Metal fatigue crack initiation simulation method for coupling holes and microstructures

Abstract

The invention discloses a metal fatigue crack initiation simulation method for coupling holes and microstructures, which comprises the following steps of: firstly, establishing a microscopic scale model by collecting microstructure characteristic data and hole distribution data in a metal material, obtaining basic parameters by combining a mechanical property test result, and deducing and calculating microscopic orthotropic parameters; the method comprises the following steps of: scanning internal defects of an alloy, establishing a hole defect model with the same characteristic information according to the scanned internal defects of the alloy, extracting key holes through finite element simulation to establish a geometric model, introducing a stress concentration coefficient, and replacing a shear stress amplitude calculation mode in a Tanaka-Mura dislocation theoretical formula with a stress amplitude calculation mode. And micro-scale numerical simulation of fatigue crack initiation of the metal material with the hole defect is completed. According to the method, factors such as the microstructure and the internal holes of the material are considered, and the finite element simulation technology is combined, so that accurate prediction of the microscale metal fatigue crack initiation life can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of numerical simulation of metal fatigue crack initiation, and in particular relates to a metal fatigue crack initiation simulation method of coupling holes and microstructures. Background Art

[0002] Fatigue crack initiation generally accounts for about 90% of its service life. Therefore, predicting fatigue crack initiation is crucial to ensure the safety and reliability of the structure. Generally speaking, the microstructural characteristics and potential defects inside the material have an important influence on fatigue crack initiation. Especially in parts made by additive manufacturing, holes are common internal defects. Their existence not only changes the stress distribution of the material and causes stress concentration, but also accelerates the initiation of fatigue cracks. At the same time, microstructural characteristics (such as grain size and orientation) also play an important role in the process of fatigue evolution.

[0003] Previous studies usually reveal the specific mechanism of these factors on fatigue crack initiation through experimental verification and theoretical analysis, but the simulation of fatigue crack initiation at the microscale still faces challenges. Although the Tanaka-Mura dislocation accumulation theory model is a model that describes the fatigue crack initiation process, the model describes the mechanism of dislocation accumulation and slip band cracking at the microscale and estimates the life cycle of crack initiation, but it still has limitations in the accuracy of crack initiation life calculation due to the presence of stress concentration when considering the complex effects of pores and microstructural characteristics on crack initiation. Summary of the invention

[0004] The purpose of the present invention is to provide a metal fatigue crack initiation simulation method for coupling holes and microstructures in order to address the deficiencies in the prior art. The method collects microstructure characteristic data and hole distribution data inside the metal material, establishes a microscale model, introduces a stress concentration factor, replaces the shear stress amplitude calculation method in the Tanaka-Mura dislocation theory formula with a stress amplitude calculation method, completes the microscale numerical simulation of fatigue crack initiation of metal materials containing defective holes, and can more accurately predict the fatigue life of the metal material.

[0005] In order to achieve the above object, the present invention adopts the following technical solution.

[0006] A metal fatigue crack initiation simulation method for coupling pores and microstructures comprises the following steps: Step S1, establishing a global model of the sample and establishing a micro-sized sub-model according to the structure of the global model, setting a cyclic load on the global model, and simulating the stress-strain response of the material under the cyclic load; Step S2, obtaining the size and shape information of the internal grains of the metal material, using the Voronoi algorithm to establish a material microstructure model, and determining it as the submodel in step S1, the microstructure model includes the microscopic characteristics of grain size and grain orientation; Step S3, observing and analyzing the structure according to the stress-strain response obtained in step S1 and the size and shape information of the internal grains of the metal material obtained in step S2, obtaining basic parameters and inferring and calculating microscopic orthogonal anisotropy parameters; Step S4, based on the characteristic information of the hole defects inside the metal material under CT scanning, a hole defect model with the same characteristic information is established, key holes of the hole defect model are identified through finite element simulation, and the key holes are extracted; Step S5, based on the key holes extracted in step S4, a model characterizing the hole defect characteristics inside the metal material is established, and the stress distribution state under different hole sizes, positions, and shape characteristics is simulated using finite element software to obtain the mathematical relationship between the hole defect characteristics and the stress concentration factor; Step S6, substituting the stress concentration factor obtained in step S5 into the Tanaka-Mura dislocation theory to correct the formula; Step S7, according to the formula corrected by Tanaka-Mura dislocation theory in step S6, combined with the sub-model, the Python language is used to complete the secondary development of ABAQUS, realize the numerical simulation of fatigue crack initiation of metal materials containing hole defects, and obtain the crack initiation life and the specific location of the crack.

