An integrated numerical simulation method for process-fatigue performance of additive manufacturing metal

Abstract

The application discloses a kind of metal " process-fatigue performance " integrated numerical simulation method of additive manufacturing, comprising: step S1, the assumption of additive manufacturing numerical simulation boundary condition;Step S2, the construction of metal additive manufacturing transient macroscopic temperature field model;Step S3, the dynamic simulation of metal additive manufacturing fatigue crack propagation;Step S4, simulation calculation and result export.The model established by the application can simulate the influence of forming process on temperature field in the process of metal additive manufacturing on three-dimensional scale, and calculate the corresponding residual stress field using different temperature field, so as to calculate the fatigue life of metal additive manufacturing parts under different residual stress, finally provide a feasible finite element simulation method for studying the influence of defects (residual stress) caused by forming process in the process of metal additive manufacturing on fatigue performance.

Description

Technical Field

[0001] This invention belongs to the field of numerical simulation technology for additive manufacturing of metallic materials, and specifically relates to an integrated numerical simulation method for the "process-fatigue performance" of additively manufactured metals. Background Technology

[0002] With the rapid development of aerospace, shipbuilding, chemical engineering, and biomedicine, the requirements for material properties are becoming increasingly stringent. Titanium alloys, due to their low density, excellent specific strength, good corrosion resistance, and high-temperature mechanical properties, have been widely used in additive manufacturing technology. However, the large cyclic temperature gradient during additive manufacturing, along with the high thermal conductivity and large coefficient of thermal expansion of titanium alloys, can lead to significant residual stress during part manufacturing, causing microcracks and even fractures, which can adversely affect the fatigue performance and load-bearing stability of the parts in subsequent operations. Therefore, studying the impact of defects (residual stress) caused by additive manufacturing processes on the fatigue performance of workpieces is of great significance. On the other hand, because metal additive manufacturing is a complex multi-scale, multi-physics coupling problem, traditional research methods are significantly limited. Current experimental equipment and conditions make it difficult to monitor and obtain the distribution of temperature and stress fields inside the molten pool in real time. Using the finite element method (FEM) for parametric simulation can intuitively obtain the distribution of temperature and stress fields inside the molten pool during additive manufacturing. By using the finite element method, suitable forming process parameters can be found more quickly and easily, thereby optimizing the distribution of temperature and stress fields inside the molten pool during the metal additive manufacturing process. Ultimately, this improves the defects generated by the additive manufacturing process and enables the control and improvement of the fatigue performance of metal additive manufactured parts.

[0003] Currently, scholars both domestically and internationally have conducted a series of numerical modeling and computational simulation analyses to address the complex multi-scale, multi-physics coupling problems in metal additive manufacturing. These studies primarily focus on temperature field, thermal stress, molten pool morphology, microstructure simulation, and the development and control methods of residual stress. However, research on the impact of residual stress on the subsequent service performance and safety of components is relatively limited. Therefore, establishing a finite element simulation method for the "process-defect (residual stress)-performance" model in titanium alloy metal additive manufacturing is particularly important.

[0004] References

[0005] [1]Dong L, Correia JPM, Barth N, et al. Finite element simulations oftemperature distribution and of densification of a titanium powder during metal laser sintering[J]. Additive Manufacturing, 2017,13:37-48.

[0006] [2]Kolossov S,Boillat E,Glardon R,et al.3D FE simulation fortemperature evolution in the selective laser sintering process[J].International Journal of Machine Tools and Manufacture,2004,44(2-3):117-123.

[0007] [3]Xiao Z, Chen C, Zhu H, et al. Study of residual stress in selective laser melting of Ti6Al4V[J]. Materials&Design, 2020,193:108846. Summary of the Invention

[0008] The purpose of this invention is to provide an integrated numerical simulation method for the "process-fatigue performance" of additive manufacturing metals, in order to solve the problem that there is currently a lack of systematic finite element numerical simulation methods for the "process-fatigue performance" of metal additive manufacturing technology.

