Method for calculating fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition

Abstract

The invention discloses a method for calculating the fatigue behavior of gradient structure metal based on a deformation mechanism and microstructure composition. According to the method, based on a deformation mechanism and microstructure composition, a gradient grain size distribution nanostructure metal low-cycle fatigue hysteresis curve can be simulated, and the fatigue life can be predicted. Under an elastic-plastic theoretical framework, microstructure characteristics such as grain size, dislocation density and microcracks in metal are comprehensively considered, and elastic-plastic constitutive and toughness characteristics during uniaxial tension / compression are accurately simulated through numerical calculation. When a low-cycle fatigue hysteretic curve is simulated, cyclic strain loading conditions are set on the basis of the elastic-plastic constitutive model, a curve is generated through numerical calculation, the curve shape, area change and cyclic hardening / softening behaviors can be accurately captured, and a fatigue life prediction model is established according to the curve shape, area change and cyclic hardening / softening behaviors. The model can accurately predict the fatigue life according to a microstructure and loading conditions by combining microscopic and macroscopic relations. The method provides a new way for low-cycle fatigue simulation and life prediction, and provides theoretical guidance for prolonging the life of the gradient material.

Description

Technical Field

[0001] This invention relates to the field of materials science and engineering, specifically a computational method for simulating and predicting the low-cycle fatigue performance and fatigue life of nanostructured metals with gradient grain size distributions. This method combines the material's microstructural characteristics with its macroscopic mechanical properties, and is applicable to materials design, performance evaluation, and service life prediction. Background Art

[0002] Low-cycle fatigue refers to the fatigue failure phenomenon of materials under high strain amplitude and low cycle loading. It is one of the common failure modes of engineering structural materials under complex stress environments. For nanostructured metals with gradient grain size distribution, their microstructural characteristics (such as grain size gradient, dislocation density evolution, and the generation and evolution of microcracks) have a significant impact on low-cycle fatigue performance and fatigue life. However, traditional fatigue life prediction methods are mainly based on empirical formulas or macroscopic mechanical models, which are difficult to accurately reflect the influence of microstructural characteristics on fatigue performance. Therefore, it is of great significance to develop a low-cycle fatigue simulation and life prediction method that can comprehensively consider microstructural characteristics.

[0003] While some research has focused on the fatigue properties of nanostructured metals, most studies have focused on nanomaterials with a single grain size. The inherent connection between the complex microstructure and macroscopic mechanical properties of nanostructured metals with gradient grain size distributions has yet to be fully understood. Furthermore, existing methods for simulating low-cycle fatigue hysteresis curves often fail to accurately capture the shape, area variation, and cyclic hardening / softening behavior of the hysteresis curve, resulting in insufficient fatigue life prediction accuracy. Therefore, a new computational approach is needed to address these issues. Summary of the Invention

[0004] The purpose of the present invention is to address the deficiencies of the prior art and provide a method for calculating the fatigue behavior of gradient structured metals based on deformation mechanism and microstructure composition.

[0005] The object of the present invention is achieved through the following technical solution: a method for calculating the fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition, comprising the following steps:

[0006] (1) Obtain the material parameters and structural information of the metal through experimental characterization, clarify the elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, yield strength of coarse grains, gradient grain size distribution, grain size gradient distribution law of nanostructured metals, true stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures, set the initial conditions of uniaxial tension / compression, and select the appropriate strain loading rate within the quasi-static tension / compression range;

[0007] (2) By adjusting the grain strain gradient parameters included in the elastic-plastic model, the dynamic sensitivity coefficient of the viscoplastic model, the parameters C1, C2, and C3 of the dislocation evolution model, and the maximum number of dislocations or the dislocation slip length coefficient of the back stress model, the elastic, yield, and strengthening stages of the true stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures are simulated and fitted, and all the final model parameters are determined;

[0008] (3) Based on the material parameters and model parameters determined in steps (1) and (2), cyclic strain loading conditions are set to simulate the low-cycle fatigue hysteresis curve of the material and calculate its fatigue life. The grain size gradient distribution law is modified to predict the fatigue life of different grain size gradient structures.

