Method for calculating energy density of dislocation structure energy surface and fatigue life prediction method based on discrete dislocation dynamics

Abstract

The present invention relates to a method for calculating dislocation structure energy surface energy density based on discrete dislocation dynamics and a fatigue life prediction method, wherein the method for calculating dislocation structure energy surface energy density based on discrete dislocation dynamics includes: simulating the dislocation behavior of the target material during plastic deformation; determining two sizes of grids required for calculating the dislocation structure energy surface density: in the first grid, using the dislocation dynamics model to calculate the geometrically required dislocation density; in the second grid, determining the stress and strain field by local evaluation, and then calculating the local structure energy density; averaging the energy density and the dislocation density by a hybrid meshing method; and then calculating the dislocation structure energy surface density. In this way, by adopting the hybrid meshing method, the influence of the dislocation density and the local dislocation structure energy density on the dislocation structure energy surface density can be considered simultaneously in the same subdomain, thereby achieving more accurate calculation.

Description

Technical Field

[0001] The present invention relates to the field of material science, and in particular to a method for calculating the energy density of a dislocation structure energy surface based on discrete dislocation dynamics and a fatigue life prediction method. Background Art

[0002] Dislocation structural energy caused by dislocation structural evolution plays an important role in the evolution of material microstructure, especially in the process of twin nucleation, crack initiation and other processes involving the formation of new interfaces. However, this energy itself is not enough to drive the local generation of new surfaces alone, and the length scale of stored dislocation structural energy needs to be considered. This length scale provides the driving rate of energy per unit area, which is crucial for promoting the incremental energy balance between the energy associated with the new free surface energy and the release of dislocation structural energy per unit crack area. Therefore, in order to gain a deeper understanding of these microstructural evolution processes, it is particularly important to calculate the surface energy density of dislocation structural energy and determine its length scale.

[0003] Among the existing calculation methods, the method based on crystal plasticity can provide a certain means of calculating energy density. This method usually involves parameters such as the volume fraction of energy stored in the material, stress, and plastic strain increment, while considering the influence of the density of statistically stored dislocations (SSD) and geometrically necessary dislocations (GND). However, although this method has been widely used in the field of crystal plasticity, it has not been deeply considered based on dislocation dynamics. Therefore, a method based on dislocation dynamics that can accurately calculate the energy surface density of dislocation structures is urgently needed to solve these problems. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above problems and / or the problems existing in the prior art, the present invention is proposed.

[0006] In a first aspect, the present invention provides a method for calculating the energy density of a dislocation structure energy surface based on discrete dislocation dynamics, comprising:

[0007] The dislocation behavior of the target material during plastic deformation is simulated based on the preset dislocation dynamics model;

[0008] Determine the two sizes of grids required for calculating the dislocation structure energy surface density: the first grid is used to calculate the dislocation density, and the second grid is used to calculate the local structure energy density;

[0009] In the first grid, the geometrically required dislocation density in the target material is calculated using the dislocation dynamics model; the geometrically required dislocation density is calculated by dividing the dimensionless net Burgers vector by its area; in the first grid, the geometrically required dislocation density near the grain boundary where dislocation accumulation occurs meets the preset value;

[0010] In the second type of grid, the stress and strain fields are determined by local evaluation, and then the local structural energy density is calculated; the local extrema in the second type of grid correspond to the positions of discrete dislocations, and the average energy density converges;

[0011] Through the hybrid meshing method, a mesh size between the two mesh sizes is selected, and the energy density and dislocation density in the unit are averaged to comprehensively consider the influence of different variables on the energy surface density of the dislocation structure in the same subdomain;

[0012] The dislocation structure energy surface density is calculated based on the averaged energy density and dislocation density; the dislocation structure energy surface density is obtained through a preset functional relationship between the dislocation density and the local structure energy density.

[0013] In some possible implementations, the dislocation dynamics model includes a discrete dislocation dynamics model for simulating the generation, movement, and interaction of dislocations in a material.

[0014] In some possible implementations, the first grid size is selected based on being able to clearly distinguish differences in geometrically required dislocation densities at different locations and avoiding inaccurate calculation of dislocation density due to an excessively large grid size.

[0015] In some possible implementations, the second grid size is selected based on being able to reflect the local energy concentration stored in the dislocation structure and ensure the convergence of the average energy density.

[0016] In some possible implementations, the hybrid meshing method includes selecting an appropriate mesh size between the two meshes and performing weighted averaging on the energy density and dislocation density within the unit to improve the calculation accuracy of the dislocation structure energy surface density.