[0009] To achieve the above objectives, the present invention adopts the following technical solution.

[0010] An integrated numerical simulation method for additive manufacturing metal "process-fatigue properties" includes the following steps:

[0011] Step S1: Assumptions for boundary conditions in additive manufacturing numerical simulation;

[0012] Step S2: Construction of the transient macroscopic temperature field model for metal additive manufacturing;

[0013] Step S3: Dynamic simulation of fatigue crack propagation in metal additive manufacturing;

[0014] Step S4: Simulation calculation and result export.

[0015] Specifically, the assumptions for the boundary conditions of the additive manufacturing numerical simulation in step S1 include:

[0016] Assumption 1: The entire temperature field model solidification process only involves three material states: powder, molten, and alloy.

[0017] Assumption 2: The entire powder bed is considered a homogeneous and continuous medium, and the effect of heat conduction from the workpiece to the experimental platform is ignored;

[0018] Assumption 3: Throughout the process, the thermophysical parameters of the material are related to temperature;

[0019] Assumption 4: The simulation region is divided into cubic units, and each unit is an element;

[0020] Assumption 5: In order to reduce the amount of calculation during the simulation, the surface heat transfer coefficient of the object is regarded as a constant value;

[0021] Assumption 6: Neglect the stress of unmelted powder.

[0022] Specifically, the construction of the transient macroscopic temperature field model for metal additive manufacturing described in step S2 is as follows:

[0023] Step S21: Select a Gaussian distributed heat source as the laser heat source for metal additive manufacturing. The heat source model is then expressed as:

[0024]

[0025] Where k is the heat source concentration coefficient; A represents the absorption rate of laser energy by the powder; and P represents the heat source power. ω represents the laser penetration depth of TC4 titanium alloy powder, ω represents the laser radius, and x, y, z represent the spatial coordinates of the heat source.

[0026] Step S22: After the heat source is applied to the workpiece, heat conduction occurs on the surface and inside the workpiece. The three-dimensional transient heat transfer equation for additive manufacturing is expressed as:

[0027]

[0028] Where ρ(T) is the material density / kg·m 3 ;c p (T) is the specific heat capacity / J / kg·K; T is the temperature of the powder system / K; t is the interaction time / s; k(T) is the thermal conductivity / W / m·K; Q(x, y, z) is the heat generated per volume in the component; thermal conductivity, specific heat capacity and density are all functions of temperature T;

[0029] Step S23: Determine the initial conditions for heat conduction.

[0030] The initial conditions for the temperature distribution in the powder bed at time t=0 are determined by the following formula:

[0031] T(x,y,z,t)| t＝0 =T0(x,y,z) (3)

[0032] Where T0(x, y, z) is the ambient temperature of 293.15 K; T(x, y, z, t)| t＝0 Initial temperature / K;

[0033] Step S24: Determine the boundary conditions for thermal conduction.

[0034] The boundary conditions refer to the heat exchange between the object's surface and the surrounding medium, and are determined by the following formula:

[0035]

[0036] Where S represents the surface attached to the applied heat flux, convection, and radiation; n is the normal vector of surface S; q is the input heat flux; T0 and T are the ambient temperature and the temperature of the powder system, respectively; h c It is the thermal convection coefficient / W / m 2 / K;ε t σ is the material emissivity; σ is the Stefan-Boltzmann radiation constant, σ = 5.67 × 10⁻⁶. -8 W / m 2 K 4 .

[0037] Specifically, the dynamic simulation of fatigue crack propagation in metal additive manufacturing described in step S3 includes the following steps:

[0038] Step S31: Determine the stress and strain in metal additive manufacturing.

[0039] Metal additive manufacturing processes generate significant thermal gradients and localized shrinkage during the solidification stage, which in turn produce residual stresses and strains in the manufactured parts. These stresses and strains are determined by the following formula:

[0040] {ε}=[D] -1 {σ}+{ε p}+{ε t} (5)

[0041] Where {ε} is the total stress vector; [D] is the elastic stiffness matrix; {σ} is the stress vector; {ε p} is a plastic strain carrier; {ε t} is the thermal strain vector;

[0042] Thermal strain is calculated using the following formula:

[0043] εt =α e ΔT=α e (TT ref (6)

[0044] Where, α e T is the coefficient of thermal expansion; T is the instantaneous temperature; T ref This is a reference temperature, typically taken as the temperature at t=0.