[0007] Specifically, the sub-model described in step S1 is constructed at the stress concentration area of ​​the metal part, and its size is determined according to the crack initiation growth, while taking into account the grain size and microstructural characteristics to capture the microscopic mechanism of crack initiation and expansion. In the sub-model, the grains are given random orientation to simulate the random arrangement of actual materials; slip is set, and the nucleation position of fatigue cracks is determined by calculating the average shear stress on the slip band. The boundary conditions and loads of the global model are set according to the actual working conditions or test conditions. The boundary conditions are extracted from the global model and locally refined at the sub-model boundaries to ensure the calculation accuracy; the load distribution is dynamically adjusted according to the crack initiation situation to truly reflect the mechanical behavior during the crack initiation process.

[0008] Specifically, the Voronoi algorithm is used to establish the material microstructure model in step S2, and the model building process is as follows: Step S21, using MATLAB software to randomly generate coordinate points within a specified area; Step S22, connecting the generated coordinate points to form a triangular network, so as to obtain the circumcenters of these triangles, and generating Voronoi polygons by connecting the circumcenters of these triangles; Step S23: Use a dedicated Python script to import the Voronoi polygon information into ABAQUS in text format, establish an ideal grain feature model, and assign random grain orientations to the grains.

[0009] Specifically, the basic parameters obtained in step S3 and the microscopic orthogonal anisotropy parameters inferred and calculated include elastic modulus E, Poisson's ratio , shear modulus G; the microscopic orthogonal anisotropy parameters are inferred and calculated, and the microstructure of the material is obtained, observed and analyzed using common experimental testing techniques, thereby indirectly inferring its orthogonal anisotropy parameters. The inference calculation process is: According to the linear elastic material, based on the generalized Hooke's law, the fully anisotropic material constitutive equation of the material is: ; For microscopic materials, the orthotropic anisotropy is: ; The calculated relationship of microscopic orthogonal anisotropy parameters is: ; ; ; In the above formula, , , Respectively indicate that the materials x, y, z Direction of positive stress (normal stress); , , Respectively indicate that the materials xy、yz、zx Shear stress (tangential stress) in the plane; the stiffness matrix C is a 6×6 symmetric matrix with a total of 21 independent elastic constants; The series of parameters describes the elastic properties of the material, i =1,2,3,...,n, j =1,2,3,...,n, n is a positive integer; , , Respectively indicate that the materials x, y, z Direction of positive strain (normal strain); , , Respectively indicate that the materials xy、yz、zx Shear strain in the plane (tangential strain).

[0010] Specifically, the mathematical relationship between the hole defect characteristics and the stress concentration factor in step S5 is derived as follows: Set the size of the hole: major axis a, minor axis b, and inclination angle θ relative to the loading direction; use the finite element analysis method to calculate the local stress distribution in the grains near the hole, and establish the stress concentration factor K by fitting the finite element simulation results. t The relationship between the hole shape and position: ; In formula (1), D is the distance from the hole center to the sub-model boundary; a is the length of the major axis of the hole ellipse; and b is the length of the minor axis of the hole ellipse.

