Improved Chboche model suitable for friction stir welding and parameter identification method of improved Chboche model

Abstract

The invention provides an improved Chboche model suitable for friction stir welding. According to the improved Chboche model, the tension and compression response is judged through the difference value between elastic tentative stress and total back stress; equivalent plastic strain and process peak residual strain are introduced to characterize elastic modulus degradation and isotropic softening and softening behaviors; characterizing follow-up hardening by adopting superposition of multiple groups of independent nonlinear components; and respectively calibrating elastic modulus degradation, isotropic softening and softening and follow-up hardening parameters of the tensile domain and the compression domain so as to realize optional tension-compression response asymmetry modeling. The invention further provides a parameter identification method of the improved Chboche model suitable for friction stir welding. According to the method, by improving the multi-mechanism coupling characterization capacity of the Chboch model and combining the swarm intelligence optimization algorithm, an efficient tool is provided for fatigue life prediction and structure optimization of the friction stir welding joint, and the engineering application value of numerical simulation is remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of friction stir welding, and in particular to an improved Chaboche model suitable for friction stir welding and a parameter identification method thereof. Background Art

[0002] Friction stir welding is a solid-phase joining process. Its basic principle is to rapidly heat the material in the joint area to a visco-plastic state through the friction and extrusion between the high-speed rotating stirring head and the workpiece to be welded. As the stirring head moves along the joint path at a certain forward speed, a stable plastic material flow zone is formed behind it. Under the extrusion of the stirring head shoulder, the plasticized material is re-compacted and cooled to form a dense, continuous and firmly bonded weld. Compared with traditional fusion welding processes such as TIG welding or MIG welding, the friction stir welding process significantly reduces the risk of welding deformation and thermal cracking due to its lower heat input and temperature gradient. Its welded joints not only show the advantages of high strength and low residual stress, but also have the advantages of fewer defects and no need for filler welding materials. It has been successfully used in aerospace, automotive manufacturing, industrial construction and other fields, and has shown broad application prospects in the connection of aluminum-based materials.

[0003] In actual service, friction stir welded aluminum alloy butt joints are often subjected to low-cycle cyclic loading, and their mechanical response is significantly dependent on the existing plastic loading history. To accurately characterize the nonlinear mechanical response of metal materials under low-cycle cyclic loading in numerical simulations, existing technologies usually use cyclic constitutive models for finite element modeling and analysis, such as the Dafalias-Popov hyperboloid model and the traditional Chaboche model. A reasonable cyclic constitutive model can not only characterize the nonlinear behaviors of materials such as strain hardening effect, temperature effect, and strain rate effect under low-cycle cyclic loading, but also effectively capture complex mechanical phenomena such as memory effect, Bauschinger effect, and ratcheting effect. The construction of a cyclic constitutive model is of great significance for the design and optimization of structural parts. It can provide a reliable numerical basis for achieving high-precision simulation of structural mechanical response under complex service conditions, thereby improving material utilization efficiency and reducing manufacturing costs.

[0004] The hysteresis curves of friction stir welded aluminum alloy butt joints exhibit plump, spindle-shaped characteristics. During cyclic loading, the joints exhibit significant loading path dependence, influenced by the coupling of multiple mechanisms, including dislocation density evolution and material microstructure damage accumulation. Under different loading regimes, friction stir welded aluminum alloy butt joints exhibit significant differences in mechanical properties, including elastic modulus degradation, isotropic soft hardening, and asymmetric tensile and compressive responses. The traditional Chaboche model struggles to effectively characterize these complex characteristics. With the rapid advancement of simulation technology, although various improved cyclic constitutive models have been proposed, they generally suffer from complex model structures, low computational efficiency, limited accuracy, and cumbersome parameter identification, making them difficult to meet the practical needs of rapid prediction and performance evaluation in engineering. Therefore, a cyclic constitutive model for friction stir welded aluminum alloy butt joints with clear physical mechanisms, efficient computational performance, and a simple parameter identification process is urgently needed to support the numerical simulation and engineering applications of these joints in fields such as aviation, automotive, and construction. Summary of the Invention

[0005] To solve the above problems, the present invention aims to propose an improved Chaboche model suitable for friction stir welding and its parameter identification method. By improving the multi-mechanism coupling characterization capability of the Chaboche model and combining it with an intelligent parameter optimization method, an efficient tool is provided for fatigue life prediction and structural optimization of friction stir welded joints, significantly improving the engineering application value of numerical simulation.