[0017] In some possible implementations, the method is suitable for calculating the dislocation structure energy surface density in metal materials, alloy materials or other materials with complex microstructures.

[0018] In a second aspect, an embodiment of the present invention provides a method for predicting fatigue life based on dislocation structure energy surface energy density, comprising:

[0019] Calculate the dislocation structure energy surface energy density of the target material by the method provided in the first aspect;

[0020] Based on the surface energy density, combined with the mechanical properties and fatigue behavior characteristics of the target material, a fatigue life prediction model is established;

[0021] According to the fatigue life prediction model, fatigue life prediction is performed on the target material under preset working conditions to obtain the fatigue life prediction value of the target material under the predicted working conditions; wherein the preset working conditions at least include the dislocation structure energy surface energy density, stress state, and working environment of the target material.

[0022] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0023] The present invention provides a method for calculating dislocation structure energy surface energy density based on discrete dislocation dynamics and a fatigue life prediction method. The method simulates the dislocation behavior of a target material during plastic deformation based on a preset dislocation dynamics model; determines two sizes of grids required for calculating the dislocation structure energy surface density: the first grid is used to calculate the dislocation density, and the second grid is used to calculate the local structure energy density; in the first grid, the dislocation dynamics model is used to calculate the geometrically required dislocation density in the target material; the calculation of the geometrically required dislocation density is obtained by dividing the dimensionless net Burgers vector by its area; the geometrically required dislocation density near the grain boundary where dislocation accumulation occurs in the first grid is calculated. The degree meets the preset value; in the second grid, the stress and strain fields are determined by local evaluation, and then the local structural energy density is calculated; the local extreme value in the second grid corresponds to the position of the discrete dislocation, and the average energy density converges; through the hybrid grid division method, a grid size between the two grid sizes is selected, and the energy density and dislocation density in the unit are averaged to comprehensively consider the influence of different variables on the dislocation structure energy surface density in the same subdomain; according to the averaged energy density and dislocation density, the dislocation structure energy surface density is calculated; the dislocation structure energy surface density is obtained by the preset functional relationship between the dislocation density and the local structure energy density. In this way, the problem of grid inconsistency encountered in calculating the dislocation structure energy surface density is solved. By adopting the hybrid grid division method, this method can simultaneously consider the influence of dislocation density and local dislocation structure energy density on the dislocation structure energy surface density in the same subdomain, thereby achieving more accurate calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention, the accompanying drawings required for use in the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0025] Figure 1 A schematic flow chart of an embodiment of a method for calculating energy density of dislocation structure energy planes based on discrete dislocation dynamics provided by an embodiment of the present invention;

[0026] Figure 2a Schematic diagram of GND density under a 0.5μm grid;

[0027] Figure 2b Schematic diagram of GND density under a 0.1μm grid;

[0028] Figure 2c Schematic diagram of GND density under a 0.01μm grid;

[0029] Figure 3a Schematic diagram of local structural energy density under a 0.6μm grid;

[0030] Figure 3b Schematic diagram of local structural energy density under a 0.2μm grid;

[0031] Figure 3c Schematic diagram of local structural energy density under a grid of 0.04μm;

[0032] Figure 3d Schematic diagram of local structure energy density under a grid of 0.004μm. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] In the relevant description of this embodiment, the terms "including, containing, having" and the like are open terms and are generally understood to include but not be limited to; the term "at least one" is generally understood to mean one or more, where "plurality" refers to two or more; the term "at least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items, for example, "at least one of a, b or c", or "at least one of a, b and c", can all represent: a, b, c, ab (i.e., a and b), ac, bc, or abc, where a, b, c can be single or multiple, respectively; the symbol "A / B" is used to describe the selection relationship of associated objects, generally indicating an "or" relationship before and after.

[0035] In the following description of the present embodiment, the terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0036] Those skilled in the art should understand that in the following description of the embodiments of the present application, the order of serial numbers does not mean the order of execution, some or all of the steps can be executed in parallel or sequentially, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0037] Those skilled in the art will appreciate that the numerical ranges in the embodiments of the present application are to be construed as also specifically disclosing each intermediate value between the upper and lower limits of the scope. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the range is also included in the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded in the scope.