[0045] The Prandtl-Reuss plasticity equations are represented by the following set of equations:

[0046]

[0047] Among them, σ′ x σ′ y and σ′ z dλ represents the deviatoric stress in the x, y, and z directions; dλ is the instantaneous positive constant of the proportion.

[0048] In summary, for a system based on Cartesian coordinates, equation (5) can be given by the following set of equations:

[0049]

[0050] Where E is the elastic modulus; G is the shear modulus; and μ is Poisson's ratio.

[0051] Step S32: Determine the residual stress in metal additive manufacturing.

[0052] Neglecting the stress in the unmelted powder, the stress field problem is simplified to a thermo-elastic-plastic problem in the molten region. In this case, the plastic deformation follows the Von Mises yield criterion, and the equivalent stress σ is used. e Also known as Von Mises stress, it is used to assess residual stress, equivalent stress σ. e Determined by the following formula:

[0053]

[0054] Where, σ x σ y and σ z These are the X, Y, and Z components of the stress; and These are the shear stress components along the XY, YZ, and ZX planes, respectively.

[0055] Step S33: Determine the fatigue life of the metal additive manufacturing workpiece.

[0056] The relationship between strain and low-cycle fatigue crack initiation life under strain control is described using the Basquin-Coffin-Manson general method:

[0057]

[0058] Where, σ′ f and σ′ f denoted by , where b and c are the fatigue strength coefficient and fatigue ductility coefficient, respectively;

[0059] The accumulated fatigue damage in each cycle is characterized by a damage evolution equation, expressed by the following formula:

[0060]

[0061] The simulation process is as follows: First, the maximum stress of each element mesh is extracted using a program, then the stress amplitude of the element is calculated, the strain amplitude is obtained according to the Ramberg-Osgood equation, and then the fatigue life of the element is predicted by equation (10). The fatigue damage accumulated in each cycle can be calculated using the damage evolution equation (11). The accumulated fatigue damage in each cycle is accumulated. If the accumulated damage value reaches the threshold, the element in the CT sample model will fail, thereby simulating the crack propagation process.

[0062] Specifically, the simulation calculation and result export described in step S4 are performed by exporting the calculation results according to the following steps:

[0063] Step S41: Construct a three-dimensional numerical simulation model based on the assumptions made in Step S1 regarding the boundary conditions of the additive manufacturing numerical simulation.

[0064] Step S42: Based on the transient macroscopic temperature field model of metal additive manufacturing constructed in step S2, program the temperature field subroutine;

[0065] Step S43: Based on the transient macroscopic fatigue crack model of metal additive manufacturing constructed in step S3, program the fatigue life subroutine.

[0066] Step S44: Import the programmed temperature field subroutine into the ABAQUS software, input the assumptions about the simulation boundary conditions into the three-dimensional numerical simulation model and perform calculations to obtain the three-dimensional numerical simulation results of the transient macroscopic temperature field in metal additive manufacturing.

[0067] Step S45: Based on the temperature-related mechanical property parameters of metal additive manufacturing input in step S3, change the three-dimensional model type, import the prepared fatigue life subroutine into the ABAQUS software, and use the temperature field simulation results of step S44 as a prerequisite to perform structural analysis calculations on the constructed three-dimensional numerical simulation model. This will yield the three-dimensional numerical simulation results of the transient macroscopic stress field of metal additive manufacturing and the fatigue life results of the three-dimensional finite element model of metal additive manufacturing.

[0068] Step S46: Change the additive manufacturing process parameters and repeat steps S41 to S45 to obtain the fatigue life simulation results under different metal additive manufacturing processes.