[0006] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0007] An improved Chaboche model suitable for friction stir welding is disclosed. The improved Chaboche model discriminates the tensile and compressive responses by using the difference between the elastic test stress and the total back stress; introduces equivalent plastic strain and peak residual strain to characterize the elastic modulus degradation and isotropic soft hardening behavior; characterizes the kinematic hardening by superposing multiple independent nonlinear components; and calibrates the elastic modulus degradation, isotropic soft hardening, and kinematic hardening parameters in the tensile and compressive domains, respectively, to achieve optional asymmetric modeling of the tensile and compressive responses.

[0008] Furthermore, the elastic stiffness matrix of the improved Chaboche model is:

[0009]

[0010] Where C is the elastic stiffness matrix; λ is the first Lamé parameter; G is the shear modulus; v is the Poisson's ratio; E n is the elastic modulus at the current moment; E0 is the initial elastic modulus; E sat is the saturation value of elastic modulus degradation; ω and μ are parameters that control the degradation rate of elastic modulus; is the equivalent plastic strain; ε p,m is the peak residual strain; ε is the total strain; σ is the Von Mises stress.

[0011] Furthermore, the yield criterion and hardening criterion of the improved Chaboche model are:

[0012]

[0013] Where f is the yield function; σ e is the equivalent stress; σ|0 is the initial yield stress; S is the deviatoric stress tensor; α is the back stress tensor; R is the isotropic soft hardening component; α i is the i-th back stress component; N is the number of back stress groups. By increasing the N value, the kinematic hardening accuracy can be improved; C i and γ i is the kinematic hardening parameter; Q ∞ and D ∞ are the hardening saturation value and softening saturation value respectively; b and a are the isotropic hardening rate and softening rate respectively; k and r are the material parameters that control the soft hardening saturation value respectively; is the equivalent plastic strain increment.

[0014] Furthermore, the flow criterion of the improved Chaboche model is:

[0015]

[0016] Among them, dε p is the plastic strain increment tensor; dη is the plastic multiplier; σ′ is the stress tensor.

[0017] Furthermore, the tensile and compressive response criterion of the improved Chaboche model is:

[0018]

[0019] Among them, σ trial is the current elastic test stress; α is the total back stress.

[0020] Furthermore, the improved Chaboche model adopts a tension-compression dual-domain definition method for the model parameter system, with a total number of parameters of 22+4N, where N is the number of back stress groups; the model parameters are specifically composed as follows: Tensile domain parameters (11+2N): E 0,拉 、E sat,拉 、ω 拉 、μ 拉 、 b 拉 、a 拉 、k 拉 、r拉 、σ| 0,拉 and N Group C i,拉 and γ i,拉 (i=1,2,3…N); compression domain parameter (11+2N): E 0,压 、E sat,压 、ω 压 、μ 压 、 b 压 、a 压 、k 压 、r 压 、σ| 0,压 and N Group C i,压 and γ i,压 (i=1,2,3…N).

[0021] Furthermore, for materials with symmetrical characteristics of tension and compression response, with back stress as the symmetry center, the improved Chaboche model is simplified to be defined using only the tension domain parameters, and the compression domain parameters are set to be the same as the tension domain parameters, i.e., E 0,拉 =E 0,压 、E sat,拉 =E sat,压 、ω 拉 =ω 压 、μ 拉 =μ 压 、 b 拉 =b 压 、a 拉 =a 压 、k 拉 =k 压 、r 拉 =r 压 、σ| 0,拉 =σ| 0,压 and C i,拉 =C i,压 and γ i,拉 =γ i,压 (i=1,2,3…N).

[0022] Furthermore, for materials that undergo compressive buckling and tension-compression asymmetry, the improved Chaboche model independently defines the tension domain and compression domain parameter groups and establishes a tension-compression dual-domain constitutive relationship to achieve differentiated characterization of compression and tension behaviors.

[0023] In order to achieve the above object, the present invention also provides a parameter identification method of an improved Chaboche model suitable for friction stir welding, comprising the following steps:

[0024] S1: Low-cycle loading tests were performed on friction stir welded aluminum alloy butt joint specimens under various loading conditions to collect complete hysteresis curve data.