[0009] Furthermore, the step (1) specifically includes the following sub-steps:

[0010] (1.1) Obtain material parameters and structural information of metal materials through experimental characterization, clarifying the elastic modulus, Poisson's ratio, yield strength of coarse grains, grain size of coarse grains, uniaxial tensile / compressive stress-engineering strain curves of coarse grains, engineering stress-strain curves of gradient structures, and gradient grain size distribution of nanostructured metals; the engineering stress-strain curves include three stages: elasticity, yield, and strengthening;

[0011] (1.2) The coarse-grained uniaxial tensile / compressive stress-engineering strain curve is converted into a coarse-grained uniaxial tensile / compressive true stress-strain curve according to the basic mechanical formula, and the gradient structure's uniaxial tensile / compressive engineering stress-strain curve is converted into a gradient structure's uniaxial tensile / compressive true stress-strain curve; the shear modulus and bulk modulus of the metal material are then calculated based on the elastic modulus and Poisson's ratio; the gradient distribution law of the gradient grain size distribution nanostructured metal is then fitted with a continuous function curve to obtain the grain size gradient distribution law used in simulating the gradient structure's uniaxial tensile / compressive true stress-strain curve;

[0012] (1.3) Set the initial conditions of the metal material. The initial elastic-plastic stress and strain of the metal material are set to 0. The initial dislocation density is normalized to 1. The strain loading of the metal material is within the quasi-static loading range, and the strain step is 10 -5 , the strain rate is 10 -1 ~10 -4 s -1 .

[0013] Furthermore, the step (2) specifically includes the following sub-steps:

[0014] (2.1) The Taylor dislocation model calculates the corresponding flow stress by using the dislocation density within the grains and the dislocation density in the grain boundary dislocation accumulation zone simulated by the dislocation evolution model; the dislocation density in the grain boundary dislocation accumulation zone is related to the grain size of the coarse grain, the thickness of the grain boundary dislocation accumulation zone, the grain strain gradient parameter, the geometric parameters, and the size of the Burgers vector; the thickness of the grain boundary dislocation accumulation zone, the geometric parameters, and the size of the Burgers vector are model constants; by adjusting the grain strain gradient parameter included in the elastic-plastic model and the dynamic sensitivity coefficient in the viscoplastic model, the trends of the elastic and yield stages in the simulated true stress-strain curve of the coarse grain under uniaxial tension / compression are consistent with the trends of the elastic and yield stages in the true stress-strain curve of the coarse grain under uniaxial tension / compression obtained by experimental characterization;

[0015] (2.2) Obtain the yield strength and grain size of the coarse crystals of the metal material and the shear modulus of the metal material through experimental characterization to calculate the calculable parameter C1 in the dislocation evolution model;

[0016] (2.3) Adjusting the maximum number of dislocations or the dislocation slip length coefficient in the back stress model and the parameter C2 representing the dislocation multiplication rate or the parameter C3 representing the dislocation annihilation rate in the dislocation evolution model so that the trend of the strengthening stage in the simulated true stress-strain curve of coarse grains under uniaxial tension / compression is consistent with the trend of the strengthening stage in the experimentally characterized true stress-strain curve of coarse grains under uniaxial tension / compression;

[0017] (2.4) Divide the number of layers according to the shape of the metal material, and the grain size of each layer is determined according to the grain size gradient distribution law obtained by fitting in step (1.2); the process of simulating the true stress-strain curve of the uniaxial tension / compression of the gradient structure is compared with the process of simulating the true stress-strain curve of the uniaxial tension / compression of the coarse grain. The material parameters including elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, and yield strength of the coarse grain are the same, but the grain size is different. At the same time, the model parameters including grain strain gradient parameter and dynamic sensitivity coefficient are modified in a small range based on the adjustment in step (2.1) The slightly modified grain strain gradient parameters and dynamic sensitivity coefficients make the trend of the strengthening stage in the simulated true stress-strain curve of coarse-grained uniaxial tension / compression coincide with the trend of the strengthening stage in the true stress-strain curve of coarse-grained uniaxial tension / compression obtained by experimental characterization; however, the maximum number of dislocations or the dislocation slip length coefficient are different, which makes the trends of the elastic and yield stages in the simulated true stress-strain curve of uniaxial tension / compression of the gradient structure coincide with the trends of the elastic and yield stages in the true stress-strain curve of uniaxial tension / compression of the gradient structure obtained by experimental characterization, respectively.

