Method for determining parameters of crystal plasticity constitutive model of multi-component materials in welded joints

Abstract

The present invention relates to the technical field of metal material processing engineering, and in particular to a method for determining parameters of a crystal plastic constitutive model of a multi-component material of a welded joint, comprising the following steps: S1: determining the material parameters of the base material of the crystal plastic constitutive model based on a low-cycle fatigue test of the base material; S2: determining the material parameters of the welding material of the crystal plastic constitutive model based on a low-cycle fatigue test of the welding material; S3: determining the material parameters of the heat-affected zone of the crystal plastic constitutive model based on a low-cycle fatigue test of the welding joint. The present invention extracts information of an ABAQUS finite element simulation INP file through a compiled PYTHON script, generates a corresponding MATLAB optimization program, reads the calculation results of the ABAQUS finite element, and automatically calculates the difference between the simulation results and the test results, and automatically adjusts the material parameters of the crystal plastic finite element through the optimization program, so that the ABAQUS simulation results are consistent with the test results, thereby obtaining accurate crystal plastic material parameters.

Description

Technical Field

[0001] The invention relates to the technical field of metal material processing engineering, and in particular to a method for determining parameters of a crystal plastic constitutive model of a multi-component material of a welded joint. Background Art

[0002] Welding is a commonly used connection method in engineering, and the performance of welded joints directly affects the reliability, strength and durability of the entire structure. However, the microstructure of welded joints is complex, containing many defects and various crystal structures, so it is challenging to accurately simulate and predict their mechanical properties. In traditional research methods, experiments and numerical simulations are commonly used. Experimental methods usually require a large amount of samples and time, and are affected by equipment limitations and test conditions. It is difficult to fully consider the microstructure and mechanical behavior of welded joints. Although numerical simulation methods can simulate the micromechanical properties of welded joints, they often need to rely on empirical models when determining material parameters, and the accuracy and reliability of the results are limited.

[0003] In contrast, the crystal plasticity method has significant advantages. This method is based on crystal plasticity theory and can more accurately describe the micromechanical behavior of welded joints. By simulating the deformation and dislocation movement of crystals under stress, the plastic behavior, deformation behavior and damage morphology of welded joints can be accurately predicted, thereby determining their mechanical properties. Compared with traditional methods, the crystal plasticity method has higher accuracy and reliability, and can better guide the design and optimization of welded joints in engineering practice. Therefore, the method for determining the material parameters of complex microstructures of welded joints based on the crystal plasticity method has significant engineering application value. The application of this method will promote the development of welding technology and provide more reliable and efficient solutions for engineering practice. Summary of the invention

[0004] Based on the above objectives, the present invention provides a method for determining parameters of a crystal plastic constitutive model of a multi-component material of a welded joint.

[0005] The method for determining parameters of a crystal plastic constitutive model of a multi-component material of a welded joint comprises the following steps:

[0006] S1: Determine the parent material parameters of the crystal plasticity constitutive model based on the low cycle fatigue test of the parent material;

[0007] S2: Determine the material parameters of the crystal plasticity constitutive model welding material based on the low cycle fatigue test of welding material;

[0008] S3: Determine the material parameters of the heat-affected zone of the crystal plasticity constitutive model based on low-cycle fatigue tests of welded joints.

[0009] Furthermore, the S1 specifically includes:

[0010] S11: Use the welded joint base metal to make standard test specimens, carry out low cycle fatigue tests, and obtain the stress-strain curve of the base metal;

[0011] S12: Take metallographic photos of the base material of the welded joint, measure the average grain size of the base material grains, and establish a crystal plasticity finite element model of the base material;

[0012] S13: Randomly assign material parameter groups to the parent material part of the crystal plastic finite element, apply the same mechanical load and boundary conditions as the parent material test, and perform low-cycle fatigue simulation;

[0013] S14: extracting stress and strain data of all units of the parent material finite element model respectively, summing the stress and strain data of all units of the parent material finite element model respectively, dividing the summed stress and strain data of the parent material finite element model by the area of ​​the parent material finite element model, and obtaining a stress-strain curve diagram of the entire parent material finite element model;

[0014] S15: Compare the difference between the stress-strain of the simulated parent material finite element model and the stress-strain of the parent material test, and repeat S13 and S14 until the stress-strain curve of the simulated parent material finite element model is consistent with the stress-strain curve of the parent material test.

