A simulation method for metal fatigue crack initiation coupling holes and microstructure

Abstract

The present invention discloses a method for simulating the initiation of metal fatigue cracks coupling holes and microstructures. First, by collecting the microstructural characteristic data and hole distribution data inside the metal material, establishing a microscale model, combining the mechanical property test results to obtain basic parameters and inferring and calculating the micro-orthotropic parameters. Then, according to the scanned internal defects of the alloy, a hole defect model with the same characteristic information is established, and the key holes are extracted through finite element simulation to establish a geometric model. After that, the stress concentration coefficient is introduced, and the calculation method of the shear stress amplitude in the Tanaka-Mura dislocation theory formula is replaced with the calculation method of the stress amplitude, completing the microscale numerical simulation of the fatigue crack initiation of the metal material with hole defects. The method of the present invention can accurately predict the fatigue crack initiation life of metals at the microscale by considering factors such as the microstructure and internal holes of the material and combining finite element simulation technology.

Description

Technical Field

[0001] The present invention belongs to the technical field of numerical simulation of metal fatigue crack initiation, and particularly relates to a method for simulating metal fatigue crack initiation by coupling pores and microstructure. Background Art

[0002] Fatigue crack initiation generally occupies about 90% of its service life cycle. Therefore, predicting the initiation of fatigue cracks is crucial for ensuring the safety performance and reliability of structures. Generally speaking, the characteristics of the microstructure and the latent defects inside the material have an important impact on fatigue crack initiation. Especially in the components manufactured by additive manufacturing processes, pores, as common internal defects, not only change the stress distribution of the material, cause stress concentration, but also accelerate the initiation of fatigue cracks. At the same time, the microstructure characteristics (such as the size and orientation of grains) also play an important role in the process of fatigue evolution.

[0003] Previous studies usually revealed the specific action mechanisms of these factors on fatigue crack initiation through experimental verification and theoretical analysis. However, 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 process of fatigue crack initiation, which describes the mechanism of dislocation accumulation and slip band cracking at the microscale and estimates the life cycle of crack initiation, there are still limitations in the accuracy of calculating the crack initiation life due to stress concentration when considering the complex influence of pores and microstructure characteristics on crack initiation. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for simulating metal fatigue crack initiation by coupling pores and microstructure in view of the deficiencies of the prior art. This method collects the microstructure characteristic data and pore distribution data inside the metal material, establishes a microscale model, and by introducing a stress concentration coefficient, replaces the calculation method of the shear stress amplitude in the Tanaka-Mura dislocation theory formula with the calculation method of the stress amplitude, completing the microscale numerical simulation of fatigue crack initiation of metal materials containing defective pores, and being able to more accurately predict the fatigue life of metal materials.

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

[0006] A method for simulating metal fatigue crack initiation by coupling pores and microstructure, comprising the following steps:

[0007] Step S1, establish a global model of the specimen and determine a sub-model with microscale dimensions according to the structure of the global model, set cyclic loads on the global model, and simulate the stress-strain response of the material under cyclic loads;

[0008] Step S2: Obtain the size and shape information of the grains inside the metal material, establish a material microstructure model using the Voronoi algorithm, and determine it as the sub-model in Step S1. The microstructure model includes grain size and grain orientation micro-characteristics;

[0009] Step S3: Based on the stress-strain response obtained in Step S1 and the size and shape information of the grains inside the metal material obtained in Step S2, observe and analyze the structure, obtain basic parameters, and infer and calculate the micro-orthotropic parameters;

[0010] Step S4: Based on the hole defect characteristic information inside the metal material under CT scanning, establish a hole defect model with the same characteristic information, identify the key holes of the hole defect model through finite element simulation, and extract the key holes;

[0011] Step S5: Based on the key holes extracted in Step S4, establish a model characterizing the hole defect characteristics inside the metal material, use finite element software to simulate the stress distribution states under different hole sizes, positions, and shape characteristics, and obtain the mathematical relationship between the hole defect characteristics and the stress concentration coefficient;

[0012] Step S6: Substitute the stress concentration coefficient obtained in Step S5 into the Tanaka-Mura dislocation theory for formula correction;

[0013] Step S7: According to the formula corrected by the Tanaka-Mura dislocation theory in Step S6, combined with the sub-model, complete the secondary development of ABAQUS using the Python language, realize the numerical simulation of fatigue crack initiation of the metal material with hole defects, and obtain the crack initiation life and the specific position of the crack.