[0018] (2.5) Adjusting the maximum number of dislocations or the dislocation slip length coefficient in the back stress model parameters makes the trend of the strengthening stage in the simulated true stress-strain curve of the gradient structure under uniaxial tension / compression consistent with the trend of the strengthening stage in the experimentally characterized true stress-strain curve of the gradient structure under uniaxial tension / compression;

[0019] (2.6) Repeat steps (2.1) to (2.5) so that the trends of the three stages of elasticity, yielding, and strengthening in the simulated true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures are consistent with the trends of the three stages of elasticity, yielding, and strengthening in the experimentally characterized true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures, respectively, and determine all the final model parameters.

[0020] Furthermore, the step (3) specifically includes the following sub-steps:

[0021] (3.1) Setting cyclic strain loading conditions, simulating fatigue cyclic hysteresis curves for coarse grains and gradient structures respectively; calculating the fatigue cyclic hysteresis energy of the coarse grains through the fatigue cyclic hysteresis curve of the coarse grains, adjusting the fatigue life prediction model parameters based on the cyclic hysteresis energy, and calculating the fatigue life of the coarse grains using the fatigue cyclic hysteresis energy of the coarse grains, which is consistent with the experimental results; and calculating the fatigue cyclic hysteresis energy of the gradient structure through the fatigue cyclic hysteresis curve of the gradient structure, and then calculating the fatigue life of the gradient structure using the fatigue cyclic hysteresis energy of the gradient structure based on the fatigue life prediction model parameters based on the coarse grains, and the experimental data are consistent with each other;

[0022] (3.2) Maintaining all the material parameters determined in step (1) and all the final model parameters, changing the grain size gradient distribution law obtained by fitting in step (1.2), and predicting the fatigue life of different grain size gradient structures.

[0023] The beneficial effects of the present invention are: being able to comprehensively consider low-cycle fatigue simulation of microstructural characteristics, accurately capturing the shape of the hysteresis curve, area variation law and cyclic hardening / softening behavior and performing fatigue life prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The figure is a flow chart of a method for calculating the fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to illustrate the present invention, rather than to represent all embodiments. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0026] This model uses the elastic-plastic constitutive theory of metals to simulate the changes in the stress-strain curve during the tension / compression process of metals. Cyclic strain loading conditions are set to simulate the low-cycle fatigue hysteresis curve. The fatigue life is then predicted based on the fatigue cycle hysteresis energy that can be obtained from the low-cycle fatigue hysteresis curve. The high-temperature elastic-plastic constitutive theory of metals used in this method comprehensively considers microstructural characteristics such as the internal grain size, dislocation density evolution, and the generation and evolution of microcracks at high temperatures. It can accurately reflect the elastic-plastic deformation behavior and damage accumulation process of metal materials during cyclic loading at high temperatures.

[0027] Example 1

[0028] like Figure 1 As shown, the present invention provides a method for calculating the fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition, comprising the following steps:

[0029] (1) Obtain the material parameters and structural information of the metal through experimental characterization, clarify the elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, yield strength of coarse grains, gradient grain size distribution, grain size gradient distribution law of nanostructured metals, and the true stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures, set the initial conditions of uniaxial tension / compression, and select the appropriate strain loading rate (10 -1 ~10 -4 s -1 ).

[0030] The step (1) specifically includes the following sub-steps:

[0031] (1.1) Obtain the material parameters and structural information of metal materials through experimental characterization, and clarify the elastic modulus, Poisson's ratio, yield strength of coarse grains, grain size of coarse grains, uniaxial tensile / compressive stress-engineering strain curve of coarse grains, engineering stress-strain curve of gradient structure, and gradient grain size distribution of nanostructured metals; the engineering stress-strain curve includes three stages: elasticity, yield, and strengthening.

[0032] (1.2) The coarse-grained uniaxial tensile / compressive stress-engineering strain curve is converted into the coarse-grained uniaxial tensile / compressive true stress-strain curve according to the basic mechanical formula, and the gradient structure's uniaxial tensile / compressive engineering stress-strain curve is converted into the gradient structure's uniaxial tensile / compressive true stress-strain curve; the shear modulus and bulk modulus of the metal material are then calculated based on the elastic modulus and Poisson's ratio; the grain size gradient distribution law of the gradient grain size distribution nanostructured metal is then fitted with a continuous function curve to obtain the grain size gradient distribution law used in simulating the gradient structure's uniaxial tensile / compressive true stress-strain curve.