[0038] Unless otherwise specified, the technical / scientific terms used herein have the same meanings as those generally understood by those skilled in the art to which this application belongs. Although this application only describes preferred methods and materials, any methods and materials similar or equivalent to these may also be used in the implementation or testing of this application. All documents mentioned in this specification are incorporated by reference to disclose and describe methods and / or materials related to the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0039] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0040] Dislocation structural energy caused by dislocation structural evolution plays an important role in the evolution of material microstructure, especially in the process of twin nucleation, crack initiation and other processes involving the formation of new interfaces. However, this energy itself is not enough to drive the local generation of new surfaces alone, and the length scale of stored dislocation structural energy needs to be considered. This length scale provides the driving rate of energy per unit area, which is crucial for promoting the incremental energy balance between the energy associated with the new free surface energy and the release of dislocation structural energy per unit crack area. Therefore, in order to gain a deeper understanding of these microstructural evolution processes, it is particularly important to calculate the surface energy density of dislocation structural energy and determine its length scale.

[0041] Among the existing calculation methods, the method based on crystal plasticity can provide a certain means of calculating energy density. This method usually involves parameters such as the volume fraction of energy stored in the material, stress, and plastic strain increment, while considering the influence of statistical storage dislocation density and geometric required dislocation density. However, although this method has been widely used in the field of crystal plasticity, it has not been deeply considered based on dislocation dynamics. Therefore, a method based on dislocation dynamics that can accurately calculate the energy surface density of dislocation structure is urgently needed to solve these problems.

[0042] For example, the existing calculation method of the dislocation structure energy surface density based on crystal plasticity can be expressed as:

[0043]

[0044] in, is the volume fraction of energy stored in the material, is stress, is the plastic strain increment, To calculate the storage dislocation density, is the geometrically required dislocation density. There is no calculation method based on dislocation dynamics.

[0045] Figure 1 A schematic diagram of an embodiment of a method for calculating the energy density of a dislocation structure energy surface based on discrete dislocation dynamics provided by an embodiment of the present invention, see Figure 1 As shown, the above method may include:

[0046] S101, simulating the dislocation behavior of the target material during plastic deformation based on a preset dislocation dynamics model;

[0047] In some embodiments, the dislocation dynamics model includes a discrete dislocation dynamics model for simulating the generation, movement, and interaction of dislocations in a material.

[0048] It should be noted that the dislocation dynamics model is a key tool for studying and understanding the plastic deformation behavior of materials. Among them, the discrete dislocation dynamics model is widely used to simulate the generation, movement and interaction of dislocations in materials. Dislocations are a type of defect in materials, and they have an important influence on the mechanical properties and microstructural evolution of materials. By simulating dislocation behavior, we can have a deeper understanding of the microscopic mechanism of materials during plastic deformation. The discrete dislocation dynamics model can capture the specific location and morphology of dislocations, as well as how they move and interact in materials. This sophisticated simulation can more accurately predict the mechanical response of materials, including stress-strain relationships, crack initiation and propagation, etc.

[0049] During the simulation, the parameters of the discrete dislocation dynamics model can be set according to the characteristics of the target material, such as lattice structure, elastic modulus, plastic deformation mechanism, etc. By adjusting these parameters, the dislocation behavior of the target material during plastic deformation can be simulated more accurately.

[0050] S102, determining two sizes of grids required for calculating dislocation structure energy surface density: the first grid is used for calculating dislocation density, and the second grid is used for calculating local structure energy density;

[0051] S103, in the first grid, using a dislocation dynamics model to calculate the geometrically required dislocation density in the target material; the geometrically required dislocation density is calculated by dividing the dimensionless net Burgers vector by its area; the geometrically required dislocation density near the grain boundary where dislocation accumulation occurs in the first grid satisfies a preset condition;

[0052] In some embodiments, the first grid size is selected based on the ability to clearly distinguish differences in geometrically required dislocation densities at different locations and to avoid inaccurate calculation of dislocation density due to excessively large grid size.

[0053] Among them, the geometrically required dislocation density is an important parameter in the dislocation structure, and its calculation is obtained by dividing the dimensionless net Burgers vector by its area. In the first grid, the dislocation dynamics model is used to calculate the GND density in the target material. In order to ensure the accuracy of the calculation, the grid size cannot be too large, otherwise the net Burgers vector in each unit will be low, making it difficult to distinguish the difference in GND density at different positions. At the same time, the grid size cannot be too small, otherwise there may be only one dislocation or no dislocation in each unit, and the calculated GND density will correspond to a single dislocation and cannot reflect the real dislocation structure. Therefore, the selection of the first grid size needs to be based on the ability to clearly distinguish the difference in GND density at different positions, and avoid inaccurate calculation of dislocation density caused by too large a grid size. Therefore, it is necessary to determine the appropriate grid size to accurately reflect the dislocation structure characteristics of the material.