[0025] S2: Based on the equivalent plastic strain, peak residual strain, elastic test stress, and total back stress, an improved Chaboche cyclic constitutive model with elastic modulus degradation, kinematic hardening, isotropic soft hardening, and optional asymmetric tensile and compressive response characteristics is constructed, and the model parameter set that needs to be identified is determined accordingly;

[0026] S3: Based on the experimentally obtained hysteresis curve data, the improved Chaboche model is inverted using the sparrow search algorithm to minimize the deviation between the model predicted stress and the experimental stress, and finally the optimal model parameter solution set is obtained; its fitness function is:

[0027]

[0028] Among them, σ opt Predict stress for the model; σ exp is the stress measured in the test, K is the total number of measurement points of all test pieces or the total number of data points after data noise reduction processing;

[0029] During the global optimization process, the explorer position is updated as follows:

[0030]

[0031] Among them, X i,j is the position of the i-th sparrow in the j-th dimension; n is the current iteration number; κ max is the maximum number of iterations; α s is a random number between 0 and 1 and satisfies α s ≠0; Q is a random number that follows a normal distribution; L is a row vector containing d elements 1; W T and S T They are warning value and safety value respectively;

[0032] During the global optimization process, the joiner position is updated as follows:

[0033]

[0034] Among them, X p is the optimal position of the current explorer; X W is the current global worst position; A + is a row vector containing d elements 1 or -1, and satisfies A + =A T (AA T ) -1 ;

[0035] During the global optimization process, the position of the sentinel is updated as follows:

[0036]

[0037] Among them, X b is the current global optimal position; β and η are random numbers; f i 、f g and f w are the fitness values ​​of the current individual, the current global optimal solution, and the current global worst solution respectively; Ψ is a non-zero decimal.

[0038] Furthermore, the parameter value range of the improved Chaboche model is determined by trial and error, and the improved Chaboche model adopts Latin hypercube sampling and initializes the population in a multidimensional parameter space.

[0039] Beneficial effects: The present invention improves the multi-mechanism coupling characterization capability of the Chaboche model and combines it with the swarm intelligence optimization algorithm to provide an efficient tool for fatigue life prediction and structural optimization of stir friction welded joints, significantly enhancing the engineering application value of numerical simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 This is an overall flow chart of a parameter identification method for an improved Chaboche model applicable to friction stir welding according to an embodiment of the present invention;

[0042] Figure 2 The following is a comparison diagram of hysteresis curves drawn using the improved Chaboche model parameter identification method for friction stir welding for 6061-T6 friction stir welded aluminum alloy butt joint specimens under three low-cycle loading regimes and experimental measured data under the conditions of N=3 and the compression domain parameters being equal to the tension domain parameters;

[0043] Figure 3 The following is a comparison diagram of the hysteresis curves drawn using the parameter identification method of the improved Chaboche model for friction stir welding under three low-cycle loading regimes and the measured data for a 7075-T6 friction stir welded aluminum alloy butt joint test piece under the conditions of N=3 and unequal compression domain parameters and tension domain parameters;

[0044] Figure 4A schematic diagram of a friction stir welding aluminum alloy plate welding process to which the parameter identification method of the improved Chaboche model suitable for friction stir welding is applicable;

[0045] Figure 5 A schematic diagram of a sampling position of a test piece applicable to the parameter identification method of the improved Chaboche model for friction stir welding;

[0046] Figure 6 for Figure 2 Schematic diagram of the loading system for the 6061-T6 friction stir welded aluminum alloy butt joint test piece;

[0047] Figure 7 for Figure 3 Schematic diagram of the loading system for the 7075-T6 friction stir welded aluminum alloy butt joint test piece;

[0048] Figure 8 Based on Figure 2 The elastic modulus degradation surface and isotropic soft hardening evolution surface of the improved Chaboche cyclic constitutive model calibrated by the hysteresis curve of the 6061-T6 friction stir welded aluminum alloy butt joint specimen;

[0049] Figure 9 When some compression domain parameters are 0 times, 1 / 4 times, 1 / 2 times, 3 / 4 times, 1 times and 1.5 times of the stretch domain parameters, use Figure 6 The hysteresis curve drawn for medium loading regime 3;

[0050] Figure 10 Schematic diagram of the peak residual strain. DETAILED DESCRIPTION

[0051] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0052] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0053] Example 1

[0054] An improved Chaboche model suitable for friction stir welding is disclosed. The improved Chaboche model discriminates the tensile and compressive responses by using the difference between the elastic test stress and the total back stress; introduces equivalent plastic strain and peak residual strain to characterize the elastic modulus degradation and isotropic soft hardening behavior; characterizes the kinematic hardening by superposing multiple independent nonlinear components; and calibrates the elastic modulus degradation, isotropic soft hardening, and kinematic hardening parameters in the tensile and compressive domains, respectively, to achieve optional asymmetric modeling of the tensile and compressive responses.