[0011] Specifically, in step S6, the stress concentration factor obtained in step S5 is substituted into the Tanaka-Mura dislocation theory to perform formula correction, and the process is as follows: The traditional Tanaka-Mura formula mainly considers the crack initiation in homogeneous materials, and its crack initiation life N i The specific calculation formula is: ; In formula (2), d is the slip band length, W is the specific fracture energy per unit area, G is the shear modulus, k is the critical dislocation slip resistance, is the Poisson's ratio, is the average shear stress amplitude over the length of the slip band; In order to simplify the formula, a new parameter η is introduced: ; Therefore, formula (2) becomes: ; However, in actual metal materials, hole defects can cause local stress concentration, so the Taylor factor M is introduced, and the applied fatigue stress amplitude is used instead of the shear stress amplitude, which is expressed as: ; In formula (5), is the mean stress amplitude; Since the critical dislocation slip resistance and fatigue limit stress are in a similar order of magnitude, the approximate factor λ=1 is introduced to linearize formula (5): ; In formula (6), σ e The fatigue life is 10 7 The fatigue limit corresponding to the load of the cycle; Substituting formula (6) into formula (4) and normalizing the dimensions, we get: ; According to Griffith's surface energy criterion, since the surface energy is equal to the specific fracture energy, that is, the γ value is equal to the specific fracture energy per unit area W, formula (7) is finally concretized as: ; The stress concentration near the hole will cause the local stress amplitude Δσ local If the stress amplitude is higher than the average stress amplitude Δσ, then formula (8) becomes: ; In order to calculate the crack initiation life and study the influence of hole stress concentration on the initiation life in the sub-model, the shear stress amplitude is not used in the first calculation of the sub-model, but the stress concentration factor K is used. t Substitute it into the Tanaka-Mura formula to calculate the crack initiation life and get the corrected formula: .

[0012] Specifically, the numerical simulation of fatigue crack initiation of the metal material containing hole defects is implemented in step S7, and the specific process is as follows: Step S71, import the modified Tanaka-Mura formula in step S6 into the Python script of ABAQUS, and define all relevant parameters; Step S72: extract the local stress concentration factor and average stress amplitude around the hole defect from the sub-model through the stress analysis function of ABAQUS, and import these stress data into the modified Tanaka-Mura formula through the Python script interface; Step S73, using the cyclic iteration method, considering the stress accumulation effect under different numbers of cycles, accurately calculate the crack initiation life of each grain containing hole defects, identify the location where the crack first initiates based on the calculation result of the crack initiation life, and mark the crack initiation location in the sub-model through the visualization function of ABAQUS, and generate the corresponding stress cloud map and crack initiation location map.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The method of the present invention quantifies the stress concentration coefficient of the holes inside the metal accurately, so that the influence of the holes on the fatigue performance of the metal material can be more accurately evaluated. Through quantitative analysis, we can deeply understand how the hole defects lead to local stress concentration and promote the initiation and development of cracks.

[0014] 2. The method of the present invention constructs a dual-scale crack initiation finite element model, which not only takes into account the structural characteristics at the macro scale, but also incorporates the material properties at the micro scale, providing a more comprehensive and detailed simulation of the fatigue crack initiation process of metal materials. This dual-scale modeling method helps to more accurately predict the fatigue life of metal materials.

[0015] 3. The method of the present invention proposes a new numerical method to simulate the fatigue crack initiation of metal materials containing holes by modifying the original formula, taking into account the influence of hole defects on stress concentration, which helps to improve the accuracy of fatigue life prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the metal fatigue crack initiation simulation method of coupling pores and microstructures of the present invention; Figure 2 This is a simulation calculation flow chart of the crack initiation model based on the Tanaka-Mura dislocation theory of the present invention; Figure 3 The titanium alloy sample size diagram and microscopic sub-model diagram in the embodiment of the present invention; Figure 4 A schematic diagram of random orientation of grains in a titanium alloy sub-model according to an embodiment of the present invention; Figure 5 It is a schematic diagram of the arrangement of the two lattice structures of the α-phase and β-phase titanium alloys and the generation of the two lattice Voronoi diagrams of the α-phase and β-phase titanium alloys and the assignment of grain orientations in an embodiment of the present invention; Figure 6 Schematic diagram of stress distribution with different hole characteristics; Figure 7 It is a simulation diagram of defect feature information and key hole features under CT scanning; Figure 8 Schematic diagram of the relationship between stress concentration factors of holes with different aspect ratios; Fig. 9 Schematic diagram of crack initiation results without stress concentration and with stress concentration induced by hole defects; Fig.10 The simulation results are verified based on the experimental data in the literature. DETAILED DESCRIPTION