[0014] Specifically, the sub-model in Step S1 is constructed at the stress concentration area position of the metal component. Its size is determined according to the crack initiation length, and at the same time, the grain size and microstructure characteristics are considered to capture the micro-mechanisms of crack initiation and propagation. In the sub-model, the grains are given random orientations to simulate the random arrangement of the actual material; slip is set, and the nucleation position of fatigue cracks is judged 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 boundary 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.

[0015] Specifically, the material microstructure model is established using the Voronoi algorithm in Step S2, and the model construction process is as follows:

[0016] Step S21: Use MATLAB software to randomly generate coordinate points within the specified area range;

[0017] Step S22: Connect the generated coordinate points to form a triangular mesh, so that the circumcenters of these triangles can be obtained, and the Voronoi polygons are generated by connecting the circumcenters of these triangles;

[0018] 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.

[0019] Specifically, in step S3, the obtained basic parameters and the inferred and calculated micro-orthotropic parameters are described. The basic parameters include the elastic modulus E, Poisson's ratio , and shear modulus G; for the inferred and calculated micro-orthotropic parameters, common experimental testing techniques are used to obtain, observe, and analyze the microstructure of the material, so as to indirectly infer its orthotropic parameters. The inference and calculation process is as follows:

[0020] Based on linear elastic materials and the generalized Hooke's law, the constitutive equation of a fully anisotropic material is:

[0021] ;

[0022] For micro-material orthotropy:

[0023] ;

[0024] The calculated relationship of the obtained micro-orthotropic parameters is:

[0025] ; ; ;

[0026] In the above formula, , , respectively represent the normal stresses (normal stresses) of the material in the x, y, z direction; , , respectively represent the shear stresses (tangential stresses) of the material in the xy, yz, zx plane; the stiffness matrix C is a 6×6 symmetric matrix with a total of 21 independent elastic constants; A series of parameters describe the elastic properties of the material, i =1,2,3,...,n, j =1,2,3,...,n, where n is a positive integer; , , respectively represent the material inx, y, z The normal strain (longitudinal strain) in the , , respectively represent the shear strain (tangential strain) of the material in the xy, yz, zx plane.

[0027] Specifically, the mathematical relationship between the hole defect characteristics described in step S5 and the stress concentration factor is derived as follows:

[0028] Set the dimensions of the hole: the major axis a, the minor axis b, and the 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 t The relational expression between the hole shape and position:

[0029] ;

[0030] 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 elliptical hole of the hole; b is the length of the minor axis of the elliptical hole of the hole.

[0031] Specifically, the process of substituting the stress concentration factor obtained in step S5 into the Tanaka-Mura dislocation theory for formula correction in step S6 is as follows:

[0032] The traditional Tanaka-Mura formula mainly considers crack initiation in homogeneous materials, and the calculation formula for its crack initiation life N i is specifically:

[0033] ;

[0034] 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 slip band length;

[0035] In order to simplify the formula, a new parameter η is introduced:

[0036] ;

[0037] Therefore, formula (2) becomes:

[0038] ;

[0039] However, in actual metal materials, hole defects will 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, expressed as:

[0040] ;

[0041] In formula (5), is the mean stress amplitude;

[0042] Since the critical dislocation slip resistance is of the same order of magnitude as the fatigue limit stress, an approximate factor λ = 1 is introduced to linearize formula (5):

[0043] ;

[0044] In formula (6), σ e is the fatigue limit corresponding to the load with a fatigue life of 10 7 cycles;

[0045] Substituting formula (6) into formula (4) and performing dimensional normalization gives:

[0046] ;

[0047] According to the Griffith 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 W per unit area, formula (7) is finally specified as:

[0048] ;

[0049] Since the stress concentration near the hole will cause the local stress amplitude Δσ local to be higher than the mean stress amplitude Δσ, formula (8) is further changed to:

[0050] ;

[0051] To facilitate the calculation of the crack initiation life in the sub-model and study the influence of the hole stress concentration on the initiation life, the shear stress amplitude is not used in the first calculation in the sub-model, but the stress concentration factor K t is brought into the Tanaka-Mura formula to calculate the crack initiation life, and the modified formula is obtained:

[0052] .

[0053] Specifically, the implementation of the numerical simulation of fatigue crack initiation in the metal material with hole defects described in step S7 is as follows:

[0054] Step S71: Import the modified Tanaka-Mura formula in step S6 into the Python script of ABAQUS and define all relevant parameters;

[0055] Step S72: Using the stress analysis function of ABAQUS, extract the local stress concentration factor and average stress amplitude around the hole defect from the sub-model, and import this stress data into the modified Tanaka-Mura formula through the Python script interface;

[0056] Step S73: Using the method of cyclic iteration, considering the stress accumulation effect under different numbers of cycles, accurately calculate the crack initiation life of each grain with a hole defect. According to the calculation results of the crack initiation life, identify the location where the crack first initiates, and through the visualization function of ABAQUS, mark the crack initiation location in the sub-model, and generate the corresponding stress nephogram and crack initiation location map.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] 1. The method of the present invention quantifies the stress concentration factor of the holes inside the metal accurately, enabling a more accurate assessment of the influence of holes on the fatigue performance of metal materials. Through quantitative analysis, it is possible to deeply understand how hole defects cause local stress concentration, thereby promoting the process of crack initiation and development.

