Method and system for predicting additive and subtractive composite manufacturing stress and deformation of metal thin-wall component

Abstract

The invention discloses a metal thin-wall component additive and subtractive composite manufacturing stress and deformation prediction method and system, and the method comprises the steps: carrying out the three-dimensional modeling of a component sample and a machining tool, importing a model into finite element software, and completing the assembly of the component sample and the tool; establishing a thermal elastic-plastic constitutive equation in the material increasing process in finite element software, and setting material attributes of the component sample; finite element software is used for setting a life-death unit to simulate the material forming behavior in the actual laser cladding process; setting a moving path of the heat source between different cladding layers; calculating an additive temperature field and converting the additive temperature field into a structural unit; a geometric matrix for converting unit node displacement into node strain is obtained, and an additive stress field is obtained; additive simulation stress data are extracted and loaded; a constitutive equation is used for defining material constitutive attributes, and the number of steps and machining time of milling machining analysis are set; and setting a material failure criterion, and calculating the stress distribution and deformation of the sample by using a solver. The testing precision of the residual stress of the metal thin-wall component is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of additive and subtractive hybrid manufacturing, and particularly relates to a method and system for predicting stress and deformation in the additive and subtractive hybrid manufacturing of metal thin-walled components. Background Art

[0002] Traditional laser additive manufacturing technology has process defects such as limited forming accuracy and obvious surface layer deposition lines, and often relies on subsequent machining processes to meet the service performance requirements of parts. For components with complex geometric features (such as internal cavities, shaped holes, and continuous curved surfaces), due to the process characteristics of layer-by-layer stacking, structural interference is likely to occur, resulting in a significant reduction in forming efficiency and material utilization rate. At the same time, the supporting structure and post-processing procedures further extend the manufacturing cycle and significantly increase the production cost. This process limitation makes traditional laser additive manufacturing technology face technical bottlenecks in the overall forming field of complex components, restricting the popularization and application of this technology in the manufacturing field of precision complex components.

[0003] The additive and subtractive hybrid manufacturing technology uses additive manufacturing to achieve rapid and high-degree-of-freedom forming of parts to be processed. After the specimen manufacturing is completed, appropriate machining such as milling is selected to reduce the surface roughness of the additive part. Combining these two technologies can efficiently and accurately complete the processing of the specimen. The additive and subtractive hybrid manufacturing technology not only retains the advantages of additive manufacturing such as near-net shape forming, short production cycle, and high material utilization rate, but also gives play to the advantages of high surface quality and high dimensional accuracy of subtractive machining, and can solve problems such as large cutting amount of thin-walled parts in traditional machining, inaccessibility of cutting tools for complex internal cavity structures, and insufficient dimensional accuracy of additive manufacturing.

[0004] However, there are still process bottlenecks in the application of additive and subtractive hybrid manufacturing technology. Specifically, in laser melting deposition - milling hybrid manufacturing, the bottleneck problems lie in the inevitable contradictions among tool accessibility, feature finishing, and subsequent heat treatment. The reason is that obvious tensile and compressive stresses will be generated during the rapid thermal cycle in laser melting deposition. Traditional metal additive manufacturing generally requires heat treatment of the additive blank to eliminate residual stresses, and then necessary cutting processing. However, in the process of additive and subtractive hybrid manufacturing, the previous features have been processed to meet the accuracy and surface quality requirements, and subsequent heat treatment processes are hardly allowed. Therefore, there must be complex stress evolution behaviors during the repeated alternation of laser melting deposition hot forming and milling cold processing, which in turn lead to the technical bottlenecks of difficult control of milling deformation and difficult guarantee of process quality, restricting the engineering application of additive and subtractive hybrid manufacturing technology. In addition, existing stress measurement methods such as the hole drilling method and X - ray diffraction method have the disadvantages of low test accuracy and high cost, and it is difficult to accurately measure the residual stress inside the specimen. For some large thin - wall components, it is also difficult to analyze their processing deformation through experiments. Therefore, there is an urgent need for a simulation method of residual stress and processing deformation to simulate the stress evolution and processing deformation of the entire process of additive and subtractive hybrid manufacturing of thin - wall components. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for predicting stress and deformation in additive and subtractive hybrid manufacturing of metal thin - wall components, aiming at the above - mentioned problems in the existing technology, to simplify the measurement of processing deformation in laser additive and subtractive hybrid manufacturing of metal thin - wall components and improve the test accuracy of residual stress.