[0054] In some embodiments, the preset condition may be that the geometrically required dislocation density near the grain boundary where dislocation accumulation occurs satisfies a preset density threshold. By setting a reasonable GND density threshold, it is ensured that the calculated GND density near the grain boundary where dislocation accumulation occurs is not lower than the threshold. This threshold can be determined based on the properties of the material, deformation conditions, experimental data, etc.

[0055] In other embodiments, the preset condition may also be that the density satisfies a density gradient condition. For example, consider the gradient change of the GND density near the grain boundary. Since dislocation accumulation usually causes a sharp increase in the GND density near the grain boundary, the preset condition may include requiring the GND density to have a significant gradient change near the grain boundary to reflect the phenomenon of dislocation accumulation.

[0056] Alternatively, the preset condition may be a combination of one or more of the above aspects, depending on the properties of the material, the deformation conditions, and the research purpose, or may be determined based on the needs in practical applications, which are not specifically limited in the embodiments of the present invention. By setting reasonable preset conditions, it is possible to ensure that the dislocation structure characteristics of the material are accurately reflected during the calculation process, providing strong support for a deep understanding of the microstructure and performance of the material.

[0057] For example, near the grain boundaries where dislocation accumulation occurs, the GND density is usually higher. Therefore, it is necessary to ensure that in the first grid, the GND density in these areas can meet the preset conditions to accurately reflect the dislocation structure characteristics of the material.

[0058] For example, the present invention selects three grid sizes of 0.5 μm, 0.1 μm, and 0.01 μm to calculate the GND density of the same dislocation structure. Figure 2a Schematic diagram of GND density under a 0.5μm grid. Figure 2b Schematic diagram of GND density under a 0.1μm grid. Figure 2c This is a schematic diagram of GND density under a 0.01μm grid. Figure 2a to Figure 2c As shown, when the grid size is selected as 0.1μm, a higher GND density is observed near the grain boundaries where dislocation accumulation occurs. Therefore, in the embodiment of the present invention, a grid size of 0.1μm can be selected to calculate the GND density (that is, when the grid size is 0.1μm, the geometrically necessary dislocation density near the grain boundaries where dislocation accumulation occurs in the first grid satisfies the preset conditions. At this time, the size of the first grid can be 0.1μm).

[0059] S104, in the second grid, determining the stress and strain fields by local evaluation, and then calculating the local structural energy density; the local extreme values ​​in the second grid correspond to the positions of the discrete dislocations, and the average energy density converges;

[0060] Among them, the local structural energy density is another key parameter in the calculation of the dislocation structure energy surface density. In the second grid, the stress and strain fields are determined by local evaluation, and then the local structural energy density is calculated. In order to ensure the accuracy of the calculation, the size of the second grid cannot be too large, otherwise the average energy density will be highly dependent on the node position, resulting in a relatively uniform energy distribution and unable to reflect the local energy concentration stored in the dislocation structure. At the same time, the grid size cannot be too small, otherwise the local extreme values ​​may not correspond to the positions of discrete dislocations, and the average energy density may not converge. Therefore, in the second grid, it is necessary to ensure that the local extreme values ​​correspond to the positions of discrete dislocations and that the average energy density converges in order to accurately calculate the local structural energy density.

[0061] For example, the embodiment of the present invention calculates the local structure energy density using four grid sizes of 0.004 μm, 0.04 μm, 0.2 μm, and 0.6 μm. Figure 3a Schematic diagram of local structural energy density under a 0.6μm grid. Figure 3b Schematic diagram of local structural energy density under a 0.2μm grid. Figure 3c Schematic diagram of local structural energy density under a 0.04μm grid. Figure 3d Schematic diagram of local structural energy density under a 0.004μm grid. Figure 3a to Figure 3d As shown, the smaller the grid size, the higher the local structural energy density. When the grid size is greater than 0.04 μm, the average energy density is highly dependent on the node position, the energy distribution is relatively uniform, and the generated structural energy density resolution is insufficient to reflect the local energy concentration stored in the dislocation structure. When the grid size is less than or equal to 0.04 μm, the local extreme values ​​begin to correspond to the positions of discrete dislocations, and the average energy density converges at this time, that is, the grid size of 0.04 μm is suitable for determining the energy stored in the dislocation structure. That is, the size of the second grid can be selected as 0.04 μm, or a smaller size such as Figure 3d The specific mesh size can be selected based on the requirements of the actual application.

