Dissimilar stainless steel inertia friction welding flash forming and multi-physics field prediction method

Abstract

The invention relates to a dissimilar stainless steel inertia friction welding flash forming and multi-physics field prediction method. The method comprises the following steps that S1, an inertia friction welding model is established; s2, setting material attribute parameters; s3, dividing a grid; s4, setting the action of the clamp; s5, setting boundary conditions; s6, interaction and friction behaviors between the contact surfaces are set; s7, a thermal-force coupling model in the inertial friction welding process is constructed, temperature change data of the feature points are obtained through calculation, and the simulated welding flash morphology is obtained; model parameters are updated according to the temperature change data of the feature points, whether the temperature of the feature points and the simulated flash morphology reach termination conditions or not is judged, if yes, iteration is stopped, a simulation prediction result is obtained, and if not, the temperature change data of the feature points of the ith iteration is read, and i is made to be equal to i + 1. The method is beneficial to efficiently and accurately predicting flash forming and multi-physics fields.

Description

Technical Field

[0001] The invention relates to the technical field of friction welding process simulation, and in particular to a method for flash forming and multi-physical field prediction of inertia friction welding of heterogeneous stainless steel based on numerical simulation. Background Art

[0002] In the prior art, the inertia friction welding process is as follows Figure 1 As shown in the figure, because it is a complex thermal-mechanical coupling dynamic process, welding is generally completed within 3-6 seconds, making it difficult to measure the real-time temperature changes, stress changes, and metal plastic layer flow in different areas of the welding material through experiments. The finite element method can be free from the constraints of experimental conditions, and can study the influence of various physical effects in the welding process based on the simulation process and result data, saving research costs. In addition, in the actual production process, the removal of weld flash increases the molding cost. If the welding flash morphology can be effectively controlled, the cost can be reduced accordingly. To achieve the goal of flash control, it is necessary to have a certain predictive ability for the physical field change process. Therefore, it is very necessary to predict the temperature field, stress field and plastic field of inertia friction welding.

[0003] At present, the simulation of inertia friction welding lacks consideration of heat generation due to plastic deformation, or considers the friction behavior as a single Coulomb friction, or regards the material parameters as constants, resulting in inaccurate simulation results. Therefore, it is of great significance to establish a flash formation and multi-physics field prediction method based on numerical simulation. Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting flash formation and multi-physical fields in inertia friction welding of dissimilar stainless steels, which is conducive to efficiently and accurately predicting flash formation and multi-physical fields.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: a method for flash formation and multi-physical field prediction of inertia friction welding of dissimilar stainless steels, comprising the following steps:

[0006] S1. Establishing inertia friction welding model;

[0007] S2. Set material property parameters;

[0008] S3, grid division;

[0009] S4, setting the fixture action;

[0010] S5. Set boundary conditions;

[0011] S6. Setting the interaction and friction behavior between contact surfaces;

[0012] S7. Construct a thermal-mechanical coupling model of the inertia friction welding process, calculate and obtain the temperature change data of the feature points, and obtain the simulated welding flash morphology; then set the number of iterations i=1, and start the iterative simulation calculation: update the model parameters according to the temperature change data of the feature points, and then determine whether the temperature of the feature points and the simulated flash morphology meet the termination conditions. If so, stop the iteration and obtain the simulation prediction result. Otherwise, read the temperature change data of the feature points of the i-th iteration, and set i=i+1.

[0013] Furthermore, in step S1, considering the complexity of model establishment as well as the calculation efficiency and accuracy, the following assumptions are made for the inertia friction welding model to be established: (1) the welding material is isotropic; (2) the initial temperature of the material is constant and the same as the ambient temperature; (3) the heat-to-work conversion coefficient is constant during friction welding; (4) the physical parameters of the material change with temperature; and (5) the yield strength of the material obeys the Mises yield criterion.