[0059] 2. The method of the present invention constructs a finite element model for crack initiation at double scales, which not only considers the structural characteristics at the macroscopic scale but also incorporates the material properties at the microscopic scale, providing a more comprehensive and refined simulation of the fatigue crack initiation process of metal materials. This double-scale modeling method helps to more accurately predict the fatigue life of metal materials.

[0060] 3. By modifying the original formula, the method of the present invention proposes a new numerical method to simulate the fatigue crack initiation of metal materials with holes, considering the influence of hole defects on stress concentration, which helps to improve the prediction accuracy of fatigue life. Description of the Drawings

[0061] Figure 1 is the flowchart of the method for simulating fatigue crack initiation of metal coupling holes and microstructure of the present invention;

[0062] Figure 2 is the flowchart of the simulation calculation of the crack initiation model based on the Tanaka-Mura dislocation theory of the present invention;

[0063] Figure 3 is the drawing of the size of the titanium alloy specimen and the microscopic sub-model in the embodiment of the present invention;

[0064] Figure 4 is the schematic diagram of the random orientation assignment of grains in the titanium alloy sub-model in the embodiment of the present invention;

[0065] Figure 5Schematic diagrams of the arrangement modes of the two lattice structures of the α-phase and β-phase of the titanium alloy and the generation of the Voronoi diagrams of the two lattices of the α-phase and β-phase of the titanium alloy and the assignment of grain orientations in the embodiments of the present invention;

[0066] Figure 6 Schematic diagram of the stress distribution of different pore characteristics;

[0067] Figure 7 Simulation diagram of defect characteristic information and key pore characteristics under CT scanning;

[0068] Figure 8 Schematic diagram of the relationship between the stress concentration coefficients of pores with different aspect ratios;

[0069] Figure 9 Schematic diagram of the crack initiation results under stress concentration induced by no stress concentration and pore defects;

[0070] Figure 10 Results of simulation verification based on experimental data in the literature. Detailed implementation manners

[0071] To facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the following will detail each step of the method proposed by the present invention. It should be understood that these embodiments are only used to illustrate the present invention and not 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 this application.

[0072] Embodiment

[0073] As Figure 1 and Figure 2 shown, the present invention discloses a metal fatigue crack initiation simulation method coupling pores and microstructure, including the following steps:

[0074] Step S1: Establish a global model of the specimen and determine a sub-model of microscopic dimensions according to the structure of the global model, set cyclic loads on the global model, and simulate the stress-strain response of the material under cyclic loads;

[0075] In this embodiment, the specimen is made of additively manufactured titanium alloy. An additively manufactured titanium alloy finite element specimen global model is established based on the test specimen, and finite element simulation is performed on the specimen to find the position with the maximum stress concentration. A sub-model is established at the position with the maximum stress concentration. As Figure 3 shown, Figure 3 in Figure 3 A is the position with the maximum stress, and Figure 3At position C in the figure is the microscopic region of the sub-model. Considering that the general definition of the engineering fatigue crack initiation length is 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 into the sub-model.

[0076] Step S2: Obtain the size and shape information of the grains inside the metal material, use the Voronoi algorithm to establish a material microstructure model, and determine it as the sub-model in Step S1. The microstructure model includes microscopic features such as grain size and grain orientation;

[0077] In this embodiment, the EBSD technology (electron backscatter diffraction technology) is used to obtain the size and shape data of the grains inside the titanium alloy, and the Voronoi diagram algorithm is modeled according to this data. The specific modeling process of this model is as follows:

[0078] Step S21: Use MATLAB software to randomly generate coordinate points within a specified area range;

[0079] Step S22: Connect the generated coordinate points to form a triangular mesh, so that the circumcenters of these triangles can be obtained, and Voronoi polygons are generated by connecting the circumcenters of these triangles;

[0080] 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;

[0081] As Figure 4 shown, since the titanium alloy is a duplex 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. Therefore, it is necessary to model its duplex characteristics. The final modeling and orientation assignment results are as Figure 5 shown.