[0069] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0070] 1. This invention provides an integrated numerical simulation method for the "process-fatigue performance" of additive manufacturing metals, which solves the problem of the lack of a systematic finite element numerical simulation method for the "process-defect (residual stress)-performance" in current metal additive manufacturing technology;

[0071] 2. This invention can reproduce the evolution of the physical state of the molten pool and the corresponding temperature field changes during the titanium alloy metal additive manufacturing process on a three-dimensional scale. The simulation results are accurate and intuitive, providing a better research scheme for further study of the titanium alloy metal additive manufacturing process.

[0072] 3. Compared with traditional in-situ measurement methods, this invention proposes a numerical simulation model for additive manufacturing based on physical processes. By compiling subroutines, a three-dimensional numerical simulation of the additive manufacturing process of titanium alloys is performed on the ABAQUS finite element simulation platform. This can save a lot of manpower and material resources, and is economical, efficient, energy-saving and environmentally friendly.

[0073] 4. Compared to studying the optimization of metal additive manufacturing processes, defects, and performance in isolation, this invention establishes a connection between metal additive manufacturing processes and fatigue performance by linking defects (residual stress). It is an integrated numerical simulation method with fatigue performance feedback. This provides a new approach for more systematically improving the fatigue performance of metal additive manufacturing parts using finite element simulation. Attached Figure Description

[0074] Figure 1 This is a flowchart of an integrated numerical simulation method for additive manufacturing metal "process-fatigue performance" according to the present invention;

[0075] Figure 2 This invention provides a three-dimensional numerical simulation model of an integrated numerical simulation method for additive manufacturing metal "process-fatigue performance";

[0076] Figure 3 This is a flowchart illustrating the subroutine of the transient macroscopic temperature field model for metal additive manufacturing.

[0077] Figure 4 This is a flowchart illustrating a subroutine for simulating transient macroscopic fatigue cracks in metal additive manufacturing.

[0078] Figure 5 These are the thermophysical parameters of TC4 titanium alloy;

[0079] Figure 6The results are three-dimensional simulations of the temperature field (a), residual stress (b), and fatigue crack and life (c) curves of the TC4 titanium alloy additive manufacturing in Example 1. Detailed Implementation

[0080] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] like Figure 1 As shown, this invention proposes an integrated numerical simulation method for additive manufacturing metal "process-fatigue performance", including the following steps:

[0082] Step S1: Assumptions for boundary conditions in additive manufacturing numerical simulation;

[0083] Step S2: Construction of the transient macroscopic temperature field model for metal additive manufacturing;

[0084] Step S3: Dynamic simulation of fatigue crack propagation in metal additive manufacturing;

[0085] Step S4: Simulation calculation and result export.

[0086] Specifically, the assumptions for the boundary conditions of the additive manufacturing numerical simulation in step S1 include:

[0087] Assumption 1: The entire temperature field model solidification process only involves three material states: powder, molten, and alloy.

[0088] Assumption 2: The entire powder bed is considered a homogeneous and continuous medium, and the effect of heat conduction from the workpiece to the experimental platform is ignored;

[0089] Assumption 3: Throughout the process, the thermophysical parameters of the material are related to temperature;

[0090] Assumption 4: The simulation region is divided into cubic units, and each unit is an element;

[0091] Assumption 5: In order to reduce the amount of calculation during the simulation, the surface heat transfer coefficient of the object is regarded as a constant value;

[0092] Assumption 6: Neglect the stress of unmelted powder.

[0093] Specifically, the construction of the transient macroscopic temperature field model for metal additive manufacturing described in step S2 is as follows:

[0094] Step S21: The magnitude, distribution, and conduction of heat applied to the powder bed affect the physical state transformation of the molten pool metal and the temperature field distribution. In the additive manufacturing process, the laser directly acts on the powder bed surface to form heating spots. Therefore, a Gaussian heat source is selected as the laser heat source for metal additive manufacturing in the simulation. The heat source model is then expressed as:

[0095]

[0096] Where k is the heat source concentration coefficient; A represents the absorption rate of laser energy by the powder; and P represents the heat source power. ω represents the laser penetration depth of TC4 titanium alloy powder, ω represents the laser radius, and x, y, z represent the spatial coordinates of the heat source.