[0014] Furthermore, based on the established assumptions, a two-dimensional axisymmetric geometric model of inertia friction welding is established by using AutoCAD software. The geometric model includes: a rotating end fixture, a moving end fixture, a rod A and a rod B.

[0015] Furthermore, in step S2, the established geometric model is imported into the pre-processing module of the DEFORM simulation software, the fixture is set to a rigid material that will not deform, and the rod A and the rod B are set to a plastic material that can undergo torsional deformation;

[0016] In JMAtpro software, simulate the element content of the input material to obtain the physical parameters that change with temperature; assign the material relevant physical parameters that change with temperature;

[0017] Considering that the welding material will be severely deformed during inertia friction welding, the hyperbolic sine constitutive equation is used to describe the relationship between the flow stress, strain and temperature of rod A and rod B:

[0018]

[0019] Where A, α, and n are set constants, ΔH is the thermal activation energy of thermal deformation, R = 8.314 J / (mol·K) is the gas constant, T is the temperature during welding, ε is the strain, and σ is the flow stress.

[0020] Further, in step S3, the meshing is performed using the mesh window method. Considering the influence of temperature on the welding process, the temperature distribution weight of the mesh window is set to 0.2, and the rest is the window weight; the mesh module of the DEFORM simulation software is entered, and the four-node tetrahedron unit is selected to perform local meshing of the imported geometric model; the mesh re-division condition is set to a maximum growth step of 50 steps, and the distorted units are re-meshed to obtain the final mesh model; the mesh windows away from the welding surface are: mesh dense area, mesh dense area, mesh sparse area; the thermal-mechanical coupling field of the material at the weld changes dramatically, and the mesh size of the mesh window at the weld is set to the mesh dense area. Considering the calculation accuracy and efficiency, the mesh size at the weld is set to 0.01; the mesh size of the mesh dense area close to the weld is set to 0.1, and the mesh size of the mesh sparse area at the parent material is set to 1;

[0021] The DEFORM subroutine is used to re-grid the model to eliminate distortion, and the mapping technology is used to assign the data contained in each node unit before re-gridding to the new grid node unit accordingly.

[0022] Furthermore, in step S4, the tool movement module of the DEFORM simulation software is entered to set the rotation speed of the rotating end fixture and the welding pressure of the mobile end fixture respectively; the rotation speed of the rotating end fixture and the pressure of the mobile end fixture change with time. To ensure the accuracy of the simulation parameters, the real parameters under the corresponding welding conditions are obtained through the inertial friction welding monitoring platform.

[0023] Furthermore, in step S5, the Boundary conditions module of the DEFORM simulation software is entered to set the displacement conditions and thermal boundary conditions of the finite element model:

[0024] The thermal boundary conditions are calculated by the following formula:

[0025]

[0026] The heat generated by friction and plastic deformation is conducted into the workpiece; the heat loss includes convection heat transfer between the workpiece surface and the environment and heat conduction between the workpiece and the fixture; the effect of thermal radiation on heat loss is negligible; where h c is the heat convection coefficient, λ (w,c) is the thermal conductivity between the workpiece and the fixture, T w , T a and T c are the temperatures of the workpiece, the surrounding environment and the fixture, respectively, fr The frictional heat, q pl Generates heat for plastic deformation;

[0027] The boundary conditions of the rotating end fixture are composed of three displacement constraints u (x,0,0) =0,u (0,y,0) =0,u (0,0,z) = 0 and two rotation constraints θ (x，0，0) =0,θ (0,0,z) = 0; the boundary conditions of the mobile end fixture are composed of two displacement constraints u (x,0,0) =0,u (0,0,z) = 0 and three rotation constraints θ (x，0，0) =0,θ (0,y,0) =0,θ (0,0,z) =0 composition.