[0082] Step S3: According to the stress-strain response obtained in Step S1 and the size and shape information of the grains inside the metal material obtained in Step S2, observe and analyze the structure, obtain the basic parameters, and infer and calculate the microscopic orthotropic parameters;

[0083] In this embodiment, through mechanical property test experiments, basic mechanical property parameters such as the elastic modulus and Poisson's ratio of the titanium alloy specimen are measured. Using common experimental testing techniques, the microstructure of the material is obtained, observed, and analyzed, so as to indirectly infer its orthotropic parameters. The material parameters of the titanium alloy component are shown in Tables 1 and 2 below.

[0084] Table 1. Tanaka-Mura dislocation parameters of TC4 titanium alloy

[0085] ;

[0086] Table 2, Components of Orthotropic Elastic Stiffness Matrix

[0087] ;

[0088] Based on linear elastic materials and the generalized Hooke's law, the constitutive equation of a fully anisotropic material is:

[0089] ;

[0090] For microscale materials with orthotropic properties:

[0091] ;

[0092] The calculation formulas for the obtained microscale orthotropic parameters are:

[0093] ; ; ;

[0094] In the above formula, , , respectively represent the normal stresses (normal stresses) of the material in the x, y, z direction; , , respectively represent the shear stresses (tangential stresses) of the material in the xy, yz, zx plane; The stiffness matrix C is a 6×6 symmetric matrix with a total of 21 independent elastic constants. A series of parameters describe the elastic properties of the material, i = 1, 2, 3,..., n, j = 1, 2, 3,..., n, where n is a positive integer; , , respectively represent the normal strains (normal strains) of the material in the x, y, z direction; , , respectively represent the shear strains (tangential strains) of the material in the xy, yz, zx plane.

[0095] Step S4: Based on the internal hole defect characteristic information of the metal material under CT scanning, establish a hole defect model with the same characteristic information, identify the key holes of the hole defect model through finite element simulation, and extract the key holes;

[0096] As Figure 6 shown, Figure 6In (a), the stress distribution under different grain sizes is shown, Figure 6 In (b), the shear stress distribution under different grain orientations is shown, Figure 6 In (c), the change in the magnitude and distribution of shear stress caused by different hole defects is shown; Figure 6 It can be seen that at the microscale, holes will cause stress concentration in the grains, which in turn leads to changes in shear stress; therefore, it is necessary to extract the stress concentration coefficient to correct the original Tanaka-Mura dislocation theory formula.

[0097] As Figure 7 shown, according to the CT microtomography inspection of the hole defects in the additive manufacturing titanium alloy, the basic information such as the size, position, and shape of the internal hole clusters is obtained, and a hole defect model with the same characteristic information is established through secondary development of ABAQUS; since the hole defects are often irregular in the metal, in order to quantitatively characterize the hole defects, the three-dimensional hole defects are equivalent to ellipsoids, and 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, and the key holes of the model are identified through finite element simulation, and the key holes are extracted to establish a geometric model.

[0098] Step S5: According to the key holes extracted in step S4, establish a characteristic model of the hole defects inside the metal material, use finite element software to simulate the stress distribution state under different hole sizes, positions, and shape characteristics, and obtain the mathematical relationship between the hole defect characteristics and the stress concentration coefficient;

[0099] Set the size of the hole: the major axis a, the minor axis b, and the inclination angle θ relative to the loading direction; adopt the finite element analysis method to calculate the local stress distribution in the grains near the hole, and establish the stress concentration coefficient K t between the hole morphology and position by fitting the finite element simulation results, as Figure 8 shown, in (a) of Figure 8, the relationship between the stress concentration coefficients at different distances from the surface of the hole ion model with different aspect ratios is shown, Figure 8 in (b), the relationship between the stress concentration coefficients of holes with different aspect ratios at different rotation angles is shown; then the stress concentration coefficient of the internal hole is expressed by fitting according to the simulation results as:

[0100] ;

[0101] In formula (1), D is the distance from the hole center to the boundary of the submodel, a is the length of the major axis of the hole elliptical hole, and b is the length of the minor axis of the hole elliptical hole.