[0097] Step S22: After the heat source is applied to the workpiece, heat conduction occurs on the surface and inside the workpiece. The three-dimensional transient heat transfer equation for additive manufacturing is expressed as:

[0098]

[0099] Where ρ(T) is the material density / kg·m 3 c p (T) is the specific heat capacity / J / kg·K; T is the temperature of the powder system / K; t is the interaction time / s; k(T) is the thermal conductivity / W / m·K; Q(x, y, z) is the heat generated per volume in the component; thermal conductivity, specific heat capacity and density are all functions of temperature T;

[0100] Step S23: Determine the initial conditions for heat conduction.

[0101] Before solving the heat conduction problem, it is necessary to determine the initial and boundary conditions for heat conduction. The simulation environment of this invention is room temperature, so the initial conditions for the temperature distribution in the powder bed at time t=0 are determined by the following formula:

[0102] T(x,y,z,t)| t＝0 =T0(x,y,z) (3)

[0103] Where T0(x, y, z) is the ambient temperature of 293.15 K; T(x, y, z, t)| t＝0 Initial temperature / K;

[0104] Step S24: Determine the boundary conditions for thermal conduction.

[0105] The boundary condition refers to the heat exchange between the object's surface and the surrounding medium. The boundary condition selected in this invention stipulates that the object's surface undergoes free heat exchange; therefore, the boundary condition can be determined by the following formula:

[0106]

[0107] Where S represents the surface attached to the applied heat flux, convection, and radiation; n is the normal vector of surface S; q is the input heat flux; T0 and T are the ambient temperature and the temperature of the powder system, respectively; h c It is the thermal convection coefficient / W / m 2 / K;ε t σ is the material emissivity; σ is the Stefan-Boltzmann radiation constant, σ = 5.67 × 10⁻⁶. -8 W / m 2 K 4 .

[0108] Specifically, the dynamic simulation of fatigue crack propagation in metal additive manufacturing described in step S3 includes the following steps:

[0109] Step S31: Determine the stress and strain in metal additive manufacturing.

[0110] Metal additive manufacturing processes generate significant thermal gradients and localized shrinkage during the solidification stage, which in turn produce residual stresses and strains in the manufactured parts. These stresses and strains are determined by the following formula:

[0111] {ε}=[D] -1 {σ}+{ε p}+{ε t} (5)

[0112] Where {ε} is the total stress vector; [D] is the elastic stiffness matrix; {σ} is the stress vector; {ε p} is a plastic strain carrier; {ε t} is the thermal strain vector;

[0113] Thermal strain is calculated using the following formula:

[0114] ε t =α e ΔT=α e (TT ref (6)

[0115] Where, α e It is the coefficient of thermal expansion; T is the instantaneous temperature; T ref This is a reference temperature, typically taken as the temperature at t=0.

[0116] The Prandtl-Reuss plasticity equations are represented by the following set of equations:

[0117]

[0118] Among them, σ′ x σ′ y and σ′ zdλ represents the deviatoric stress in the x, y, and z directions; dλ is the instantaneous positive constant of the proportion.

[0119] In summary, for a system based on Cartesian coordinates, equation (5) can be given by the following set of equations:

[0120]

[0121] Where E is the elastic modulus; G is the shear modulus; and μ is Poisson's ratio.

[0122] Step S32: Determine the residual stress in metal additive manufacturing.

[0123] Neglecting the stress in the unmelted powder, the stress field problem is simplified to a thermo-elastic-plastic problem in the molten region. In this case, the plastic deformation follows the Von Mises yield criterion, and the equivalent stress σ is used. e Also known as Von Mises stress, it is used to assess residual stress, equivalent stress σ. e Determined by the following formula:

[0124]

[0125] Where, σ x σ y and σ z These are the X, Y, and Z components of the stress; and These are the shear stress components along the XY, YZ, and ZX planes, respectively.