[0017] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the following detailed description is given to each step of the method proposed by the present invention, and it should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0018] Example like Figure 1 and Figure 2 As shown, the present invention discloses a metal fatigue crack initiation simulation method for coupling pores and microstructures, comprising the following steps: Step S1, establishing a global model of the sample and establishing a micro-sized sub-model according to the structure of the global model, setting a cyclic load on the global model, and simulating the stress-strain response of the material under the cyclic load; In this embodiment, the sample is an additively manufactured titanium alloy. A global model of the additively manufactured titanium alloy finite element sample is established based on the test sample. The sample is subjected to finite element simulation to find the position with the largest stress concentration. A sub-model is established at the position with the largest stress concentration, such as Figure 3 As shown, Figure 3 Point A in the middle is the location of maximum stress. Figure 3 B in the middle is the macro region of the global model. Figure 3 Point C in the middle is the microscopic area of ​​the sub-model. Considering that the initiation growth of engineering fatigue crack is generally defined as 0.2 mm, the size of the sub-model is set to 0.5 mm × 0.5 mm. At the same time, the boundary load conditions of the global model are set to the sub-model.

[0019] Step S2, obtaining the size and shape information of the internal grains of the metal material, using the Voronoi algorithm to establish a material microstructure model, and determining it as the submodel in step S1, the microstructure model includes the microscopic characteristics of grain size and grain orientation; In this embodiment, the EBSD technology (electron backscatter diffraction technology) is used to obtain the size and shape data of the internal grains of the titanium alloy, and the Voronoi diagram algorithm modeling is performed according to the data. The specific modeling process of the model is as follows: Step S21, using MATLAB software to randomly generate coordinate points within a specified area; Step S22, connecting the generated coordinate points to form a triangular network, so as to obtain the circumcenters of these triangles, and generating Voronoi polygons by connecting the circumcenters of these triangles; Step S23, using a dedicated Python script to import the Voronoi polygon information into ABAQUS in text format, establish an ideal grain feature model, and assign random grain orientations to the grains; like Figure 4 As shown in the figure, since titanium alloy is a dual-phase polycrystalline material, it is composed of an α phase with a hexagonal lattice structure (hcp) and a β phase with a body-centered cubic lattice structure (bcc) at room temperature, so it is necessary to model its dual-phase characteristics. The final modeling and orientation assignment results are shown in Figure 5 shown.

[0020] Step S3, observing and analyzing the structure according to the stress-strain response obtained in step S1 and the size and shape information of the internal grains of the metal material obtained in step S2, obtaining basic parameters and inferring and calculating microscopic orthogonal anisotropy parameters; In this embodiment, the basic mechanical property parameters such as elastic modulus and Poisson's ratio of the titanium alloy specimen are measured through mechanical property testing experiments. The microstructure of the material is obtained, observed and analyzed using common experimental testing techniques, thereby indirectly inferring its orthotropic parameters. The material parameters of the titanium alloy components are shown in Tables 1 and 2 below, respectively.

[0021] Table 1. Tanaka-Mura dislocation parameters of TC4 titanium alloy ; Table 2. Components of orthotropic elastic stiffness matrix ; According to the linear elastic material, based on the generalized Hooke's law, the fully anisotropic material constitutive equation of the material is: ;

[0022] For microscopic materials, the orthotropic anisotropy is: ;

[0023] The calculation formula of the microscopic orthotropic parameters is: ; ; ;

[0024] In the above formula, , , Respectively indicate that the materials x, y, z Direction of positive stress (normal stress); , , Respectively indicate that the materials xy、yz、zx Shear stress (tangential stress) in the plane; the stiffness matrix C is a 6×6 symmetric matrix with a total of 21 independent elastic constants. The series of parameters describes the elastic properties of the material, i =1,2,3,...,n, j =1,2,3,...,n, n is a positive integer; , , Respectively indicate that the materials x, y, z Direction of positive strain (normal strain); , , Respectively indicate that the materials xy、yz、zx Shear strain in the plane (tangential strain).