[0055] In a specific example, the elastic stiffness matrix of the improved Chaboche model is:

[0056]

[0057] Where C is the elastic stiffness matrix; λ is the first Lamé parameter; G is the shear modulus; v is the Poisson's ratio; E n is the elastic modulus at the current moment; E0 is the initial elastic modulus; E sat is the saturation value of elastic modulus degradation; ω and μ are parameters that control the degradation rate of elastic modulus; is the equivalent plastic strain; ε p,m is the peak residual strain; ε is the total strain; σ is the Von Mises stress.

[0058] In a specific example, the yield criterion and hardening criterion of the improved Chaboche model are:

[0059]

[0060] Where f is the yield function; σ e is the equivalent stress; σ|0 is the initial yield stress; S is the deviatoric stress tensor; α is the back stress tensor; R is the isotropic soft hardening component; α i is the i-th back stress component; N is the number of back stress groups. By increasing the N value, the kinematic hardening accuracy can be improved; C i and γ i is the kinematic hardening parameter; Q ∞ and D ∞ are the hardening saturation value and softening saturation value respectively; b and a are the isotropic hardening rate and softening rate respectively; k and r are the material parameters that control the soft hardening saturation value respectively; is the equivalent plastic strain increment.

[0061] In a specific example, the flow criterion of the modified Chaboche model is:

[0062]

[0063] Among them, dε p is the plastic strain increment tensor; dη is the plastic multiplier; σ′ is the stress tensor.

[0064] In a specific example, the tensile and compressive response criterion of the improved Chaboche model is:

[0065]

[0066] Among them, σ trial is the current elastic test stress; α is the total back stress.

[0067] In a specific example, the improved Chaboche model adopts a tension-compression dual-domain definition method, and the total number of parameters is 22+4N, where N is the number of back stress groups; the model parameters are specifically composed as follows: Tensile domain parameters (11+2N): E 0,拉 、E sat,拉 、ω 拉 、μ 拉 、 b 拉 、a 拉 、k 拉 、r 拉 、σ| 0,拉 and N Group C i,拉 and γ i,拉 (i=1,2,3…N); compression domain parameter (11+2N): E 0,压 、E sat, pressure, ω pressure, μ pressure, b pressure, a pressure, k pressure, r pressure, σ| 0, Pressure and N group C i, Pressure and γ i, Pressure (i=1,2,3...N).

[0068] In a specific example, for a material with symmetrical characteristics of tension and compression response (with back stress as the symmetry center), the improved Chaboche model is simplified to be defined using only the tension domain parameters, and the compression domain parameters are set to be the same as the tension domain parameters, that is, E 0,拉 =E 0,压 、E sat,拉 =E sat,压 、ω 拉 =ω 压 、μ 拉 =μ 压 、 b 拉 =b 压 、a 拉 =a 压 、k 拉 =k 压 、r 拉 =r 压 、σ| 0,拉 =σ| 0,压 and C i,拉 =C i,压 and γ i,拉 =γ i,压 (i=1,2,3…N).

[0069] In a specific example, for materials that undergo compressive buckling and tension-compression asymmetry, the improved Chaboche model independently defines parameter groups for the tension domain and the compression domain and establishes a tension-compression dual-domain constitutive relationship to achieve differentiated characterization of compression and tension behaviors.

[0070] In summary, this embodiment achieves:

[0071] Elastic modulus degradation: By introducing equivalent plastic strain and peak residual strain, the elastic modulus is dynamically adjusted to characterize the stiffness attenuation characteristics of the material during cyclic loading.

[0072] Isotropic soft hardening: Dual-domain parameters (tension / compression) are used to describe the soft hardening behavior of yield stress, solving the problem that traditional models cannot reflect the asymmetric response of tension and compression.