[0028] Further, in step S6, the relationship between objects is set in DEFORM, including the master-slave relationship between geometric models and the friction type when the bar A and the bar B are in inertia friction welding contact, so as to ensure that the simulation process can be completed smoothly and effectively;

[0029] In the DEFORM master-slave relationship setting, three pairs of contacts are set: rotating end fixture-rod A, rod A-rod B, rod B-moving end fixture; among them, the rotating end fixture and the moving end fixture are set as the main components; the friction coefficient of the rotating end fixture-rod A and rod B-moving end fixture is set to 1; rod A-rod B is set to face-to-face contact, and the friction coefficient is set to Coulomb friction and shear friction;

[0030] The friction behavior will change during the welding process, which can be equivalently divided into two stages: Coulomb friction model and shear friction model. In the initial friction stage, the welding interface temperature is low, the workpiece does not undergo plastic deformation, and the friction between the two workpieces is mainly dry friction, so the friction type is expressed by the Coulomb friction model. The corresponding stress formula is:

[0031]

[0032] In the formula, τ a is the friction stress, σ a is the normal stress, V a is the relative friction speed, μ is the friction coefficient;

[0033] In the stable friction stage, the friction between the two workpieces generates a large amount of heat, which causes severe plastic deformation and plastic flow at the end face joint. Therefore, the friction type is represented by the shear friction model, and the corresponding stress formula is:

[0034]

[0035] In the formula, τ f is the friction stress, m is the shear friction coefficient, ranging from 0 to 1, v s is the relative linear velocity, and k is the shear yield strength of the metal material.

[0036] Furthermore, in step S7, in the simulation control module of the DEFORM simulation software, the simulation termination conditions and the time sub-step increment are set, and then the simulation calculation is performed, and the mesh distortion is controlled by the re-gridding technology; the flash morphology, temperature field, stress-strain field, interface temperature change and axial shortening change after welding are analyzed.

[0037] Furthermore, after completing the simulation calculation, an inertia friction welding test is carried out, and the temperature at the characteristic point is measured using a thermocouple for experimental verification.

[0038] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a method for the flash formation and multi-physical field prediction of inertial friction welding of heterogeneous stainless steel based on numerical simulation, which establishes a complete thermomechanical coupling model of inertial friction welding based on DEFORM, and can simultaneously calculate the friction welding temperature, fluid, stress and strain when applied, thereby realizing the multi-physical field direct coupling numerical simulation calculation of the friction welding process. When the present invention is used for inertial friction welding process simulation, the simulation calculation results can be obtained efficiently and accurately, and the consistency with the actual friction welding process can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of inertia friction welding in the prior art;

[0040] Figure 2 A flowchart of a method implementation of an embodiment of the present invention;

[0041] Figure 3 The finite element model of inertia friction welding in the embodiment of the present invention;

[0042] Figure 4 : are material parameter curves of two materials in the embodiment of the present invention; wherein (a) is a thermal conductivity and Young's modulus curve of 2205 stainless steel, and (b) is a thermal conductivity and Young's modulus curve of 316L stainless steel;

[0043] Figure 5 is the action curve of the displacement end fixture and the rotation end fixture in the embodiment of the present invention;

[0044] Figure 6 A comparison curve diagram of the simulated and measured data of the temperature of the workpiece surface measuring point during the welding process in an embodiment of the present invention;

[0045] Figure 7 It is a comparison diagram of flash formation after welding and flash formation after testing in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0048] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0049] This embodiment provides a method for the flash formation and multi-physics field prediction of inertia friction welding of heterogeneous stainless steel based on numerical simulation, using friction and plastic deformation heat flux as the model heat source, using the hyperbolic sine constitutive equation model to describe the plastic deformation law of the material, and introducing the friction coefficient equation that varies with temperature to describe the coupling effect of temperature and friction. The inertia friction welding of 2205 / 316L stainless steel is used as an example for explanation. Figure 2 Shown is the implementation flow chart of this method, and the specific implementation steps are as follows.