[0025] Step S4, based on the characteristic information of the hole defects inside the metal material under CT scanning, a hole defect model with the same characteristic information is established, key holes of the hole defect model are identified through finite element simulation, and the key holes are extracted; like Figure 6 As shown, Figure 6 (a) shows the stress distribution under different grain sizes. Figure 6 (b) shows the shear stress distribution under different grain orientations. Figure 6 (c) shows the shear stress magnitude and distribution changes caused by different hole defects; Figure 6 It can be seen that at the microscopic scale, holes will cause stress concentration in the grains, which in turn causes changes in shear stress; therefore, it is necessary to extract the stress concentration coefficient and modify it in combination with the original Tanaka-Mura dislocation theory formula.

[0026] like Figure 7 As shown in the figure, the hole defects of additively manufactured titanium alloy are inspected by CT micro-tomography, and the basic information such as the size, position, and shape of the internal hole clusters are obtained. A hole defect model with the same characteristic information is established through secondary development of ABAQUS. Since hole defects are often irregular inside the metal, in order to quantitatively characterize the hole defects, the three-dimensional hole defects are equivalent to an ellipsoid. The regular shape of the ellipsoid can be used as a representative model to study the influence of hole defects on the properties of metal materials. The key holes of the model are identified through finite element simulation, and the key holes are extracted to establish a geometric model.

[0027] Step S5, based on the key holes extracted in step S4, a model characterizing the hole defect characteristics inside the metal material is established, and the stress distribution state under different hole sizes, positions, and shape characteristics is simulated using finite element software to obtain the mathematical relationship between the hole defect characteristics and the stress concentration factor; Set the size of the hole: major axis a, minor axis b, and inclination angle θ relative to the loading direction; use the finite element analysis method to calculate the local stress distribution in the grains near the hole, and establish the stress concentration factor K by fitting the finite element simulation results. t The relationship between the hole shape and position is as follows: Figure 8 As shown in Figure 8 (a), the stress concentration coefficient relationship at different distances on the surface of the hole ion model with different aspect ratios is shown. Figure 8 (b) shows the relationship between the stress concentration coefficients of holes with different aspect ratios at different rotation angles. The stress concentration coefficient of the internal holes fitted according to the simulation results is expressed as: ; In formula (1), D is the distance from the hole center to the sub-model boundary, a is the length of the major axis of the hole ellipse, and b is the length of the minor axis of the hole ellipse.

[0028] Step S6, substituting the stress concentration factor obtained in step S5 into the Tanaka-Mura dislocation theory to correct the formula; The traditional Tanaka-Mura formula mainly considers the crack initiation in homogeneous materials, and its crack initiation life N i The specific calculation formula is: ; In formula (2), d is the slip band length, W is the specific fracture energy per unit area, G is the shear modulus, k is the critical dislocation slip resistance, is the Poisson's ratio, is the average shear stress amplitude over the length of the slip band; In order to simplify the formula, a new parameter η is introduced: ; Therefore, formula (2) becomes: ; However, in actual metal materials, hole defects can cause local stress concentration, so the Taylor factor M is introduced, and the applied fatigue stress amplitude is used instead of the shear stress amplitude, which is expressed as: ; In formula (5), is the mean stress amplitude; Since the critical dislocation slip resistance and fatigue limit stress are in a similar order of magnitude, the approximate factor λ=1 is introduced to linearize formula (5): ; In formula (6), σ e The fatigue life is 10 7 The fatigue limit corresponding to the load of the cycle; Substituting formula (6) into formula (4) and normalizing the dimensions, we get: ; According to Griffith's surface energy criterion, since the surface energy is equal to the specific fracture energy, that is, the γ value is equal to the specific fracture energy per unit area W, formula (7) is finally concretized as: ; The stress concentration near the hole will cause the local stress amplitude Δσ local If the stress amplitude is higher than the average stress amplitude Δσ, then formula (8) becomes: ; In order to calculate the crack initiation life and study the influence of hole stress concentration on the initiation life in the sub-model, the shear stress amplitude is not used in the first calculation of the sub-model, but the stress concentration factor K is used. t Substitute it into the Tanaka-Mura formula to calculate the crack initiation life and get the corrected formula: .