[0015] Furthermore, the S2 specifically includes:

[0016] S21: Use welding consumables to make standard test specimens, carry out low cycle fatigue tests, and obtain stress-strain curves of welding consumables;

[0017] S22: Take metallographic photos of the welding materials of the welded joint, measure the average grain size of the welding materials, and establish a crystal plasticity finite element model of the welding materials;

[0018] S23: Randomly assign material parameter groups to the crystal plastic finite element welding material part, apply the same mechanical load and boundary conditions as the welding material test, and perform low-cycle fatigue simulation;

[0019] S24: extracting stress and strain data of all units of the welding material finite element model respectively, summing the stress and strain data of all units of the welding material finite element model respectively, dividing the summed stress and strain data of the welding material finite element model by the area of ​​the welding material finite element model, and obtaining a stress-strain curve diagram of the entire welding material finite element model;

[0020] S25: Compare the difference between the stress-strain of the simulated welding material finite element model and the stress-strain of the welding material test, and repeat S23 and S24 until the stress-strain curve of the simulated welding material finite element model is consistent with the stress-strain curve of the welding material test.

[0021] Furthermore, the S3 specifically includes:

[0022] S31: Use the welded joint to make a standard test specimen, carry out a low cycle fatigue test, and obtain the stress-strain curve of the welded joint;

[0023] S32: Take metallographic photos of the welded joint, measure the average grain size of the grains in the heat-affected zone, and establish a crystal plasticity finite element model of the welded joint based on the microscopic characteristics of the base material, welding material and heat-affected zone;

[0024] S33: Randomly assign material parameter groups to the heat-affected zone of the crystal plastic finite element, apply the same mechanical loads and boundary conditions as the weld joint test, and generate an INP file;

[0025] S34: Read the INP file through the compiled PYTHON script, and generate the corresponding material parameter optimization program in MATLAB to automatically debug the heat affected zone parameter group and perform low cycle fatigue simulation;

[0026] S35: The MATLAB optimization program reads the simulated stress-strain data, calculates the error d between the simulated value and the test value, and repeats S33, S34, and S35 until d is less than the preset error.

[0027] Furthermore, the crystal plasticity finite element model of the base material, the crystal plasticity finite element model of the welding material and the crystal plasticity finite element model of the welded joint are all established by ABAQUS software, and the INP file is generated by ABAQUS software.

[0028] Furthermore, the calculation formula of the parameter optimization program is:

[0029]

[0030] Among them, fmincon is the optimization function to solve the minimum value of d, d is the error between the experimental stress-strain value and the simulated stress-strain value, x n is n parameter groups to be optimized [x1,2,…, n ], lb i andub i The parameters x are i The lower and upper limits of .

[0031] Furthermore, the constraint conditions for parameter optimization include equality constraints and inequality constraints, wherein;

[0032] The calculation formula of the equality constraint is: Aeq*x n =beq;

[0033] The calculation formula of the inequality constraint condition is: A*x n <=b.

[0034] Further, when the inequality constraint does not exist, A and b are set to A=[] and b=[], and when the equality constraint does not exist, Aeq and beq are set to Aeq=[] and beq=[].

[0035] Furthermore, the calculation formula of the error d is:

[0036]

[0037] Among them, T and is the temperature and loading strain rate of the low cycle fatigue test, and σ i are respectively i The simulated stress value at and the stress value measured by the experiment.

[0038] Furthermore, the preset error is 10 -5 .

[0039] Beneficial effects of the present invention:

[0040] The present invention extracts information of ABAQUS finite element simulation INP file through compiled PYTHON script, generates corresponding MATLAB optimization program, reads calculation results of ABAQUS finite element, and automatically calculates the difference between simulation results and test results. Material parameters of crystal plastic finite element are automatically adjusted through the optimization program to make ABAQUS simulation results consistent with test results, thereby obtaining accurate crystal plastic material parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of a determination method flow chart of an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of the average grain size of the parent material grains according to an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of a crystal plasticity finite element model of a base material according to an embodiment of the present invention;

[0045] Figure 4 Schematic diagram of a crystal plastic finite element model of a welded joint according to an embodiment of the present invention;

[0046] Figure 5 Schematic diagram of stress-strain curve of welding joint test and simulation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0048] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0049] like Figure 1-Figure 5 As shown, the method for determining parameters of the crystal plastic constitutive model of multi-component materials of welded joints includes the following steps:

[0050] S1. Determine the material parameters of the base material of the crystal plasticity constitutive model based on the base material low cycle fatigue test. The specific steps are as follows:

[0051] S11. Use the welded joint base metal to make a standard test specimen, conduct a low cycle fatigue test, and obtain the stress-strain curve of the base metal;

[0052] S12. Take metallographic photos of the base metal of the welded joint and measure the average grain size of the base metal grains, such as Figure 2 As shown, the crystal plasticity finite element model of the parent material is established in ABAQUS software with this feature, as shown in Figure 3 As shown;

[0053] S13, randomly assign material parameter groups to the parent material part of the crystal plastic finite element, apply the same mechanical load and boundary conditions as the parent material test and perform low cycle fatigue simulation, such as Figure 3 As shown;

[0054] S14, extracting the stress and strain data of all units of the parent material finite element model respectively and summing them. Dividing the summed stress and strain by the area of ​​the finite element model to obtain a stress-strain curve diagram of the entire model;

[0055] S15, comparing the difference between the simulated stress-strain and the experimental stress-strain, by repeating steps S13 and S14 until the simulated stress-strain curve matches the experimental stress-strain curve.