[0062] S105, selecting a grid size between the two grid sizes through a hybrid grid division method, averaging the energy density and dislocation density in the unit, so as to comprehensively consider the influence of different variables on the energy surface density of the dislocation structure in the same subdomain;

[0063] In some embodiments, the hybrid meshing method includes selecting an appropriate mesh size between the sizes corresponding to the first mesh and the second mesh, and performing weighted averaging on the energy density and dislocation density within the unit to improve the calculation accuracy of the dislocation structure energy surface density.

[0064] Specifically, the hybrid meshing method includes the following steps:

[0065] Step S1, select an appropriate grid size: between the first large grid for calculating dislocation density and the second small grid for calculating local structural energy density, select an appropriate grid size as a hybrid grid. This size should be able to balance the resolution of dislocation density and the accuracy of local structural energy density.

[0066] Step S2, averaging: In each cell of the hybrid grid, the energy density and dislocation density are averaged. This can be achieved by weighted averaging, that is, different weights are given according to the contribution of each sub-grid (i.e., the cells in the first and second grids) to the overall dislocation structure energy surface density, and then the weighted average is calculated.

[0067] Step S3, comprehensively consider different variables: Through the hybrid meshing method, the influence of different variables on the dislocation structure energy surface density can be comprehensively considered in the same subdomain. This includes dislocation density, local structure energy density, and the interaction between them. It can more comprehensively reflect the energy distribution and dislocation evolution process in the dislocation structure, thereby improving the calculation accuracy of the dislocation structure energy surface density.

[0068] Step S4, verification and adjustment: After implementing the hybrid meshing method, the calculation results can be verified and adjusted. By comparing with experimental data or other reliable calculation results, the accuracy and applicability of the hybrid meshing method can be evaluated, and appropriate adjustments and optimizations can be made as needed.

[0069] S106, calculating the dislocation structure energy surface density according to the averaged energy density and dislocation density; the dislocation structure energy surface density is obtained by a preset functional relationship between the dislocation density and the local structure energy density.

[0070] Specifically, there is a specific functional relationship between the dislocation structure energy surface density and the dislocation density and local structure energy density. This relationship may be linear or nonlinear, depending on various factors such as the characteristics of the material, the distribution of dislocations, and the stress-strain state. In order to obtain the accurate dislocation structure energy surface density, this functional relationship can be established through experiments or theoretical derivations. Once this relationship is determined, the averaged energy density and dislocation density can be substituted into the function to calculate the dislocation structure energy surface density.

[0071] For example, the dislocation structure energy determined based on discrete dislocation dynamics can be expressed as:

[0072]

[0073] In some embodiments, determining dislocation structure energy based on discrete dislocation dynamics can be achieved by the following process:

[0074] According to the crystallographic information of the target crystal material, a discrete dislocation dynamics geometric model of the target crystal material is constructed;

[0075] According to the geometric model and based on the dislocation evolution mechanism, the dynamic evolution of dislocations in the target crystal material during plastic deformation is simulated;

[0076] Among them, the dynamic evolution process is used to describe the dynamic distribution and morphological changes of dislocations in the target crystal material;

[0077] Specifically, according to the geometric model and based on the dislocation evolution mechanism, the dynamic evolution process of dislocations in the target crystal material during plastic deformation can be simulated by:

[0078] Determine the initial dislocation configuration of the target crystal material and apply a preset shear stress to the discrete dislocation dynamics model ;

[0079] When the shear stress After the dislocation source intensity exceeds the preset time, the Burgers vector is The edge dislocation nucleates from the dislocation source and continues to slide along the corresponding slip plane. The dislocation nucleation time for:

[0080] ,

[0081] in is a constant related to the dislocation drag coefficient, is the length of the dislocation source. When the attraction between dislocations is equal to the applied shear stress nuc At equilibrium, the diameter of the initial dislocation ring is for:

[0082] ,

[0083] Where G is the shear modulus, v is Poisson's ratio, and length The dislocation source strength is , the sliding velocity of the dislocation between the pinning obstacles for:

[0084] ,

[0085] in, is the Boltzmann constant, is the representative distance of cooperative dislocation slip, is the atomic vacancy volume, It is the temperature The vacancy equilibrium concentration under is the vacancy diffusion coefficient.