[0033] (1.3) Set the initial conditions of the metal material. The initial elastic-plastic stress and strain of the metal material are set to 0. The initial dislocation density is normalized to 1. The strain loading of the metal material is within the quasi-static loading range, the strain step is 10-5, and the strain rate is 10 -1 ~10 -4 s -1 .

[0034] (2) By adjusting the grain strain gradient parameters included in the elastic-plastic model, the dynamic sensitivity coefficient of the viscoplastic model, the parameters C1, C2 and C3 of the dislocation evolution model, and the maximum number of dislocations or the dislocation slip length coefficient of the back stress model, the elastic, yield and strengthening stages of the real stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures are simulated and fitted respectively, and all the final model parameters are determined.

[0035] The step (2) specifically includes the following sub-steps:

[0036] (2.1) The Taylor dislocation model calculates the corresponding flow stress by using the dislocation density within the grains and the dislocation density in the grain boundary dislocation accumulation zone simulated by the dislocation evolution model; the dislocation density in the grain boundary dislocation accumulation zone is related to the grain size of the coarse grain, the thickness of the grain boundary dislocation accumulation zone, the grain strain gradient parameter, the geometric parameters, and the size of the Burgers vector; the thickness of the grain boundary dislocation accumulation zone, the geometric parameters, and the size of the Burgers vector are model constants; by adjusting the grain strain gradient parameter contained in the elastic-plastic model and the dynamic sensitivity coefficient in the viscoplastic model, the trends of the elastic and yield stages in the simulated true stress-strain curve of the coarse grain under uniaxial tension / compression are consistent with the trends of the elastic and yield stages in the true stress-strain curve of the coarse grain under uniaxial tension / compression obtained by experimental characterization.

[0037] (2.2) The yield strength and grain size of the coarse crystals of the metal material and the shear modulus of the metal material are obtained through experimental characterization to calculate the calculable parameter C1 in the dislocation evolution model.

[0038] (2.3) Adjust the maximum number of dislocations or the dislocation slip length coefficient in the back stress model and the parameter C2 representing the dislocation multiplication rate or the parameter C3 representing the dislocation annihilation rate in the dislocation evolution model, so that the trend of the strengthening stage in the simulated true stress-strain curve of the coarse grain under uniaxial tension / compression is consistent with the trend of the strengthening stage in the true stress-strain curve of the coarse grain under uniaxial tension / compression obtained by experimental characterization.

[0039] (2.4) Divide the number of layers according to the shape of the metal material, and the grain size of each layer is determined according to the grain size gradient distribution law obtained by fitting in step (1.2); the process of simulating the true stress-strain curve of the uniaxial tension / compression of the gradient structure is compared with the process of simulating the true stress-strain curve of the uniaxial tension / compression of the coarse grain. The material parameters including elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, and yield strength of the coarse grain are the same, but the grain size is different. At the same time, the model parameters including grain strain gradient parameter and dynamic sensitivity coefficient are modified in a small range based on the adjustment in step (2.1) The slightly modified grain strain gradient parameters and dynamic sensitivity coefficients make the trend of the strengthening stage in the simulated true stress-strain curve of coarse-grained uniaxial tension / compression consistent with the trend of the strengthening stage in the true stress-strain curve of coarse-grained uniaxial tension / compression obtained by experimental characterization; but the maximum number of dislocations or the dislocation slip length coefficient is different, which makes the trends of the elastic and yield stages in the simulated true stress-strain curve of the gradient structure under uniaxial tension / compression consistent with the trends of the elastic and yield stages in the true stress-strain curve of the gradient structure under uniaxial tension / compression obtained by experimental characterization.

[0040] (2.5) The maximum number of dislocations or the dislocation slip length coefficient in the back stress model parameters is adjusted so that the trend of the strengthening stage in the true stress-strain curve of the uniaxial tension / compression of the gradient structure obtained by simulation is consistent with the trend of the strengthening stage in the true stress-strain curve of the uniaxial tension / compression of the gradient structure obtained by experimental characterization.

[0041] (2.6) Repeat steps (2.1) to (2.5) so that the trends of the three stages of elasticity, yielding, and strengthening in the simulated true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures are consistent with the trends of the three stages of elasticity, yielding, and strengthening in the experimentally characterized true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures, respectively, and determine all the final model parameters.

[0042] (3) Based on the material parameters and model parameters determined in steps (1) and (2), cyclic strain loading conditions are set to simulate the low-cycle fatigue hysteresis curve of the material and calculate its fatigue life. The grain size gradient distribution law is modified to predict the fatigue life of different grain size gradient structures.