[0073] Kinematic hardening: By superimposing multiple sets of nonlinear back stress components, the adaptability to complex back stress paths is enhanced.

[0074] Tensile and compressive response criterion: Based on the difference between the elastic test stress and the total back stress, the mechanical behavior in the tension and compression domains is dynamically distinguished.

[0075] Example 2

[0076] To achieve the above purpose, see Figure 1-10 This embodiment also provides a parameter identification method of an improved Chaboche model applicable to friction stir welding, comprising the following steps:

[0077] S1: Low-cycle loading tests were performed on friction stir welded aluminum alloy butt joint specimens under various loading conditions to collect complete hysteresis curve data.

[0078] S2: Based on the equivalent plastic strain, peak residual strain, elastic test stress, and total back stress, an improved Chaboche cyclic constitutive model with elastic modulus degradation, kinematic hardening, isotropic soft hardening, and optional asymmetric tensile and compressive response characteristics is constructed, and the model parameter set that needs to be identified is determined accordingly;

[0079] S3: Based on the experimentally obtained hysteresis curve data, the improved Chaboche model is inverted using the sparrow search algorithm to minimize the deviation between the model predicted stress and the experimental stress, and finally the optimal model parameter solution set is obtained; its fitness function is:

[0080]

[0081] Among them, σ opt Predict stress for the model; σ expis the stress measured in the test, K is the total number of measurement points of all test pieces or the total number of data points after data noise reduction processing;

[0082] During the global optimization process, the explorer position is updated as follows:

[0083]

[0084] Among them, X i,j is the position of the i-th sparrow in the j-th dimension; n is the current iteration number; κ max is the maximum number of iterations; α s is a random number between 0 and 1 and satisfies α s ≠0; Q is a random number that follows a normal distribution; L is a row vector containing d elements 1; W T and S T They are warning value and safety value respectively;

[0085] During the global optimization process, the joiner position is updated as follows:

[0086]

[0087] Among them, X p is the optimal position of the current explorer; X W is the current global worst position; A + is a row vector containing d elements 1 or -1, and satisfies A + =A T (AA T ) -1 ;

[0088] During the global optimization process, the position of the sentinel is updated as follows:

[0089]

[0090] Among them, X b is the current global optimal position; β and η are random numbers; f i 、f g and f w are the fitness values ​​of the current individual, the current global optimal solution, and the current global worst solution respectively; Ψ is a non-zero decimal.

[0091] This embodiment effectively solves the problem that the traditional single constitutive model is difficult to accurately reflect the differences in mechanical characteristics of stir friction welded aluminum alloy butt joints under different loading regimes, including behaviors such as elastic modulus degradation, isotropic soft hardening and asymmetric tension and compression response. The proposed improved Chaboche cyclic constitutive model has a clear physical mechanism, the meaning of each parameter is clear, and it has good computational efficiency. The sparrow search algorithm is used to inversely optimize the model parameters, effectively avoiding the problem of easily falling into local optimal solutions in high-dimensional parameter identification. Through this method, a cyclic constitutive model that is applicable to a variety of loading regimes and can accurately characterize the asymmetric mechanism of tension and compression response can be established, so as to analyze and apply stir friction welded aluminum alloy structures in advanced analysis and engineering fields. This embodiment has the advantages of being fast, accurate, easy to operate, effective and feasible.

[0092] In a specific example, in order to improve recognition efficiency and stability, the parameter value range of the improved Chaboche model is determined by trial and error. The improved Chaboche model adopts Latin hypercube sampling and initializes the population in a multidimensional parameter space.

[0093] It should be noted that this embodiment calculates the peak residual strain of the history by the forward Euler method; when computing resources are insufficient, the dimension of the search space can be selectively reduced by fixing some parameters; the stir friction welded aluminum alloy butt joint test pieces of all load conditions should be measured using an extensometer with the same gauge length; the aluminum alloy base material can also use an improved Chaboche cyclic constitutive model as the material model for numerical simulation; when performing numerical simulation, the improved Chaboche cyclic constitutive model of the stir friction welded aluminum alloy butt joint test piece is input into the area within the extensometer gauge length of the stir friction welded aluminum alloy butt joint test piece, and the improved Chaboche cyclic constitutive model of the aluminum alloy base material is input into the area outside the extensometer gauge length of the test piece to improve the simulation accuracy.