[0050] S1. Establishing inertia friction welding model

[0051] First, considering the complexity of model establishment as well as the calculation efficiency and accuracy, the following assumptions are made for the inertia friction welding model to be established:

[0052] (1) The welding material is isotropic; (2) The initial temperature of the material is constant and the same as the ambient temperature (20°C); (3) The heat-to-work conversion coefficient is constant during friction welding; (4) The physical parameters of the material (specific heat, thermal conductivity, Young's modulus) change with temperature; (5) The yield strength of the material obeys the Mises yield criterion.

[0053] Then, based on the established assumptions, a two-dimensional axisymmetric geometric model of inertia friction welding was established using AutoCAD software, including: a rotating end fixture, a moving end fixture, rod A, and rod B.

[0054] Since the welding material is axially symmetrical, and the changes in the temperature field, stress field, and plastic field that are the focus of attention are also axially symmetrically distributed, a structure of half the welding rod is sufficient. In this embodiment, the geometric model includes: a rotating end fixture, a moving end fixture, rod 2205, and rod 316L. According to the actual measured material dimensions, the geometric models of rods 2205 and rods 316L are rectangular, 120 mm long and 17.5 mm wide. The dimensions of the rotating end fixture and the moving end fixture have no effect on the simulation process, and the specific dimensions can be unrestricted. The finite element model is as follows Figure 3 shown.

[0055] S2. Set material property parameters

[0056] The established geometric model is imported into the pre-processing module of the DEFORM simulation software, the fixture is set to a rigid material that will not deform, and the rod 2205 and the rod 316L are set to plastic materials that can undergo torsional deformation.

[0057] The element content of the input material is simulated in the JMAtpro software to obtain the physical parameters that change with temperature. The material is given the relevant physical parameters that change with temperature as described in step 1. In this embodiment, the material parameter attribute parameters are as follows Figure 4 shown.

[0058] Considering that the welding material will be severely deformed during inertia friction welding, the hyperbolic sine constitutive equation is used to describe the relationship between the flow stress, strain and temperature of the rod 2205 and the rod 316L:

[0059]

[0060] Where A, α, and n are set constants, ΔH is the thermal activation energy of thermal deformation, R = 8.314 J / (mol·K) is the gas constant, T is the temperature during welding, ε is the strain, and σ is the flow stress.

[0061] S3. Grid division

[0062] The grid division adopts the grid window method. Considering the influence of temperature on the welding process, the temperature distribution weight of the grid window is set to 0.2, and the rest is the window weight.

[0063] Enter the mesh module of the DEFORM simulation software, select the four-node tetrahedron unit to perform local mesh division on the imported geometric model. Set the mesh re-division condition to a maximum growth step of 50 steps, and re-mesh the distorted units to obtain the final mesh model. The mesh windows away from the welding surface are: dense mesh area, dense mesh area, and sparse mesh area. The thermal-mechanical coupling field of the material at the weld changes dramatically, and the mesh size of the mesh window at the weld needs to be set relatively small, so it is set to a dense mesh area. Considering the calculation accuracy and efficiency, the mesh size at the weld is set to 0.01. The mesh size of the dense mesh area near the weld is set to 0.1, and the mesh size of the sparse mesh area at the parent material is set to 1.

[0064] The DEFORM subroutine is used to re-grid the model to eliminate distortion, and the mapping technology is used to assign the data contained in each node unit before re-gridding to the new grid node unit accordingly.

[0065] S4. Set the fixture action

[0066] Enter the tool movement module of the DEFORM simulation software and set the rotation speed of the rotating fixture and the welding pressure of the mobile fixture. The rotation speed of the rotating fixture and the pressure of the mobile fixture change with time. To ensure the accuracy of the simulation parameters, the real parameters under the corresponding welding conditions are obtained through the inertial friction welding monitoring platform, such as Figure 5 shown.