[0043] The step (3) specifically includes the following sub-steps:

[0044] (3.1) Cyclic strain loading conditions were set to simulate the fatigue cyclic hysteresis curves of coarse grains and gradient structures respectively; the fatigue cyclic hysteresis energy of coarse grains was calculated through the fatigue cyclic hysteresis curve of coarse grains, the fatigue life prediction model parameters based on cyclic hysteresis energy were adjusted, and the fatigue life of coarse grains was calculated using the fatigue cyclic hysteresis energy of coarse grains, which was consistent with the experimental results; and the fatigue cyclic hysteresis energy of gradient structure was calculated through the fatigue cyclic hysteresis curve of gradient structure, and based on the fatigue life prediction model parameters of the cyclic hysteresis energy of coarse grains, the fatigue life of gradient structure was calculated using the fatigue cyclic hysteresis energy of gradient structure, which was consistent with the experimental data.

[0045] (3.2) Maintaining all the material parameters determined in step (1) and all the final model parameters, changing the grain size gradient distribution law obtained by fitting in step (1.2), and predicting the fatigue life of different grain size gradient structures.

[0046] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for calculating fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition, characterized in that: The following steps are involved: (1) Obtain the material parameters and structural information of the metal through experimental characterization, clarify the elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, yield strength of coarse grains, gradient grain size distribution, grain size gradient distribution law of nanostructured metals, true stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures, set the initial conditions of uniaxial tension / compression, and select the appropriate strain loading rate within the quasi-static tension / compression range; (2) By adjusting the grain strain gradient parameters included in the elastic-plastic model, the dynamic sensitivity coefficient of the viscoplastic model, the parameters C1, C2, and C3 of the dislocation evolution model, and the maximum number of dislocations or the dislocation slip length coefficient of the back stress model, the elastic, yield, and strengthening stages of the true stress-strain curves of uniaxial tension / compression of coarse grains and gradient structures are simulated and fitted, and all the final model parameters are determined; (3) Based on the material parameters and model parameters determined in steps (1) and (2), cyclic strain loading conditions are set to simulate the low-cycle fatigue hysteresis curve of the material and calculate its fatigue life. The grain size gradient distribution law is modified to predict the fatigue life of different grain size gradient structures.

2. The method for calculating fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition according to claim 1, characterized in that: The step (1) specifically includes the following sub-steps: (1.1) Obtain material parameters and structural information of metal materials through experimental characterization, clarifying the elastic modulus, Poisson's ratio, yield strength of coarse grains, grain size of coarse grains, uniaxial tensile / compressive stress-engineering strain curves of coarse grains, engineering stress-strain curves of gradient structures, and gradient grain size distribution of nanostructured metals; the engineering stress-strain curves include three stages: elasticity, yield, and strengthening; (1.2) The coarse-grained uniaxial tension / compression stress-engineering strain curve is converted into the coarse-grained uniaxial tension / compression true stress-strain curve according to the basic mechanical formula, and the gradient structure's uniaxial tension / compression engineering stress-strain curve is converted into the gradient structure's uniaxial tension / compression true stress-strain curve; the shear modulus and bulk modulus of the metal material are then calculated based on the elastic modulus and Poisson's ratio; Then, the grain size gradient distribution law of the gradient grain size distribution nanostructured metal is fitted with a continuous function curve to obtain the grain size gradient distribution law used in simulating the real stress-strain curve of the uniaxial tension / compression of the gradient structure; (1.3) Set the initial conditions of the metal material. The initial elastic-plastic stress and strain of the metal material are set to 0. The initial dislocation density is normalized to 1. The strain loading of the metal material is within the quasi-static loading range, and the strain step is 10 -5 , the strain rate is 10 -1 ~10 -4 s -1 .