[0094] In summary, the sparrow optimization algorithm (SSA) of this embodiment uses the experimental hysteresis curve as a benchmark to construct a fitness function to minimize the error between the predicted and measured stresses.

[0095] Explorer, Joiner, and Sentinel Position Update: The position update strategy integrates random factors and early warning mechanisms to achieve a balance between global exploration and local development. By referencing the current optimal and worst individual positions to guide the population search direction, it effectively improves the ability to escape the local optimum.

[0096] Parameter initialization: Latin hypercube sampling is used to optimize the parameter space search efficiency and support high-dimensional (22+4N) parameter inversion.

[0097] Parameter simplification: If computing resources are limited, some parameters (such as the compression domain parameters of symmetric materials) can be fixed to reduce the dimension.

[0098] Experimental verification and application:

[0099] In a specific implementation, this embodiment can be further illustrated by using the test data of 6061-T6 friction stir welding aluminum alloy butt joint test pieces and 7075-T6 friction stir welding aluminum alloy butt joint test pieces under three low-cycle cyclic loading systems. The schematic diagram of the friction stir welding process of all aluminum alloy plates is shown in FIG. Figure 4 As shown, the sampling position and shape of the test piece are shown in Figure 5 shown.

[0100] The specific operation method is as follows:

[0101] S1: Three groups of 6061-T6 friction stir welded aluminum alloy butt joint test pieces were tested in the following manner: Figure 6 The low cycle loading test was carried out under the load conditions shown in the figure. Three groups of 7075-T6 friction stir welded aluminum alloy butt joint test pieces were tested under the following conditions: Figure 7 A low-cycle loading test was conducted under the load conditions shown, and complete hysteresis curve data was collected;

[0102] S2: Based on the assumption of volume conservation, the formula σ is used true =σ eng (1+ε eng ) and ε true =ln(1+ε eng ) The engineering stress-strain data of the hysteresis curves of the 6061-T6 friction stir welded aluminum alloy butt joint specimens and the 7075-T6 friction stir welded aluminum alloy butt joint specimens were converted into true stress-strain data. true and ε true are true stress and true strain, σ eng and ε eng are engineering stress and engineering strain, respectively;

[0103] S3: Based on the equivalent plastic strain, peak residual strain, elastic test stress, and total back stress, an improved Chaboche cyclic constitutive model with elastic modulus degradation, kinematic hardening, isotropic soft hardening, and symmetric tension-compression response mechanisms is constructed. For the 6061-T6 friction stir welded aluminum alloy butt joint specimen, N = 3 is selected, and the compression domain parameters and the tension domain parameters are set to the same. The model parameter set that needs to be identified includes 17 sets of tension domain parameters: E 0,拉 、E sat,拉 、ω 拉 、μ 拉 、 b 拉 、a拉 、k 拉 、r 拉 、σ| 0,拉 , C 1,拉 , C 2,拉 , C 3,拉 , γ 1,拉 , γ 2,拉 , γ 3,拉 For the 7075-T6 friction stir welded aluminum alloy butt joint test piece, select N = 3, set the compression domain parameters and the tension domain parameters respectively, then the model parameter set to be identified includes 17 groups of tension domain parameters: E 0,拉 、E sat,拉 、ω 拉 、μ 拉 、 b 拉 、a 拉 、k 拉 、r 拉 、σ| 0,拉 , C 1,拉 , C 2,拉 , C 3,拉 , γ 1,拉 , γ 2,拉 , γ 3,拉 ; and 17 groups of compression domain parameters: E 0,压 、E sat,压 、ω 压 、μ 压 、 b 压 、a 压 、k 压 、r 压 、σ| 0,压 , C 1,压 , C 2,压 , C 3,压 , γ 1,压 , γ 2,压 , γ 3,压 , a total of 34 sets of model parameters.

[0104] S4: Based on the experimentally obtained hysteresis curve data, the sparrow search algorithm is used to perform parameter inversion calculations on the improved Chaboche cycle constitutive model to minimize the deviation between the model predicted stress and the experimental stress, and finally obtain the optimal model parameter solution set.