[0067] S5. Set boundary conditions

[0068] Enter the Boundary conditions module of the DEFORM simulation software and set the displacement conditions and thermal boundary conditions of the finite element model:

[0069] The thermal boundary conditions are calculated by the following formula:

[0070]

[0071] The heat generated by friction and plastic deformation is conducted into the workpiece. Heat loss includes convection heat transfer between the workpiece surface and the environment and heat conduction between the workpiece and the fixture. The effect of thermal radiation on heat loss is negligible. c is the heat convection coefficient, λ (w,c) is the thermal conductivity between the workpiece and the fixture, T w 、T a and T c are the temperatures of the workpiece, the surrounding environment and the fixture, respectively, fr The frictional heat, q pl Generates heat for plastic deformation.

[0072] The boundary conditions of the rotating end fixture are composed of three displacement constraints u (x,0,0) =0,u (0,y,0) =0,u (0,0,z) = 0 and two rotation constraints θ (x，0，0) =0,θ (0,0,z) = 0; the boundary conditions of the mobile end fixture are composed of two displacement constraints u (x,0,0) =0,u (0,0,z) = 0 and three rotation constraints θ (x，0，0) =0,θ (0,y,0) =0,θ (0,0,z) =0 composition.

[0073] S6. Set the interaction and friction behavior between contact surfaces

[0074] The relationships between objects are set in DEFORM, including the master-slave relationship between geometric models and the friction type when the bar 2205 and the bar 316L are in inertia friction welding contact, to ensure that the simulation process can be completed smoothly and effectively.

[0075] In the DEFORM master-slave relationship setting, three pairs of contacts are set: rotating end fixture-rod 2205, rod 2205-rod 316L, and rod 316L-moving end fixture. Among them, the rotating end fixture and the moving end fixture are set as the main components. The rotating end fixture-rod 2205 and rod 316L-moving end fixture are set as fixed connections, and the friction coefficient is set to 1. Rod 2205-rod 316L is set to face-to-face contact, and the friction coefficient is set to Coulomb friction and shear friction.

[0076] The friction behavior will change during the welding process, which can be equivalently divided into two stages: the Coulomb friction model and the shear friction model. In the initial friction stage, the welding interface temperature is low, the workpiece does not undergo plastic deformation, and the friction between the two workpieces is mainly dry friction, so the friction type is represented by the Coulomb friction model; the corresponding stress formula is:

[0077]

[0078] In the formula, τ a is the friction stress, σ a is the normal stress, V a is the relative friction speed, μ is the friction coefficient.

[0079] In the stable friction stage, the friction between the two workpieces generates a large amount of heat, which causes severe plastic deformation and plastic flow at the end face joint. Therefore, the friction type is represented by the shear friction model, and the corresponding stress formula is:

[0080]

[0081] In the formula, τ fis the friction stress, m is the shear friction coefficient, the value range is 0 to 1, here it is 0.3, v s is the relative linear velocity, and k is the shear yield strength of the metal material.

[0082] The energy of inertia friction welding mainly comes from the high-speed rotating flywheel. Under the action of inertia, the two workpieces undergo intense friction, converting the stored kinetic energy into the heat required during the welding process. The heat flow at the welding interface can be expressed as

[0083] q(r,t)=2π·r·μ·p(r,t)·ω(t)·η

[0084] Where q(r, t) is the heat flux, r is the calculation node radius, μ is the friction coefficient, p(r, t) is the friction pressure, ω(t) is the angular velocity, and η is the conversion efficiency.

[0085] S7. Construct a thermal-mechanical coupling model of the inertia friction welding process, calculate and obtain the temperature change data of the feature points, and obtain the simulated welding flash morphology; then set the number of iterations i=1, and start the iterative simulation calculation: update the model parameters according to the temperature change data of the feature points, and then determine whether the temperature of the feature points and the simulated flash morphology meet the termination conditions. If so, stop the iteration and obtain the simulation prediction result. Otherwise, read the temperature change data of the feature points of the i-th iteration, and set i=i+1.