3. The method for calculating fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition according to claim 2, characterized in that: The step (2) specifically includes the following sub-steps: (2.1) The Taylor dislocation model calculates the corresponding flow stress by using the dislocation density within the grains and the dislocation density in the grain boundary dislocation accumulation zone simulated by the dislocation evolution model; the dislocation density in the grain boundary dislocation accumulation zone is related to the grain size of the coarse grain, the thickness of the grain boundary dislocation accumulation zone, the grain strain gradient parameter, the geometric parameters, and the size of the Burgers vector; the thickness of the grain boundary dislocation accumulation zone, the geometric parameters, and the size of the Burgers vector are model constants; by adjusting the grain strain gradient parameter included in the elastic-plastic model and the dynamic sensitivity coefficient in the viscoplastic model, the trends of the elastic and yield stages in the simulated true stress-strain curve of the coarse grain under uniaxial tension / compression are consistent with the trends of the elastic and yield stages in the true stress-strain curve of the coarse grain under uniaxial tension / compression obtained by experimental characterization; (2.2) Obtain the yield strength and grain size of the coarse crystals of the metal material and the shear modulus of the metal material through experimental characterization to calculate the calculable parameter C1 in the dislocation evolution model; (2.3) Adjusting the maximum number of dislocations or the dislocation slip length coefficient in the back stress model and the parameter C2 representing the dislocation multiplication rate or the parameter C3 representing the dislocation annihilation rate in the dislocation evolution model so that the trend of the strengthening stage in the simulated true stress-strain curve of coarse grains under uniaxial tension / compression is consistent with the trend of the strengthening stage in the experimentally characterized true stress-strain curve of coarse grains under uniaxial tension / compression; (2.4) Divide the number of layers according to the shape of the metal material, and determine the grain size of each layer according to the grain size gradient distribution law obtained by fitting in step (1.2); The process of simulating the true stress-strain curve of the uniaxial tension / compression of the gradient structure is compared with the process of simulating the true stress-strain curve of the uniaxial tension / compression of the coarse grains. The material parameters including the elastic modulus, Poisson's ratio, Burgers vector, Taylor parameter, and yield strength of the coarse grains are the same, but the grain sizes are different. At the same time, the model parameters including the grain strain gradient parameter and the dynamic sensitivity coefficient are slightly modified based on the adjustment in step (2.1). The slightly modified grain strain gradient parameter and dynamic sensitivity coefficient make the trend of the strengthening stage in the true stress-strain curve of the uniaxial tension / compression of the coarse grains obtained by simulation consistent with the trend of the strengthening stage in the true stress-strain curve of the uniaxial tension / compression of the coarse grains obtained by experimental characterization; however, the maximum number of dislocations or the dislocation slip length coefficient is different, so that the trends of the elastic and yield stages in the true stress-strain curve of the uniaxial tension / compression of the gradient structure obtained by simulation consistent with the trends of the elastic and yield stages in the true stress-strain curve of the uniaxial tension / compression of the gradient structure obtained by experimental characterization, respectively. (2.5) Adjusting the maximum number of dislocations or the dislocation slip length coefficient in the back stress model parameters makes the trend of the strengthening stage in the simulated true stress-strain curve of the gradient structure under uniaxial tension / compression consistent with the trend of the strengthening stage in the experimentally characterized true stress-strain curve of the gradient structure under uniaxial tension / compression; (2.6) Repeat steps (2.1) to (2.5) so that the trends of the three stages of elasticity, yielding, and strengthening in the simulated true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures are consistent with the trends of the three stages of elasticity, yielding, and strengthening in the experimentally characterized true stress-strain curves of uniaxial tension / compression of coarse-grained and gradient structures, respectively, and determine all the final model parameters.

4. The method for calculating fatigue behavior of gradient structure metal based on deformation mechanism and microstructure composition according to claim 1, characterized in that: The step (3) specifically includes the following sub-steps: (3.1) Setting cyclic strain loading conditions, simulating fatigue cyclic hysteresis curves for coarse-grained and gradient structures, respectively; calculating the fatigue cyclic hysteresis energy of the coarse-grained structure from the fatigue cyclic hysteresis curve of the coarse-grained structure, adjusting the parameters of the fatigue life prediction model based on the cyclic hysteresis energy, and calculating the fatigue life of the coarse-grained structure using the fatigue cyclic hysteresis energy of the coarse-grained structure, which is consistent with the experimental results; The fatigue cycle hysteresis energy of the gradient structure was calculated through the fatigue cycle hysteresis curve of the gradient structure. Based on the fatigue life prediction model parameters of the coarse grain hysteresis energy, the fatigue life of the gradient structure was calculated using the fatigue cycle hysteresis energy of the gradient structure, which was consistent with the experimental data. (3.2) Maintaining all the material parameters determined in step (1) and all the final model parameters, changing the grain size gradient distribution law obtained by fitting in step (1.2), and predicting the fatigue life of different grain size gradient structures.

Images