[0105] The hysteresis curves drawn by the method for 6061-T6 friction stir welded aluminum alloy butt joint test pieces under three low-cycle cyclic loading systems are compared with the experimental measured data. Figure 2 , the final recognition model parameters are shown in Table 1:

[0106] Table 1

[0107]

[0108]

[0109] The hysteresis curves drawn by the method for 7075-T6 friction stir welded aluminum alloy butt joint test pieces under three low-cycle cyclic loading systems are compared with the experimental measured data. Figure 3 , the final recognition model parameters are shown in Table 2:

[0110] Table 2

[0111]

[0112] In order to intuitively reflect the description ability of the constitutive model for elastic modulus degradation and isotropic soft hardening, the elastic modulus degradation surface and isotropic soft hardening evolution surface of the improved Chaboche cyclic constitutive model calibrated by the hysteresis curve of the 6061-T6 friction stir welded aluminum alloy butt joint specimen are plotted according to Table 1, as shown in Figure 1. Figure 8 shown.

[0113] In order to intuitively reflect the asymmetric tension and compression response that can be achieved by the improved Chaboche cycle constitutive model, the compression domain parameters in Table 1 are b 压 、a 压 、k 压 、r 压 、σ| 0,压 , C 1,压 , C 2,压 , C 3,压 , γ 1,压 , γ 2,压 , γ 3,压 When taking the stretch domain parameter of 0 times, 1 / 4 times, 1 / 2 times, 3 / 4 times, 1 times and 1.5 times, use Figure 6 The hysteresis curve is drawn for the loading system 3 as shown in the figure. Figure 9 shown.

[0114] In summary:

[0115] This embodiment adopts experimental design: multi-condition low-cycle cyclic loading is performed on 6061-T6 and 7075-T6 friction stir welded joints, and hysteresis curve data is collected.

[0116] Model Validation:

[0117] Figure 2 It shows that the simulation and experimental curves of 6061-T6 joints under symmetric parameters are highly consistent, verifying the model's ability to characterize elastic modulus degradation and isotropic soft hardening.

[0118] Figure 3The differential tensile and compressive responses of the 7075-T6 joint under asymmetric parameters are shown, demonstrating the advantage of the model in handling complex asymmetries.

[0119] Parameter impact analysis: Figure 9 The effect of compression domain parameter scaling on the hysteresis curve shape is demonstrated, providing an intuitive basis for engineering parameter adjustment.

[0120] 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. An improved Chaboche model suitable for friction stir welding, characterized in that: The improved Chaboche model discriminates the tensile and compressive responses by the difference between the elastic test stress and the total back stress; introduces equivalent plastic strain and peak residual strain to characterize the elastic modulus degradation and isotropic soft hardening behavior; characterizes the kinematic hardening by superposing multiple independent nonlinear components; and calibrates the elastic modulus degradation, isotropic soft hardening, and kinematic hardening parameters in the tensile and compressive domains, respectively, to achieve optional asymmetric modeling of the tensile and compressive responses.

2. The improved Chaboche model suitable for friction stir welding according to claim 1, characterized in that The elastic stiffness matrix of the improved Chaboche model is: Where C is the elastic stiffness matrix; λ is the first Lamé parameter; G is the shear modulus; v is the Poisson's ratio; E n is the elastic modulus at the current moment; E0 is the initial elastic modulus; E sat is the saturation value of elastic modulus degradation; ω and μ are parameters that control the degradation rate of elastic modulus; is the equivalent plastic strain; ε p,m is the peak residual strain; ε is the total strain; σ is the Von Mises stress.

3. The improved Chaboche model suitable for friction stir welding according to claim 1, characterized in that The yield criterion and hardening criterion of the improved Chaboche model are: Where f is the yield function; σ e is the equivalent stress; σ|0 is the initial yield stress; S is the deviatoric stress tensor; α is the back stress tensor; R is the isotropic soft hardening component; α i is the i-th back stress component; N is the number of back stress groups. By increasing the N value, the kinematic hardening accuracy can be improved; C i and γ i is the kinematic hardening parameter; Q ∞ and D ∞ are the hardening saturation value and softening saturation value respectively; b and a are the isotropic hardening rate and softening rate respectively; k and r are the material parameters that control the soft hardening saturation value respectively; is the equivalent plastic strain increment.

4. The improved Chaboche mold suitable for friction stir welding according to claim 1, characterized in that The flow criterion of the modified Chaboche model is: Among them, dε p is the plastic strain increment tensor; dη is the plastic multiplier; σ′ is the stress tensor.