[0126] Step S33: Determine the fatigue life of the metal additive manufacturing workpiece.

[0127] The relationship between strain and low-cycle fatigue crack initiation life under strain control is described using the Basquin–Coffin–Manson general method:

[0128]

[0129] Where, σ′ f and σ′ f denoted by , where b and c are the fatigue strength coefficient and fatigue ductility coefficient, respectively;

[0130] The accumulated fatigue damage in each cycle is characterized by a damage evolution equation, expressed by the following formula:

[0131]

[0132] The simulation process is as follows: First, the maximum stress of each element mesh is extracted using a program, then the stress amplitude of the element is calculated, the strain amplitude is obtained according to the Ramberg-Osgood equation, and then the fatigue life of the element is predicted by equation (10). The fatigue damage accumulated in each cycle can be calculated using the damage evolution equation (11). The accumulated fatigue damage in each cycle is accumulated. If the accumulated damage value reaches the threshold, the element in the CT sample model will fail, thereby simulating the crack propagation process.

[0133] Specifically, the simulation calculation and result export described in step S4 are performed by exporting the calculation results according to the following steps:

[0134] Step S41: Construct a three-dimensional numerical simulation model based on the assumptions made in Step S1 regarding the boundary conditions of the additive manufacturing numerical simulation.

[0135] Step S42: Based on the transient macroscopic temperature field model of metal additive manufacturing constructed in step S2, program the temperature field subroutine;

[0136] Step S43: Based on the transient macroscopic fatigue crack model of metal additive manufacturing constructed in step S3, program the fatigue life subroutine.

[0137] Step S44: Import the programmed temperature field subroutine into the ABAQUS software, input the assumptions about the simulation boundary conditions into the three-dimensional numerical simulation model and perform calculations to obtain the three-dimensional numerical simulation results of the transient macroscopic temperature field in metal additive manufacturing.

[0138] Step S45: Based on the temperature-related mechanical property parameters of metal additive manufacturing input in step S3, change the three-dimensional model type, import the prepared fatigue life subroutine into the ABAQUS software, and use the temperature field simulation results of step S44 as a prerequisite to perform structural analysis calculations on the constructed three-dimensional numerical simulation model. This will yield the three-dimensional numerical simulation results of the transient macroscopic stress field of metal additive manufacturing and the fatigue life results of the three-dimensional finite element model of metal additive manufacturing.

[0139] Step S46: Change the additive manufacturing process parameters and repeat steps S41 to S45 to obtain the fatigue life simulation results under different metal additive manufacturing processes.

[0140] Example 1

[0141] The following uses TC4 titanium alloy as an example to simulate the fatigue life of TC4 titanium alloy under different additive manufacturing processes using the method of the present invention.

[0142] 1) A three-dimensional numerical simulation model is constructed based on the assumptions about the boundary conditions of the additive manufacturing numerical simulation. The constructed three-dimensional numerical simulation model is as follows: Figure 2 As shown;

[0143] 2) Based on the constructed transient macroscopic temperature field model of metal additive manufacturing, the temperature field subroutine is programmed. The subroutine flowchart is as follows: Figure 3 As shown;

[0144] 3) Based on the constructed transient macroscopic fatigue crack model of metal additive manufacturing, a fatigue life subroutine was programmed. The subroutine flowchart is as follows: Figure 4 As shown;

[0145] 4) Import the programmed temperature field subroutine into the ABAQUS software, input the boundary conditions into the three-dimensional numerical simulation model and perform calculations to obtain the three-dimensional numerical simulation results of the transient macroscopic temperature field in metal additive manufacturing.

[0146] 5) Based on the temperature-related mechanical property parameters of TC4 titanium alloy additive manufacturing input in step 3), as shown in Tables 1 and 2 below, change the three-dimensional model type, import the prepared fatigue life subroutine into the ABAQUS software, and use the temperature field simulation results in step 4) as a prerequisite to perform structural analysis calculations on the constructed three-dimensional numerical simulation model. This will yield the three-dimensional numerical simulation results of the transient macroscopic stress field in TC4 titanium alloy additive manufacturing and the fatigue life results of the three-dimensional finite element model of metal additive manufacturing.