[0029] Step S7, according to the formula corrected by Tanaka-Mura dislocation theory in step S6, combined with the sub-model, the Python language is used to complete the secondary development of ABAQUS, to realize the numerical simulation of fatigue crack initiation of metal materials containing hole defects, and to obtain the crack initiation life and the specific location of the crack; In this embodiment, according to the modified formula of Tanaka-Mura dislocation theory in step S6, a special script based on Python programming language is developed, which combines Tanaka-Mura model and finite element analysis technology; by using Python ABAQUS secondary development, combined with the sub-model containing Voronoi diagram in step 2, finite element simulation of crack initiation process is performed, including crack nucleation and interaction, to predict fatigue crack initiation life; specifically: Step S71, import the modified Tanaka-Mura formula in step S6 into the Python script of ABAQUS, and define all relevant parameters; Step S72: extract the local stress concentration factor and average stress amplitude around the hole defect from the sub-model through the stress analysis function of ABAQUS, and import these stress data into the modified Tanaka-Mura formula through the Python script interface; Step S73, using the cyclic iteration method, considering the stress accumulation effect under different numbers of cycles, accurately calculate the crack initiation life of each grain containing hole defects, identify the location where the crack first initiates based on the calculation result of the crack initiation life, and mark the crack initiation location in the sub-model through the visualization function of ABAQUS, and generate the corresponding stress cloud map and crack initiation location map.

[0030] The stress concentration factor K obtained by the above method is t The modified formula of Tanaka-Mura dislocation theory is used to calculate the stress and shear stress amplitude inside the material and simulate the evolution of the microstructure. At the same time, the crack initiation process is simulated, including the nucleation and interaction of the crack, and the influence of crack initiation on the fatigue life of the material is analyzed to predict the fatigue life. The prediction results are as follows: Fig. 9 As shown, Fig. 9 The fatigue crack initiation life and crack initiation path under different stress concentration factors are shown in the figure. Fig. 9 It can be clearly seen that the stress concentration factor, as a key parameter to measure the degree of stress concentration around the hole, has a negative correlation with the crack initiation life. When the stress concentration factor caused by the hole increases, it is easier to promote crack initiation, resulting in a significant shortening of the crack initiation life.

[0031] In order to verify the prediction accuracy of the method of the present invention, the data in the existing literature [Dang L, He X, Tang D, et al. Pore-induced fatigue failure: Critical pore criterion for Ti-6Al-4V alloy manufactured by laser-directed energy deposition [J]. Theoretical and Applied Fracture Mechanics, 2024, 129: 104204.] are selected as shown in Table 3 below. The hole defect is modeled and simulated based on the characteristic parameters of the hole defect in the literature. The simulation results are shown in Table 3. Fig.10 shown.

[0032] Table 3. Selected simulation parameters ; The fatigue life predicted by the method of the present invention and the simulation analysis method given in the existing literature were compared and analyzed, and the results are shown in Table 4 below.

[0033] Table 4. Fatigue data life comparison ; It can be concluded from Table 4 that when the hole equivalent diameter is 51.2 μm, the crack initiation life predicted by the simulation analysis method given in the existing literature is 19619 cycles, while that predicted by the method of the present invention is 18624 cycles. The relative error between the method of the present invention and the actual crack initiation life of 18279 cycles is reduced from 9.8% of the existing simulation method to 1.9%; and when the hole equivalent diameter is 86.8 μm, the relative error between the method of the present invention and the actual crack initiation life of 35602 cycles is reduced from 6.1% of the existing simulation method to 1.1%, indicating that the prediction accuracy of the method of the present invention is higher than that of the simulation analysis method given in the existing literature.