[0086] It can be understood that the use of the above-mentioned Boltzmann constant, the representative distance of cooperative dislocation slip, the atomic vacancy volume, the vacancy equilibrium concentration at temperature, and the vacancy diffusion coefficient to calculate the sliding speed of dislocations between pinning obstacles has clear physical meaning and a solid theoretical basis (for example, the Boltzmann constant is related to thermodynamics, and the vacancy diffusion coefficient describes the diffusion rate of vacancies in the material. These parameters jointly determine the dynamic behavior of dislocations between pinning obstacles). These parameters are not only directly related to the sliding mechanism of dislocations, but also can be measured or estimated by experimental means (for example, the vacancy diffusion coefficient can be obtained by diffusion experiments, and the vacancy equilibrium concentration can be obtained by thermodynamic calculations. This makes this method feasible in practical applications). As a result, the above-mentioned calculation method has a wider range of applications in practical applications, and it can be applied to various types of materials and conditions. Whether it is metal, ceramic or polymer material, as long as the relevant parameters can be obtained, this method can be used for calculation. In addition, this method is also applicable to the calculation of dislocation sliding speed under different temperature, pressure and stress conditions. Compared with using only macroscopic mechanical property parameters, these fundamental parameters reveal the microscopic mechanism of dislocation sliding more deeply, thus providing more accurate and reliable calculation results.

[0087] In some embodiments, the stress and strain generated during the actual plastic deformation of the target crystal material are respectively the superposition of the corresponding elastic field and the additional field; in this case, the strain generated during the actual plastic deformation is expressed as:

[0088] ,

[0089] in, is the actual strain, is the strain field of the dislocation, is the additional field of strain;

[0090] Similar to strain, the stress generated during actual plastic deformation is expressed as:

[0091] ,

[0092] in, is the actual stress, is the stress field of the dislocation, is the additional field of stress.

[0093] The additional field can be solved by numerical analysis methods, including but not limited to finite element method, boundary element method or discrete element method; the elastic field is calculated by elastic mechanics theory, specifically the superposition of elastic fields of all dislocations;

[0094] in, It is expressed as:

[0095]

[0096] in, Indicates dislocations, N represents the number of dislocations, Indicates The elastic field strain of a dislocation;

[0097] It is expressed as:

[0098]

[0099] in, Indicates The elastic field stress of a dislocation.

[0100] In some embodiments, The elastic field stress of a dislocation can be expressed as:

[0101] ,

[0102] in:

[0103] ,

[0104] ,

[0105] ,

[0106] in, is the shear modulus, is the Burgers vector, is Poisson's ratio, , is the coordinate of the current dislocation in the local coordinate system;

[0107] In some embodiments, The elastic field strain of a dislocation can be expressed as:

[0108] ,

[0109] in:

[0110] ,

[0111] ,

[0112] .

[0113] Afterwards, based on the stress and strain generated during the actual plastic deformation of the target crystal material, the dislocation structural energy in the target crystal material can be derived using the free energy calculation formula.

[0114] Specifically, the free energy calculation formula can be expressed as:

[0115] ,

[0116] It can be further deduced as:

[0117] .

[0118] It should be noted that the free energy in the plastic deformation process The stored energy associated with the dislocation and elastic storage energy Composition, and is the dislocation strain energy and dislocation structure energy The sum of , that is, the free energy can also be expressed as:

[0119] .

[0120] Due to the singularity of the dislocation stress-strain field, it is difficult to obtain a finite value for the free energy, so the free energy can be further determined as:

[0121]

[0122] The elastic storage energy associated with remote loading can be expressed as:

[0123] ,

[0124] in, and They are the stress field and strain field when the same external force is applied to a pure elastic body with the same geometric shape. From this, the dislocation structural energy can be derived.

[0125] Furthermore, based on the above formula of dislocation structural energy, the local dislocation structural energy density It can be expressed as:

[0126]

[0127] Its unit is J·m -3 . Further, the preset functional relationship can be expressed as:

[0128]

[0129] in, is the dislocation structure energy surface density, is the dislocation density, the mean free path of dislocations The structural energy density is determined and the length scale for storing structural energy is provided. However, the calculation method of GND density in discrete dislocation dynamics is different from that in crystal plasticity. The GND density in a certain area is obtained by dividing the dimensionless net Burgers vector by its area.