[0147] 6) By changing the additive manufacturing process parameters and repeating steps 1) to 5), the fatigue life simulation results of TC4 titanium alloy additive manufacturing under different processes can be obtained.

[0148] Table 1 Temperature-dependent mechanical properties of TC4 titanium alloy

[0149]

[0150] Table 2 Mechanical property parameters of TC4 titanium alloy

[0151]

[0152] like Figure 6 As shown, from Figure 6 The verification of the temperature field in (a) shows that the simulation method of this invention provides temperature predictions that more closely approximate experimental results; from Figure 6 The verification of the residual stress field in (b) shows that the negative correlation between power and residual stress obtained by the simulation method of this invention is consistent with that in the literature. [3] Consistent. Furthermore, based on the study of the accuracy of the model's predictions in the temperature field and residual stress field using the method of this invention, integrated simulation of additive manufacturing "process-fatigue performance" can be carried out, thereby studying the influence of different additive manufacturing process parameters on fatigue performance and providing a theoretical basis for optimizing additive manufacturing processes.

[0153] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent implementations for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the protection scope of the technical solution of the present invention.

Claims

1. An integrated numerical simulation method for additive manufacturing metal "process-fatigue performance", characterized in that, Includes the following steps: Step S1: Assumptions for boundary conditions in additive manufacturing numerical simulation; Step S2: Construction of the transient macroscopic temperature field model for metal additive manufacturing; Step S21: Select a Gaussian distributed heat source as the laser heat source for metal additive manufacturing. The heat source model is then expressed as: （1）； in, Here, A represents the heat source concentration coefficient; P represents the absorption rate of laser energy by the powder; and P represents the heat source power. ω represents the laser penetration depth of TC4 titanium alloy powder, ω represents the laser radius, and x, y, z represent the spatial coordinates of the heat source. Step S22: After the heat source is applied to the workpiece, heat conduction occurs on the surface and inside the workpiece. The three-dimensional transient heat transfer equation for additive manufacturing is expressed as: （2）； in, Material density / ; Specific heat capacity / T is the temperature of the powder system in K; t is the interaction time in seconds; k(T) is the thermal conductivity. ; It is the heat generated per volume within the component; thermal conductivity, specific heat capacity, and density are all functions of temperature T. Step S23: Determine the initial conditions for heat conduction. The initial conditions for the temperature distribution in the powder bed at time t=0 are determined by the following formula: （3）； in, The ambient temperature was 293.15K. Initial temperature / K; Step S24: Determine the boundary conditions for thermal conduction. The boundary conditions refer to the heat exchange between the object's surface and the surrounding medium, and are determined by the following formula: （4）； Where S represents the surface attached to the applied heat flux, convection, and radiation; n is the normal vector of surface S; and q is the input heat flux. and These are the ambient temperature and the temperature of the powder system, respectively. It is the thermal convection coefficient / ; It is the material emissivity; σ is the Stefan-Boltzmann radiation constant, σ= ; Step S3: Dynamic simulation of fatigue crack propagation in metal additive manufacturing; Step S31: Determine the stress and strain in metal additive manufacturing. Metal additive manufacturing processes generate significant thermal gradients and localized shrinkage during the solidification stage, which in turn produce residual stresses and strains in the manufactured parts. These stresses and strains are determined by the following formula: （5）； in, It is the total stress vector; It is the elastic stiffness matrix; It is a stress vector; It is a plastic strain carrier; It is the thermal strain vector; Thermal strain is calculated using the following formula: （6）； in, It is the coefficient of thermal expansion; It is the instantaneous temperature; This is the reference temperature, taken as the temperature at t=0; The Prandtl-Reuss plasticity equations are represented by the following set of equations: （7）； in, , and These are the deviatoric stresses in the x, y, and z directions; It is the instantaneous positive constant of the ratio; In summary, for a system based on Cartesian coordinates, equation (5) can be given by the following set of equations: （8）； in, It is the elastic modulus; It is the shear modulus; It is Poisson's ratio; Step S32: Determine the residual stress in metal additive manufacturing. Neglecting the stress in the unmelted powder, the stress field problem is simplified to a thermo-elastic-plastic problem in the molten region. In this case, plastic deformation follows the Von Mises yield criterion, and equivalent stress is used. Also known as Von Mises stress, it is used to assess residual stress, equivalent stress. Determined by the following formula: （9）； in, , and These are the X, Y, and Z components of the stress; , and These are the shear stress components along the XY, YZ, and ZX planes, respectively. Step S33: Determine the fatigue life of the metal additive manufacturing workpiece. The relationship between strain and low-cycle fatigue crack initiation life under strain control is described using the Basquin–Coffin–Manson general method: （10）； in, and denoted by , where b and c are the fatigue strength coefficient and fatigue ductility coefficient, respectively; The accumulated fatigue damage in each cycle is characterized by a damage evolution equation, expressed by the following formula: （11）； The simulation process is as follows: First, the program is used to extract the maximum stress of each element mesh, then the stress amplitude of the element is calculated, the strain amplitude is obtained according to the Ramberg–Osgood equation, and then the fatigue life of the element is predicted by equation (10). The fatigue damage accumulated in each cycle can be calculated by the damage evolution equation (11). The accumulated fatigue damage in each cycle is accumulated. If the accumulated damage value reaches the threshold, the element in the CT sample model will fail, thereby simulating the crack propagation process. Step S4: Simulation calculation and result export.