[0086] In the simulation control module of the DEFORM simulation software, the simulation termination condition is set to the welding time measured by the friction welding monitoring platform, and the time sub-step increment is 0.01 step / second. Then the simulation calculation is carried out, and the grid distortion is controlled by the re-gridding technology. The flash morphology, temperature field, stress-strain field, interface temperature change and axial shortening change after welding are analyzed.

[0087] After completing the simulation calculation, an inertia friction welding test is carried out to compare the flash morphology. The temperature at the characteristic point is measured using a thermocouple. The friction coefficient and other model parameters are adjusted by the difference between the simulated temperature and the measured temperature, so that the experimental temperature and the simulated temperature are within 10%. Figure 6 and Figure 7 shown.

[0088] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels, characterized in that: The following steps are involved: S1. Establish inertia friction welding model; S2. Set material property parameters; S3, grid division; S4, setting the fixture action; S5. Set boundary conditions; S6. Setting the interaction and friction behavior between contact surfaces; S7. Construct a thermal-mechanical coupling model of the inertia friction welding process, calculate and obtain the temperature change data of the feature points, and obtain the simulated welding flash morphology; then set the number of iterations i=1, and start the iterative simulation calculation: update the model parameters according to the temperature change data of the feature points, and then determine whether the temperature of the feature points and the simulated flash morphology meet the termination conditions. If so, stop the iteration and obtain the simulation prediction result. Otherwise, read the temperature change data of the feature points of the i-th iteration, and set i=i+1.

2. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steel according to claim 1, characterized in that: In step S1, considering the complexity of model establishment as well as the calculation efficiency and accuracy, the following assumptions are made for the inertia friction welding model to be established: (1) the welding material is isotropic; (2) the initial temperature of the material is constant and the same as the ambient temperature; (3) the heat-to-work conversion coefficient is constant during friction welding; (4) the physical parameters of the material change with temperature; and (5) the yield strength of the material obeys the Mises yield criterion.

3. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 2, characterized in that: Based on the established assumptions, a two-dimensional axisymmetric geometric model of inertia friction welding is established by using AutoCAD software. The geometric model includes: a rotating end fixture, a moving end fixture, a rod A and a rod B.

4. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steel according to claim 3, characterized in that: In step S2, the established geometric model is imported into the pre-processing module of the DEFORM simulation software, the fixture is set to a rigid material that will not deform, and the rod A and the rod B are set to a plastic material that can undergo torsional deformation; In JMAtpro software, simulate the element content of the input material to obtain the physical parameters that change with temperature; assign the material relevant physical parameters that change with temperature; Considering that the welding material will be severely deformed during inertia friction welding, the hyperbolic sine constitutive equation is used to describe the relationship between the flow stress, strain and temperature of rod A and rod B: Where A, α, and n are set constants, ΔH is the thermal activation energy of thermal deformation, R = 8.314 J / (mol·K) is the gas constant, T is the temperature during welding, ε is the strain, and σ is the flow stress.

5. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 4, characterized in that: In step S3, the meshing is performed using the mesh window method. Considering the influence of temperature on the welding process, the temperature distribution weight of the mesh window is set to 0.2, and the rest is the window weight. Enter the mesh module of the DEFORM simulation software, select the four-node tetrahedron unit to perform local meshing on the imported geometric model. Set the mesh re-division condition to a maximum growth step of 50 steps, and re-mesh the distorted units to obtain the final mesh model. The grid windows far away from the welding surface are: dense grid area, relatively dense grid area, and sparse grid area; The thermal-mechanical coupling field of the material at the weld changes dramatically. The mesh size of the mesh window at the weld is set to the dense mesh area. Considering the calculation accuracy and efficiency, the mesh size at the weld is set to 0.01; the mesh size of the dense mesh area near the weld is set to 0.1, and the mesh size of the sparse mesh area at the parent material is set to 1; The DEFORM subroutine is used to re-grid the model to eliminate distortion, and the mapping technology is used to assign the data contained in each node unit before re-gridding to the new grid node unit accordingly.

6. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 5, characterized in that: In step S4, enter the tool movement module of the DEFORM simulation software and set the rotation speed of the rotating end fixture and the welding pressure of the mobile end fixture respectively; the rotation speed of the rotating end fixture and the pressure of the mobile end fixture change with time. To ensure the accuracy of the simulation parameters, the real parameters under the corresponding welding conditions are obtained through the inertial friction welding monitoring platform.

7. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 6, characterized in that: In step S5, enter the Boundary conditions module of the DEFORM simulation software to set the displacement conditions and thermal boundary conditions of the finite element model: The thermal boundary conditions are calculated by the following formula: The heat generated by friction and plastic deformation is conducted into the workpiece; the heat loss includes convection heat transfer between the workpiece surface and the environment and heat conduction between the workpiece and the fixture; the effect of thermal radiation on heat loss is negligible; where h c is the heat convection coefficient, λ (w,c) is the thermal conductivity between the workpiece and the fixture, T w 、T a and T c are the temperatures of the workpiece, the surrounding environment and the fixture, respectively, fr The frictional heat, q pl Generates heat for plastic deformation; The boundary conditions of the rotating end fixture are composed of three displacement constraints u (x,0,0) =0,u (0,y,0) =0,u (0,0,z) = 0 and two rotation constraints θ (x，0，0) =0,θ (0,0,z) = 0; the boundary conditions of the mobile end fixture are composed of two displacement constraints u (x,0,0) =0,u (0,0,z) = 0 and three rotation constraints θ (x，0，0) =0,θ (0,y,0) =0,θ (0,0,z) =0 composition.

8. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 7, characterized in that: In step S6, the relationship between objects is set in DEFORM, including the master-slave relationship between geometric models and the friction type when the bar A and the bar B are in inertia friction welding contact, so as to ensure that the simulation process can be completed smoothly and effectively; In the DEFORM master-slave relationship setting, three pairs of contacts are set: rotating end fixture-rod A, rod A-rod B, rod B-moving end fixture; among them, the rotating end fixture and the moving end fixture are set as the main components; the friction coefficient of the rotating end fixture-rod A and rod B-moving end fixture is set to 1; rod A-rod B is set to face-to-face contact, and the friction coefficient is set to Coulomb friction and shear friction; The friction behavior will change during the welding process, which can be equivalently divided into two stages: Coulomb friction model and shear friction model. In the initial friction stage, the welding interface temperature is low, the workpiece does not undergo plastic deformation, and the friction between the two workpieces is mainly dry friction, so the friction type is expressed by the Coulomb friction model. The corresponding stress formula is: In the formula, τ a is the friction stress, σ a is the normal stress, V a is the relative friction speed, μ is the friction coefficient; In the stable friction stage, the friction between the two workpieces generates a large amount of heat, which causes severe plastic deformation and plastic flow at the end face joint. Therefore, the friction type is represented by the shear friction model, and the corresponding stress formula is: In the formula, τ f is the friction stress, m is the shear friction coefficient, ranging from 0 to 1, v s is the relative linear velocity, and k is the shear yield strength of the metal material.

9. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 8, characterized in that: In step S7, in the simulation control module of the DEFORM simulation software, the simulation termination conditions and the time sub-step increment are set, and then the simulation calculation is performed, and the mesh distortion is controlled by the re-gridding technology; the flash morphology, temperature field, stress-strain field, interface temperature change and axial shortening change after welding are analyzed.

10. The method for flash formation and multi-physical field prediction of inertia friction welding of heterogeneous stainless steels according to claim 9, characterized in that: After completing the simulation calculation, an inertia friction welding test was carried out, and the temperature at the characteristic point was measured using a thermocouple for experimental verification.

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