[0130] Thus, after obtaining the averaged energy density and dislocation density through the above steps S101 to S105, the averaged energy density and dislocation density are substituted into the above preset function to calculate the dislocation structure energy surface energy density of the target material.

[0131] In some embodiments, the above method is applicable to calculating the dislocation structure energy surface density in metal materials, alloy materials or other materials with complex microstructures.

[0132] It is understandable that for metal materials, which usually have a regular lattice structure and good plastic deformation ability, the dislocation structure plays a vital role in the plastic deformation process. By applying the above method, the distribution of the dislocation structure energy surface density in metal materials can be accurately calculated, and then the influence of dislocation evolution on the mechanical properties of materials can be deeply understood. Due to the addition of other elements or compounds, the microstructure of alloy materials is often more complex than that of pure metals. The evolution process of dislocation structure in alloy materials is also more complex and diverse. By applying the above method, the dislocation structure in alloy materials can be analyzed more finely, revealing the influence of alloying elements on the dislocation evolution process.

[0133] In addition, the above method is also applicable to materials with complex microstructures, such as composite materials, multilayer materials or materials with special microstructures. The microstructures of these materials often contain multiple different phases or structures, and the evolution process of dislocation structure in these phases or structures is also more complicated. By applying the above method, a more comprehensive analysis of dislocation structure in complex microstructure materials can be carried out, revealing the interaction and evolution law of dislocations between different phases or structures.

[0134] A method for calculating dislocation structure energy density based on dislocation dynamics provided by an embodiment of the present invention calibrates the calculation of GND density by selecting an appropriate grid size, thereby ensuring that representative GND and SSD structures can be accurately captured in deformed materials. In addition, the method also determines the local structure energy density by locally evaluating the stress and strain fields, thereby being able to reflect the local energy concentration stored in the dislocation structure. In addition, the method solves the problem of grid inconsistency encountered when calculating the dislocation structure energy surface density. By adopting a hybrid grid division method, the effects of dislocation density and dislocation structure energy density on the dislocation structure energy surface density can be considered simultaneously in the same subdomain, thereby achieving more accurate calculations and improving the accuracy of dislocation structure energy density calculations.

[0135] On the other hand, an embodiment of the present invention further provides a method for predicting fatigue life based on dislocation structure energy surface energy density, which may include the following steps:

[0136] S201, calculating the dislocation structure energy surface energy density of the target material by the method for calculating the dislocation structure energy surface energy density based on discrete dislocation dynamics provided in the above steps S101 to S106;

[0137] S202, establishing a fatigue life prediction model based on the calculated surface energy density and in combination with the mechanical properties and fatigue behavior characteristics of the target material;

[0138] Specifically, after obtaining the energy density of the dislocation structure energy surface of the target material, a fatigue life prediction model can be established based on this data, combined with the mechanical properties of the target material and known fatigue behavior characteristics. The specific steps include:

[0139] Data collection: Collect the mechanical properties parameters (such as elastic modulus, yield strength, etc.) and fatigue behavior characteristics (such as fatigue limit, fatigue crack growth rate, etc.) of the target material;

[0140] Model construction: Using statistical methods or existing machine learning algorithms, combined with dislocation structure energy surface energy density and obtained mechanical properties parameters and fatigue behavior characteristics, a fatigue life prediction model is constructed. The constructed fatigue life prediction model can accurately reflect the fatigue life of the material under specific working conditions.

[0141] Model validation: By comparing the experimental data or existing fatigue life data, the established model is verified and calibrated to ensure its prediction accuracy and reliability.

[0142] S203, performing fatigue life prediction on a target material under a preset working condition according to a fatigue life prediction model, and obtaining a fatigue life prediction value of the target material under the predicted working condition;

[0143] Among them, the preset working conditions include at least parameters such as the dislocation structure energy surface energy density, stress state and working environment of the target material.

[0144] Specifically, after the fatigue life prediction model is established and verified, the preset working conditions of the target material are set according to actual needs. These conditions include at least the energy density of the dislocation structure energy surface, the stress state, the working environment, and the material-related parameters of the target material. The parameters under the preset working conditions are input into the fatigue life prediction model, and these parameters will serve as the input data of the model. Based on the input data, the model calculates and outputs the fatigue life prediction value of the target material under the preset working conditions.

[0145] Exemplarily, the fatigue life prediction of the target material under the preset working condition according to the fatigue life prediction model in step S203 can be expressed by the following formula:

[0146]

[0147] When the rate is greater than a certain threshold, it is considered to have entered the macro crack extension stage and reached the fatigue life. is the crack growth rate, is the corresponding crack length increment, equivalent to the element size, is the loop count increment, , are material-related parameters, Dislocation structure energy surface density increment.