5. The improved Chaboche mold suitable for friction stir welding according to claim 1, characterized in that The tensile and compressive response criterion of the improved Chaboche model is: Among them, σ trial is the current elastic test stress; α is the total back stress.

6. The improved Chaboche mold suitable for friction stir welding according to claim 1, characterized in that The improved Chaboche model adopts a tension-compression dual-domain definition method for the model parameter system, with a total number of parameters of 22+4N, where N is the number of back stress groups; the model parameters are specifically composed as follows: Tensile domain parameters (11+2N): E 0,拉 、E sat,拉 、ω 拉 、μ 拉 、 b 拉 、a 拉 、k 拉 、r 拉 、σ| 0,拉 and N Group C i,拉 and γ i,拉 (i=1,2,3…N); compression domain parameter (11+2N): E 0,压 、E sat,压 、ω 压 、μ 压 、 b 压 、a 压 、k 压 、r 压 、σ| 0,压 and N Group C i,压 and γ i,压 (i=1,2,3…N).

7. The improved Chaboche mold suitable for friction stir welding according to claim 6, characterized in that For materials with symmetrical characteristics of tension and compression response, with back stress as the symmetry center, the improved Chaboche model is simplified to be defined using only the tension domain parameters, and the compression domain parameters are set to be the same as the tension domain parameters, i.e., E 0,拉 =E 0,压 、E sat,拉 =E sat,压 、ω 拉 =ω 压 、μ 拉 =μ 压 、 b 拉 =b 压 、a 拉 =a 压 、k 拉 =k 压 、r 拉 =r 压 、σ| 0,拉 =σ| 0,压 and C i,拉 =C i,压 and γ i,拉 =γ i,压 (i=1,2,3…N).

8. The improved Chaboche mold suitable for friction stir welding according to claim 6, characterized in that For materials that undergo compressive buckling and tension-compression asymmetry, the improved Chaboche model independently defines the tension domain and compression domain parameter groups and establishes a tension-compression dual-domain constitutive relationship to achieve differentiated characterization of compression and tension behaviors.

9. A parameter identification method for an improved Chaboche model suitable for friction stir welding, characterized in that: The steps include: S1: Low-cycle loading tests were performed on friction stir welded aluminum alloy butt joint specimens under various loading conditions to collect complete hysteresis curve data. S2: Based on the equivalent plastic strain, peak residual strain, elastic test stress, and total back stress, an improved Chaboche cyclic constitutive model with elastic modulus degradation, kinematic hardening, isotropic soft hardening, and optional asymmetric tensile and compressive response characteristics is constructed, and the model parameter set that needs to be identified is determined accordingly; S3: Based on the experimentally obtained hysteresis curve data, the improved Chaboche model is inverted using the sparrow search algorithm to minimize the deviation between the model predicted stress and the experimental stress, and finally the optimal model parameter solution set is obtained; its fitness function is: Among them, σ opt Predict stress for the model; σ exp is the stress measured in the test, K is the total number of measurement points of all test pieces or the total number of data points after data noise reduction processing; During the global optimization process, the explorer position is updated as follows: Among them, X i,j is the position of the i-th sparrow in the j-th dimension; n is the current iteration number; κ max is the maximum number of iterations; α s is a random number between 0 and 1 and satisfies α s ≠0; Q is a random number that follows a normal distribution; L is a row vector containing d elements 1; W T and S T They are warning value and safety value respectively; During the global optimization process, the joiner position is updated as follows: Among them, X p is the optimal position of the current explorer; X W is the current global worst position; A + is a row vector containing d elements 1 or -1, and satisfies A + =A T (AA T ) -1 ; During the global optimization process, the position of the sentinel is updated as follows: Among them, X b is the current global optimal position; β and η are random numbers; f i 、f g and f w are the fitness values ​​of the current individual, the current global optimal solution, and the current global worst solution respectively; Ψ is a non-zero decimal.

10. The parameter identification method of the improved Chaboche model suitable for friction stir welding according to claim 9, characterized in that: To improve recognition efficiency and stability, the parameter value range of the improved Chaboche model is determined by trial and error. The improved Chaboche model adopts Latin hypercube sampling and initializes the population in a multidimensional parameter space.

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