[0102] Step S6: Substitute the stress concentration coefficient obtained in step S5 into the Tanaka-Mura dislocation theory for formula correction;

[0103] The traditional Tanaka-Mura formula mainly considers crack initiation in homogeneous materials, and the calculation formula for its crack initiation life N i is specifically as follows:

[0104] ;

[0105] 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 slip band length;

[0106] To simplify the formula, a new parameter η is introduced:

[0107] ;

[0108] Therefore, formula (2) becomes:

[0109] ;

[0110] However, in actual metallic materials, hole defects will cause local stress concentration. Therefore, the Taylor factor M is introduced, and the applied fatigue stress amplitude is used instead of the shear stress amplitude, which is expressed as:

[0111] ;

[0112] In formula (5), is the average stress amplitude;

[0113] Since the critical dislocation slip resistance and the fatigue limit stress are in a similar order of magnitude, an approximate factor λ = 1 is introduced to linearize formula (5):

[0114] ;

[0115] In formula (6), σ e is the fatigue limit corresponding to the load at a fatigue life of 10 7 cycles;

[0116] Substituting formula (6) into formula (4) and performing dimensional normalization, we get:

[0117] ;

[0118] According to the Griffith 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 W per unit area, formula (7) is finally specified as:

[0119] ;

[0120] Since the stress concentration near the hole will cause the local stress amplitude Δσ local to be higher than the average stress amplitude Δσ, Equation (8) is further transformed into:

[0121] ;

[0122] To facilitate the calculation of the crack initiation life in the sub-model and study the influence of the hole stress concentration on the initiation life, the shear stress amplitude is not used in the first calculation in the sub-model, but the stress concentration factor K t is substituted into the Tanaka-Mura formula to calculate the crack initiation life, and the modified formula is obtained:

[0123] .

[0124] Step S7: According to the formula modified by the Tanaka-Mura dislocation theory in Step S6, combined with the sub-model, use the Python language to complete the secondary development of ABAQUS, realize the numerical simulation of the fatigue crack initiation of the metal material with hole defects, and obtain the crack initiation life and the specific position of the crack;

[0125] In this embodiment, according to the formula modified by the Tanaka-Mura dislocation theory in Step S6, a special script based on the Python programming language is developed, and this script combines the Tanaka-Mura model and the finite element analysis technology; through the secondary development of Python ABAQUS, combined with the sub-model containing the Voronoi diagram in Step 2, perform the finite element simulation of the crack initiation process, and the simulation includes the nucleation and interaction of cracks, and predict the fatigue crack initiation life; specifically:

[0126] Step S71: Import the modified Tanaka-Mura formula in Step S6 into the Python script of ABAQUS and define all relevant parameters;

[0127] Step S72: Through the stress analysis function of ABAQUS, extract the local stress concentration factor and the average stress amplitude around the hole defect from the sub-model, and import these stress data into the modified Tanaka-Mura formula through the Python script interface;

[0128] Step S73: Use the method of loop iteration, consider the stress accumulation effect under different cycle numbers, accurately calculate the crack initiation life of each grain with hole defects, identify the position where the crack first initiates according to the calculation result of the crack initiation life, and mark the crack initiation position in the sub-model through the visualization function of ABAQUS, and generate the corresponding stress nephogram and crack initiation position map.

[0129] The stress concentration factor K obtained by the above method t and the modified formula of the Tanaka-Mura dislocation theory are used to calculate the stress and shear stress amplitudes inside the material, and to simulate the evolution of the microstructure. At the same time, the crack initiation process is simulated, including the nucleation and interaction of cracks, the influence of crack initiation on the fatigue life of the material is analyzed, the fatigue life is predicted, and the prediction results are as Figure 9 shown Figure 9 in which the fatigue crack initiation life, crack initiation path, etc. under different stress concentration factors are shown. At the same time, it can be clearly seen from Figure 9 that the stress concentration factor, as a key parameter to measure the stress concentration degree 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.

[0130] To verify the prediction accuracy of the method of the present invention, the data in the existing literature [Dang L, He X, Tang D, etal. 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. Based on the pore defect characteristic parameters in the literature, the pore defects are modeled and simulated, and the simulation results are as Figure 10 shown

[0131] Table 3. Selected simulation parameters

[0132] ;

[0133] The fatigue data life predicted by the method of the present invention is compared and analyzed with the simulation analysis method given in the existing literature, and the results are shown in Table 4 below.

[0134] Table 4. Comparison of fatigue data life

[0135] ;

[0136] As can be seen from Table 4, when the equivalent diameter of the hole is 51.2 μm, the crack initiation life predicted by the simulation analysis method given in the existing literature is 19,619 cycles, while that of the method of the present invention is 18,624 cycles. The relative error between the method of the present invention and the actual crack initiation life of 18,279 cycles is reduced from 9.8% of the existing simulation method to 1.9%. When the equivalent diameter of the hole is 86.8 μm, the relative error between the method of the present invention and the actual crack initiation life of 35,602 cycles is reduced from 6.1% of the existing simulation method to 1.1%, indicating that the method of the present invention has a higher prediction accuracy than the simulation analysis method given in the existing literature.

[0137] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention in any other form. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still belong 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 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; , , 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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