in, It is a slip system dislocation density, It is the size of the Burgers vector. It is the reference velocity for dislocation slip. It is activation energy. It is the Boltzmann constant. It's temperature. and These are engineering parameters, and their value range is... , . It is a slip system Effective solution of shear stress. The lattice solid solution slip resistance of dislocation slip can be described as: , in, It is the basic sliding resistance of the sliding surface. This relates to the influence of molten pool morphology on anisotropic solid solution slip resistance. Anisotropic slip resistance. Used to characterize the differences in slip resistance caused by grain boundary density at the edge of the molten pool in different directions. It can be expressed as: , in, It is the reduction factor for slip resistance. It is the length of the molten pool. It is the width of the molten pool. It is the slip resistance at the point where the grain boundary density is highest per unit length of the molten pool edge. This indicates the angle between the laser sweeping direction and the load application direction. Figure 2 As shown.

[0038] The effective solution for shear stress can be calculated using the following formula: , in, It is a slip system Solving for shear stress It is a Hall-Petch item. It is a slip system Resistance to dislocation slip control. Hall-Petch type item. It can be expressed as: , in, It is the Hall-Petch slope, used to characterize the response relationship between average grain size and slip resistance. It is the average grain size. Dislocation slip resistance. The format is as follows: , in, It is the shear modulus. It is a characterization of slip system With slip system The latent hardening matrix of inter-interactions. and These are edge dislocations and screw dislocations, used to characterize the shear deformation and helical twisting between the lattice and dislocations. The evolution model of edge dislocation density is as follows: , in, It is a slip system The nominal freedom process. It is the maximum slip length between dislocations within the slip plane. It is the minimum length required for two edge dislocations to annihilate. Maximum slip length. and minimum annihilation length The expression is as follows: , in, These are anisotropic mechanical behavior material parameters used to characterize the influence of fine grains at the edge of the molten pool on dislocation slip annihilation in different directions. Their expression is as follows: , in, It is the basic annihilation coefficient. These are parameters representing the influence of fine grain boundaries in different directions on dislocation slip annihilation. The evolution model of screw dislocation density is as follows: , in, It is the dislocation climb rate, and its expression is: , in, It is the self-diffusion coefficient. It is the activation volume of dislocation climbing.

[0039] Plastic deformation rate gradient In this context, the shear strain rate of twinning deformation can be expressed as: , in, It is a characteristic twin shear. The rate of evolution of the twin integral can be expressed as: , in, It is the twin nucleation rate. The volume of the newly formed twin can be expressed as: , Twin nucleation rate It can be represented as: , in, It is the reference twin rate. It is a twin system Analytical shear stress, It is the resistance to twin nucleation. This is the rate-dependent power coefficient. The critical resistance to twinning deformation can be decomposed into: , in, and They are slip systems The fundamental resistance to twin deformation and Hall-Petch-like terms. Used to characterize twin systems The effect of stress concentration caused by dislocation slip on twin nucleation. (Hall-Petch type) The expression is as follows: , in, This refers to the Hall-Petch slope related to twinning. It also relates to the effect of dislocation slip on twin nucleation. It can be expressed as: , in, It is the magnitude of the twinned Burgers vector. It is a latent hardening matrix.

[0040] The model parameters used in the anisotropic crystal plasticity theory framework based on molten pool morphology are influenced by the material they are applied to. The basic parameters related to the non-molten pool morphology can be obtained from databases, literature, and other means depending on the material used.

[0041] Step 4: Obtain anisotropy data of the target macroscopic structure: For the target macrostructure, the forming parameters of laser powder bed melting are preset. The corresponding molten pool size is queried from the dataset established in step one. The relevant parameters of the molten pool size are introduced into the crystal plasticity theory framework constructed in step three to calculate the deformation behavior of the target macrostructure and establish the anisotropy level of the mechanical properties of the macrostructure. Step 5: Optimize the laser powder bed melting parameters for the target macroscopic structure: The anisotropic mechanical properties of the target macrostructure calculated in step four are compared with the target properties. The molten pool size of the target macrostructure is determined by repeating step four trial calculations. The corresponding forming parameter combination is selected from the data set constructed in step one to determine the optimized value of the laser powder bed melting forming parameters of the target macrostructure.

[0042] By incorporating parameters related to the molten pool size into the crystal plasticity theoretical framework constructed in step three, Figure 3 Demonstrated as Figure 2 The simulation and experimental results of the specimens in the defined X, Y, and Z directions are compared. The simulation results basically predict the mechanical behaviors of the experimental specimens in the three directions, such as yielding, strengthening, and softening.