[0148] Based on the determined crack growth rate, the fatigue life of the target material can be further predicted. It should be noted that fatigue is a phenomenon in which a material is damaged under a continuously variable load, and this damage is usually accompanied by energy dissipation and damage accumulation. During the fatigue process, the microstructure inside the material will change, such as dislocations and cracks, and these changes will lead to the release and dissipation of energy. Therefore, there is a close correlation between energy density and fatigue damage.

[0149] During the fatigue process, the damage inside the material will gradually accumulate, and this accumulation is closely related to energy dissipation. When the surface energy density reaches a certain critical value, fatigue failure will occur in the material. Therefore, the surface energy density can be used as an important indicator for evaluating the fatigue life of the material. In practical applications, materials are often under complex multi-axial stress states. Traditional fatigue analysis methods cannot accurately describe the fatigue behavior under this state. In the embodiment of the present invention, the effect of multi-axial stress on fatigue life can be considered through the surface energy density, which not only considers the magnitude of the stress, but also the direction and distribution of the stress.

[0150] In addition, the microstructure of the material (such as dislocation, grain size, etc.) has an important influence on its fatigue performance. Since changes in the microstructure will cause changes in the rate of energy dissipation and damage accumulation, the method of the embodiment of the present invention uses the surface energy density to predict fatigue life, which can indirectly reflect changes in the microstructure of the material.

[0151] Therefore, in the embodiment of the present invention, the use of surface energy density to predict fatigue life can comprehensively consider the influence of multiple factors such as stress, strain, multi-axial stress state and material microstructure on fatigue life, thereby providing more accurate prediction results.

[0152] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments.

[0153] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A method for calculating the energy density of dislocation structure energy surface based on discrete dislocation dynamics, characterized in that: include: Based on the preset discrete dislocation dynamics model, the dislocation behavior of the target material during plastic deformation is simulated, including the generation, movement and interaction of dislocations; Determine the two sizes of grids required to calculate the dislocation structure energy surface energy density: the first grid is used to calculate the dislocation density, and the second grid is used to calculate the local structure energy density; In the first type of grid, the geometrically required dislocation density in the target material is calculated using the dislocation dynamics model; the geometrically required dislocation density is calculated by dividing the dimensionless net Burgers vector by its area; in the first type of grid, the geometrically required dislocation density near the grain boundary where dislocation accumulation occurs meets the preset conditions; In the second type of grid, the stress and strain fields are determined by local evaluation, and then the local structural energy density is calculated; in the second type of grid, the local extrema correspond to the positions of discrete dislocations, and the average energy density converges; Through the hybrid meshing method, a mesh size between the two mesh sizes is selected, and the local structural energy density and dislocation density in the unit are averaged to comprehensively consider the influence of different variables on the energy density of the dislocation structure energy surface in the same subdomain; The dislocation structure energy surface energy density is calculated based on the averaged local structure energy density and dislocation density; the dislocation structure energy surface energy density is obtained through a preset functional relationship between the dislocation density and the local structure energy density.

2. The method according to claim 1, characterized in that The selection of the first grid size is based on being able to clearly distinguish the difference in geometrically required dislocation densities at different locations and avoiding inaccurate calculation of dislocation density due to excessively large grid size.

3. The method according to claim 2, characterized in that The second grid size is selected based on the ability to reflect the local energy concentration stored in the dislocation structure and ensure the convergence of the average local structural energy density.

4. The method according to claim 3, characterized in that: The hybrid grid division method includes selecting an appropriate grid size between two grids, and performing weighted average processing on the local structural energy and dislocation density in the unit to improve the calculation accuracy of the dislocation structure energy surface energy density.

5. A method for fatigue life prediction based on dislocation structure energy surface energy density, characterized in that: include: Calculating the dislocation structure energy surface energy density of the target material by the method according to any one of claims 1 to 4; Based on the surface energy density and in combination with the mechanical properties and fatigue behavior characteristics of the target material, a fatigue life prediction model is established; According to the fatigue life prediction model, fatigue life prediction is performed on the target material under preset working conditions to obtain the fatigue life prediction value of the target material under the predicted working conditions; wherein the preset working conditions at least include the dislocation structure energy surface energy density, stress state, and working environment of the target material.

Images