[0056] S2. Determine the material parameters of the crystal plasticity constitutive model welding material based on the welding material low cycle fatigue test. The specific steps are as follows:

[0057] S21. Use welding materials of welding joints to make standard test specimens, carry out low cycle fatigue tests, and obtain stress-strain curves of welding materials;

[0058] S22. Take metallographic photos of the welding materials of the welding joints and measure the average grain size of the welding materials. Based on this feature, a crystal plasticity finite element model of the welding materials is established in ABAQUS software;

[0059] S23, randomly assigning a material parameter group to the crystal plastic finite element welding material part, applying the same mechanical load and boundary conditions as the welding material test and performing low cycle fatigue simulation;

[0060] S24, extracting the stress and strain data of all units of the welding material finite element model respectively and summing them. Dividing the summed stress and strain by the area of ​​the finite element model to obtain a stress-strain curve diagram of the entire model;

[0061] S25, comparing the difference between the simulated stress-strain and the experimental stress-strain, by repeating steps S23 and S24 until the simulated stress-strain curve matches the experimental stress-strain curve.

[0062] S3. Determine the material parameters of the heat-affected zone of the crystal plasticity constitutive model based on the low-cycle fatigue test of the welded joint. The specific steps are as follows:

[0063] S31. Use the welded joint to make a standard test specimen, carry out a low cycle fatigue test, and obtain a stress-strain curve of the welded joint;

[0064] S32. Take metallographic photos of the welded joint, measure the average grain size of the grains in the heat-affected zone, and establish a crystal plasticity finite element model of the welded joint in ABAQUS software based on the microscopic characteristics of the base material, welding material and heat-affected zone, such as Figure 4 As shown;

[0065] S33, randomly assign a material parameter group to the heat-affected zone of the crystal plastic finite element (the material parameters of the parent material and the welding material have been determined by S1 and S2), apply the same mechanical load and boundary conditions as the weld joint test, and generate an INP file for ABAQUS;

[0066] S34, reading the INP file through the compiled PYTHON script, and generating a corresponding material parameter optimization program in MATLAB to automatically debug the heat affected zone parameter group, and perform low cycle fatigue simulation;

[0067] S35, MATLAB optimization program reads the simulated stress-strain data, calculates the error d between the simulated value and the test value, and repeats steps S33, S34, and S35 until d is less than the allowable error 10 -5 ;

[0068] MATLAB parameter optimization program in step S34;

[0069] The parameter optimizer function is:

[0070]

[0071] In the above formula, fmincon is the optimization function for solving the minimum value of d, d is the error between the experimental stress-strain value and the simulated stress-strain value, x n is n parameter groups to be optimized [x1,2,…, n ], the constraint is Aeq*x n =beq ​​and A*x n <=b. If no inequality linear constraints exist, set A=[], b=[]. lb i andub i The parameters x are i The lower and upper limits of i <=x i <=ub i , if no equality constraint exists, let Aeq = [], beq = [];

[0072] The calculation formula of error d is:

[0073]

[0074] In the above formula, T and is the temperature and loading strain rate of the low cycle fatigue test, and σ i are respectively i The simulated stress value at and the stress value measured by the experiment.

[0075] The above method was used to finally determine the parameters of the base material, welding material and crystal plastic material of the heat affected zone of the welded joint. Figure 5A comparison diagram of the finite element simulation stress-strain curve and the experimental stress-strain curve of the welded joint after the parameters are determined is given. It can be seen that this method can accurately obtain the crystal plastic material parameters of each microscopic component of the welded joint, thereby providing a strong and accurate theoretical basis for the micromechanical analysis of the welded joint.

[0076] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity.