[0043] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for controlling the anisotropic mechanical properties of laser powder bed fusion formed metals, the method comprising: The specific steps are as follows: ​ Constructing process parameter-melt pool size mapping dataset: through experiments or simulations, obtain melt pool length, width and height size data under different laser power, scanning speed and powder laying thickness process parameter combinations to form a dataset; Establishing a mapping relationship between melt pool size and anisotropy: through macro-mechanical experiments and microstructure observation, determine the mapping relationship between melt pool length, width, height and material anisotropic mechanical properties; Constructing anisotropic crystal plasticity theory framework based on melt pool size: Quantify the influence of melt pool size on anisotropic mechanical behavior as two factors: the influence of melt pool boundary fine grain boundary on solid solution slip and dislocation evolution, and the density of melt pool boundary per unit distance; based on the two factors, establish a modified model of solid solution strengthening and dislocation density evolution in crystal plasticity theory, establish a constitutive relationship integrating melt pool size characteristics, that is, complete the construction of the crystal plasticity theory framework; Predicting the anisotropic properties of the target component: preset a set of LPBF forming parameters for the target macro component, query the melt pool size corresponding to the set of parameters from the dataset, and input it into the crystal plasticity theory framework for finite element simulation to calculate the predicted mechanical property values of the component in each direction; Optimizing the forming process parameters: compare the predicted mechanical property values of the component in each direction with the target performance requirements, iteratively adjust the preset forming parameters and repeat the simulation calculation until the predicted performance meets the requirements, thereby determining the optimal LPBF forming process parameters.

2. The method of claim 1, wherein the method is for controlling the mechanical properties of the laser powder bed fusion formed metal. The dataset also includes material type and printing angle mapping relationship data to represent the relationship between melt pool morphology and build direction.

3. The method of claim 1, wherein the method is characterized by: The macro-mechanical experiments include tensile testing along different directions, and the microstructure observation includes using a metallographic microscope or a scanning electron microscope to measure the melt pool size and grain morphology.

4. The method of claim 1, wherein the method is characterized by: The specific way of introducing the density of melt pool boundary per unit distance into the solid solution slip strengthening model is to calculate the actual density of melt pool boundary per unit length, and to modify the calculation coefficient of slip resistance in the solid solution slip strengthening model with the density value; The specific way of introducing the influence of melt pool boundary fine grain boundary on solid solution slip and dislocation evolution into the dislocation density evolution model is to determine the grain size of the melt pool boundary fine grain boundary through micro-observation, and to modify the calculation parameter of dislocation slip free path in the dislocation density evolution model with the grain size.

5. The method of claim 4, wherein the method is for controlling the mechanical properties of the laser powder bed fusion formed metal. The modified model of solid solution strengthening is specifically: The modified model of the solid solution strengthening is the solid solution sliding resistance of the crystal lattice The expression is as follows: wherein, is the basal slip resistance of the slip plane, is the effect of the melt pool topography on the anisotropic solid solution slip resistance; the anisotropic slip resistance is used to characterize the difference in slip resistance due to the grain boundary density at the edge of the melt pool in each direction, is expressed as: wherein, is a reduction factor of the glide resistance, is a length of the molten pool, is a width of the molten pool, is a glide resistance at the highest grain boundary density per unit length of the molten pool edge; denotes an angle of the laser scanning direction with respect to the load application direction.

6. The method of claim 5, wherein the method is for controlling the mechanical properties of the laser powder bed fusion formed metal. The dislocation density evolution modified model includes a dislocation density evolution model, and the expression of the dislocation density evolution model is as follows: wherein is the nominal free path of the slip system , is the dislocation density of the slip system , is the screw dislocation density of the slip system ; is the slip rate of the slip system ; is the Burgers vector value, is the maximum slip length between dislocations in the slip plane, is the minimum length required for two edge dislocations to annihilate. Maximum slip length And minimum annihilation length The expressions are as follows: wherein, G is the shear modulus; is the slip system solving shear stress; is a parameter of anisotropic mechanical behavior material, used to characterize the influence of fine-grained grain at the edge of the molten pool on the annihilation of dislocation slip in different directions, and its expression is as follows: wherein, is the base annihilation coefficient, is a parameter for the effect of fine grain boundaries in different directions on the annihilation of dislocation slip, is the length of the melt pool, is the width of the melt pool.

7. The method of claim 6, wherein the method is for controlling the mechanical properties of the laser powder bed fusion formed metal anisotropy. The dislocation density evolution modified model also includes a screw dislocation density evolution model, and the expression of the screw dislocation density evolution model is as follows: wherein is the dislocation climb velocity, which is expressed as: wherein, is the self-diffusion coefficient, is the activation volume for dislocation climb, is the Boltzmann constant, is the temperature, is the activation energy.

8. The method of claim 1, wherein the method is for controlling the mechanical properties of a laser powder bed fusion formed metal. The selection of the set of LPBF forming parameters for the target macro component is based on the use scenario requirements of the target macro structure and the material properties of the formed metal; if the target macro structure is a load-bearing component in the aerospace field, the preset forming parameters need to prioritize the stability of mechanical properties in high-temperature environments, and a higher initial laser power value and a thinner initial powder laying thickness value are selected accordingly.

9. The method of claim 1, wherein the method is for controlling the mechanical properties of a laser powder bed fusion formed metal anisotropy. The preset molding parameter is adjusted iteratively by using an optimization algorithm, including gradient descent method or genetic algorithm, to automatically and efficiently search for an optimal process parameter window satisfying the target performance.

10. A method of manufacturing a laser powder bed fusion formed metal component, characterized by, The application further provides a laser powder bed fusion (LPBF) molding method, comprising the following steps: determining the optimal LPBF molding process parameters by using the method for regulating the anisotropic mechanical properties of laser powder bed fusion molding metals according to any one of claims 1-9; manufacturing a target metal component by using a laser powder bed fusion equipment based on the optimal LPBF molding process parameters, and the component has the expected anisotropic mechanical properties.

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