[0034] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A method for simulating metal fatigue crack initiation by coupling pores and microstructures, characterized in that: The following steps are involved: Step S1, establishing a global model of the sample and establishing a micro-sized sub-model according to the structure of the global model, setting a cyclic load on the global model, and simulating the stress-strain response of the material under the cyclic load; Step S2, obtaining the size and shape information of the internal grains of the metal material, using the Voronoi algorithm to establish a material microstructure model, and determining it as the submodel in step S1, the microstructure model includes the microscopic characteristics of grain size and grain orientation; Step S3, observing and analyzing the structure according to the stress-strain response obtained in step S1 and the size and shape information of the internal grains of the metal material obtained in step S2, obtaining basic parameters and inferring and calculating microscopic orthogonal anisotropy parameters; Step S4, based on the characteristic information of the hole defects inside the metal material under CT scanning, a hole defect model with the same characteristic information is established, key holes of the hole defect model are identified through finite element simulation, and the key holes are extracted; Step S5, based on the key holes extracted in step S4, a model characterizing the hole defect characteristics inside the metal material is established, and the stress distribution state under different hole sizes, positions, and shape characteristics is simulated using finite element software to obtain the mathematical relationship between the hole defect characteristics and the stress concentration factor; Step S6, substituting the stress concentration factor obtained in step S5 into the Tanaka-Mura dislocation theory to correct the formula; Step S7, according to the formula corrected by Tanaka-Mura dislocation theory in step S6, combined with the sub-model, the Python language is used to complete the secondary development of ABAQUS, realize the numerical simulation of fatigue crack initiation of metal materials containing hole defects, and obtain the crack initiation life and the specific location of the crack.

2. A metal fatigue crack initiation simulation method for coupling pores and microstructures according to claim 1, characterized in that: The sub-model described in step S1 is constructed at the stress concentration area of ​​the metal part, and its size is determined according to the crack initiation growth, while taking into account the grain size and microstructure characteristics to capture the microscopic mechanism of crack initiation and propagation; in the sub-model, the grains are given random orientation to simulate the random arrangement of actual materials; slip is set, and the nucleation position of the fatigue crack is determined by calculating the average shear stress on the slip band; the boundary conditions and loads of the global model are set according to the actual working conditions or test conditions, the boundary conditions are extracted from the global model, and are locally refined at the sub-model boundary; the load distribution is dynamically adjusted according to the crack initiation situation.

3. The method for simulating metal fatigue crack initiation by coupling pores and microstructures according to claim 1, characterized in that: In step S2, the Voronoi algorithm is used to establish a material microstructure model, and the model building process is as follows: Step S21, using MATLAB software to randomly generate coordinate points within a specified area; Step S22, connecting the generated coordinate points to form a triangular network, so as to obtain the circumcenters of these triangles, and generating Voronoi polygons by connecting the circumcenters of these triangles; Step S23: Use a dedicated Python script to import the Voronoi polygon information into ABAQUS in text format, establish an ideal grain feature model, and assign random grain orientations to the grains.

4. The method for simulating metal fatigue crack initiation by coupling pores and microstructures according to claim 1, characterized in that: The basic parameters obtained in step S3 and the microscopic orthotropic parameters are inferred and calculated, and the basic parameters include elastic modulus E, Poisson's ratio , shear modulus G; the microscopic orthogonal anisotropy parameters are inferred and calculated, and the microstructure of the material is obtained, observed and analyzed using common experimental testing techniques, thereby indirectly inferring its orthogonal anisotropy parameters. The inference calculation process is: According to the linear elastic material, based on the generalized Hooke's law, the fully anisotropic material constitutive equation of the material is: ； For microscopic materials, the orthotropic anisotropy is: ； The calculation formula of the microscopic orthotropic parameters is: ； ； ； In the above formula, , , They represent the normal stress of the material in the x, y, and z directions respectively; , , Respectively indicate that the materials xy、yz、zx Shear stress in the plane; the stiffness matrix C is a 6×6 symmetric matrix with 21 independent elastic constants; The series of parameters describes the elastic properties of the material, i =1,2,3,...,n, j =1,2,3,...,n, n is a positive integer; , , Respectively indicate that the materials x, y, z Direction of positive strain; , , Respectively indicate that the materials xy, yz、zx In-plane shear strain.