[0077] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining parameters of a crystal plastic constitutive model of a multi-component material of a welded joint, characterized in that: The following steps are involved: S1: Determine the parent material parameters of the crystal plasticity constitutive model based on the low cycle fatigue test of the parent material; S2: Determine the material parameters of the crystal plasticity constitutive model welding material based on the low cycle fatigue test of welding material; S3: Determine the material parameters of the heat-affected zone of the crystal plasticity constitutive model based on low-cycle fatigue tests of welded joints; The S3 specifically includes: S31: Use the welded joint to make a standard test specimen, carry out a low cycle fatigue test, and obtain the stress-strain curve of the welded joint; S32: Take metallographic photos of the welded joint, measure the average grain size of the grains in the heat-affected zone, and establish a crystal plasticity finite element model of the welded joint based on the microscopic characteristics of the base material, welding material and heat-affected zone; S33: Randomly assign material parameter groups to the heat-affected zone of the crystal plastic finite element, apply the same mechanical loads and boundary conditions as the weld joint test, and generate an INP file; S34: Read the INP file through the compiled PYTHON script, and generate the corresponding material parameter optimization program in MATLAB to automatically debug the heat affected zone parameter group and perform low cycle fatigue simulation; S35: The MATLAB optimization program reads the simulated stress-strain data, calculates the error d between the simulated value and the test value, and repeats S33, S34, and S35 until d is less than the preset error.

2. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 1, characterized in that: The S1 specifically includes: S11: Use the welded joint base metal to make standard test specimens, carry out low cycle fatigue tests, and obtain the stress-strain curve of the base metal; S12: Take metallographic photos of the base material of the welded joint, measure the average grain size of the base material grains, and establish a crystal plasticity finite element model of the base material; S13: Randomly assign material parameter groups to the parent material part of the crystal plastic finite element, apply the same mechanical load and boundary conditions as the parent material test, and perform low-cycle fatigue simulation; S14: extracting stress and strain data of all units of the parent material finite element model respectively, summing the stress and strain data of all units of the parent material finite element model respectively, dividing the summed stress and strain data of the parent material finite element model by the area of ​​the parent material finite element model, and obtaining a stress-strain curve diagram of the entire parent material finite element model; S15: Compare the difference between the stress-strain of the simulated parent material finite element model and the stress-strain of the parent material test, and repeat S13 and S14 until the stress-strain curve of the simulated parent material finite element model is consistent with the stress-strain curve of the parent material test.

3. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 2, characterized in that: The S2 specifically includes: S21: Use welding consumables to make standard test specimens, carry out low cycle fatigue tests, and obtain stress-strain curves of welding consumables; S22: Take metallographic photos of the welding materials of the welded joint, measure the average grain size of the welding materials, and establish a crystal plasticity finite element model of the welding materials; S23: Randomly assign material parameter groups to the crystal plastic finite element welding material part, apply the same mechanical load and boundary conditions as the welding material test, and perform low-cycle fatigue simulation; S24: extracting stress and strain data of all units of the welding material finite element model respectively, summing the stress and strain data of all units of the welding material finite element model respectively, dividing the summed stress and strain data of the welding material finite element model by the area of ​​the welding material finite element model, and obtaining a stress-strain curve diagram of the entire welding material finite element model; S25: Compare the difference between the stress-strain of the simulated welding material finite element model and the stress-strain of the welding material test, and repeat S23 and S24 until the stress-strain curve of the simulated welding material finite element model is consistent with the stress-strain curve of the welding material test.

4. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 3, characterized in that: The crystal plasticity finite element model of the base material, the crystal plasticity finite element model of the welding material and the crystal plasticity finite element model of the welded joint are all established by ABAQUS software, and the INP file is generated by ABAQUS software.

5. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 4, characterized in that: The calculation formula of the parameter optimization program is: Among them, fmincon is the optimization function to solve the minimum value of d, d is the error between the simulation value and the test value, x n is n parameter groups to be optimized [x1, x2, …, x n ], lb i andub i The parameters x are i The lower and upper limits of .

6. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 5, characterized in that: The constraint conditions of parameter optimization include equality constraint conditions and inequality constraint conditions, wherein; The calculation formula of the equality constraint is: Aeq*x n =beq; The calculation formula of the inequality constraint condition is: A*x n <=b.

7. The method for determining parameters of the crystal plastic constitutive model of a multi-component material of a welded joint according to claim 6, characterized in that: When the inequality constraint does not exist, A and b are set to A=[] and b=[]. When the equality constraint does not exist, Aeq and beq are set to Aeq=[] and beq=[].

8. The method for determining parameters of the crystal plastic constitutive model of a multi-component material of a welded joint according to claim 7, characterized in that: The calculation formula of the error d is: Among them, T and is the temperature and loading strain rate of the low cycle fatigue test, and σ i are respectively i The simulated stress value at and the stress value measured by the experiment.

9. The method for determining parameters of the crystal plastic constitutive model of a welded joint multi-component material according to claim 8, characterized in that: The preset error is 10 -5 .

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