2. The integrated numerical simulation method for additive manufacturing metal "process-fatigue performance" according to claim 1, characterized in that, The assumptions for the boundary conditions of the additive manufacturing numerical simulation in step S1 include: Assumption 1: The entire temperature field model solidification process only involves three material states: powder, molten, and alloy. Assumption 2: The entire powder bed is considered a homogeneous and continuous medium, and the effect of heat conduction from the workpiece to the experimental platform is ignored; Assumption 3: Throughout the process, the thermophysical parameters of the material are related to temperature; Assumption 4: The simulation region is divided into cubic units, and each unit is an element; Assumption 5: In order to reduce the amount of calculation during the simulation, the surface heat transfer coefficient of the object is regarded as a constant value; Assumption 6: Neglect the stress of unmelted powder.

3. The integrated numerical simulation method for additive manufacturing metal "process-fatigue performance" according to claim 1, characterized in that, The simulation calculation and result export described in step S4 are performed as follows: The calculation results are exported according to the following steps: Step S41: Construct a three-dimensional numerical simulation model based on the assumptions made in Step S1 regarding the boundary conditions of the additive manufacturing numerical simulation. Step S42: Based on the transient macroscopic temperature field model of metal additive manufacturing constructed in step S2, program the temperature field subroutine; Step S43: Based on the transient macroscopic fatigue crack model of metal additive manufacturing constructed in step S3, program the fatigue life subroutine. Step S44: Import the programmed temperature field subroutine into the ABAQUS software, input the assumptions about the simulation boundary conditions into the three-dimensional numerical simulation model and perform calculations to obtain the three-dimensional numerical simulation results of the transient macroscopic temperature field in metal additive manufacturing. Step S45: Based on the temperature-related mechanical property parameters of metal additive manufacturing input in step S3, change the three-dimensional model type, import the prepared fatigue life subroutine into the ABAQUS software, and use the temperature field simulation results of step S44 as a prerequisite to perform structural analysis calculations on the constructed three-dimensional numerical simulation model. This will yield the three-dimensional numerical simulation results of the transient macroscopic stress field of metal additive manufacturing and the fatigue life results of the three-dimensional finite element model of metal additive manufacturing. Step S46: Change the additive manufacturing process parameters and repeat steps S41 to S45 to obtain the fatigue life simulation results under different metal additive manufacturing processes.

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