5. The method for simulating metal fatigue crack initiation by coupling pores and microstructures according to claim 1, characterized in that: The mathematical relationship between the hole defect characteristics and the stress concentration factor in step S5 is derived as follows: Set the size of the hole: major axis a, minor axis b, and inclination angle θ relative to the loading direction; use the finite element analysis method to calculate the local stress distribution in the grains near the hole, and establish the stress concentration factor K by fitting the finite element simulation results. t The relationship between the hole shape and position: ； In formula (1), D is the distance from the hole center to the sub-model boundary; a is the length of the major axis of the hole ellipse; and b is the length of the minor axis of the hole ellipse.

6. The method for simulating metal fatigue crack initiation by coupling pores and microstructures according to claim 1, characterized in that: In step S6, the stress concentration factor obtained in step S5 is substituted into the Tanaka-Mura dislocation theory to correct the formula, and the process is as follows: The traditional Tanaka-Mura formula mainly considers the crack initiation in homogeneous materials, and its crack initiation life N i The specific calculation formula is: ； In formula (2), d is the slip band length, W is the specific fracture energy per unit area, G is the shear modulus, k is the critical dislocation slip resistance, is the Poisson's ratio, is the average shear stress amplitude over the length of the slip band; In order to simplify the formula, a new parameter η is introduced: ； Therefore, formula (2) becomes: ； However, in actual metal materials, hole defects can cause local stress concentration, so the Taylor factor M is introduced, and the applied fatigue stress amplitude is used instead of the shear stress amplitude, which is expressed as: ； In formula (5), is the mean stress amplitude; Since the critical dislocation slip resistance and fatigue limit stress are in a similar order of magnitude, the approximate factor λ=1 is introduced to linearize formula (5): ； In formula (6), The fatigue life is 10 7 The fatigue limit corresponding to the load of the cycle; Substituting formula (6) into formula (4) and normalizing the dimensions, we get: ； According to Griffith's surface energy criterion, since the surface energy is equal to the specific fracture energy, that is, the γ value is equal to the specific fracture energy per unit area W, formula (7) is finally concretized as: ； The stress concentration near the hole will cause the local stress amplitude Above the mean stress amplitude , then formula (8) further becomes: ； In order to calculate the crack initiation life and study the influence of hole stress concentration on the initiation life in the sub-model, the shear stress amplitude is not used in the first calculation of the sub-model, but the stress concentration factor K is used. t Substitute it into the Tanaka-Mura formula to calculate the crack initiation life and get the corrected formula: 。 7. The method for simulating metal fatigue crack initiation by coupling pores and microstructures according to claim 1, characterized in that: The numerical simulation of fatigue crack initiation of the metal material containing hole defects is implemented in step S7, and the specific process is as follows: Step S71, import the modified Tanaka-Mura formula in step S6 into the Python script of ABAQUS, and define all relevant parameters; Step S72: extract the local stress concentration factor and average stress amplitude around the hole defect from the sub-model through the stress analysis function of ABAQUS, and import these stress data into the modified Tanaka-Mura formula through the Python script interface; Step S73, using the cyclic iteration method, considering the stress accumulation effect under different numbers of cycles, accurately calculate the crack initiation life of each grain containing hole defects, identify the location where the crack first initiates based on the calculation result of the crack initiation life, and mark the crack initiation location in the sub-model through the visualization function of ABAQUS, and generate the corresponding stress cloud map and crack initiation location map.

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