[0006] To achieve the above purpose, the present invention has the following technical solutions:

[0007] In the first aspect, a method for predicting stress and deformation in additive and subtractive hybrid manufacturing of metal thin - wall components is provided, including:

[0008] Conduct three - dimensional modeling on the metal thin - wall component specimen and the processing tool;

[0009] Import the established three - dimensional model into finite element software and complete the assembly of the metal thin - wall component specimen and the processing tool;

[0010] Establish a thermo - elastoplastic constitutive equation for the additive process in finite element software and set the material properties of the metal thin - wall component specimen;

[0011] Use finite element software to set birth and death elements to simulate the material forming behavior in the actual laser cladding process;

[0012] Set the movement path of the heat source between different cladding layers;

[0013] Calculate the additive temperature field, import the additive temperature field into finite element software and convert it into structural elements;

[0014] Obtain the geometric matrix for converting the nodal displacements of the structural unit into nodal strains, and obtain the additive stress field;

[0015] Extract the additive simulation stress data related to the loading from the additive stress field according to all the element integration points of the structural unit;

[0016] Define the material constitutive properties using the constitutive equation, and set the number of steps and processing time for the milling process analysis;

[0017] Set the material failure criterion to simulate the milling process, and use the solver to calculate the stress distribution and deformation of the specimen.

[0018] As a preferred solution, the step of three-dimensional modeling of the metal thin-walled component specimen and the machining tool uses the mm unit for the three-dimensional model establishment;

[0019] The finite element software uses Abaqus engineering simulation finite element software. For the step of importing the established three-dimensional model into the finite element software, the file formats of the three-dimensional models imported into Abaqus include IGES (*.igs), STEP (*.stp), or SA (*.sat);

[0020] In the step of establishing the thermo-elastoplastic constitutive equation for the additive process in the finite element software and setting the material properties of the metal thin-walled component specimen, the material property parameters of the metal thin-walled component specimen include any one or a combination of density, Young's modulus, Poisson's ratio, specific heat capacity, thermal conductivity, coefficient of thermal expansion, and yield strength of the material at different temperatures;

[0021] The expression of the thermo-elastoplastic constitutive equation for the additive process is as follows:

[0022] {dσ} = [D]{dε} - {C}dT

[0023] [D] = [D] e

[0024]

[0025] In the formula, [D] is the elastic or elastoplastic matrix; {C} is the vector related to temperature; {α} is the linear expansion coefficient of the material.

[0026] As a preferred solution, when using finite element software to set up birth and death elements to simulate the behavior of material forming during the actual laser cladding process, the Model change function of Abaqus engineering simulation finite element software is used to set up birth and death elements. The Deactivate command is "kill", and the Reactivate command is "activate". In the initial analysis step, the heat source has not been loaded yet. All elements are "killed" within the set time. The analysis characteristic matrix of the elements in the "killed" state is multiplied by a weakening factor. Then, as the heat source moves, the elements that have been "killed" are activated one by one, and the analysis characteristics of the corresponding elements are restored to the original values.

[0027] Before the step of setting the moving path of the heat source between different cladding layers, setting the thermal boundary conditions of the material is also included.

[0028] The physical meaning of the first type of boundary condition is to specify the temperature value on the boundary of the object, and the expression is as follows:

[0029] T Ω = T(x, y, z, t)

[0030] The second type of boundary condition stipulates the heat flux density on the boundary of the object, and the expression is as follows:

[0031]

[0032] The physical meaning of the third type of boundary condition is that heat convection and heat exchange continuously occur outside the object, and the expression is as follows:

[0033]

[0034] In the formula, h is the heat transfer coefficient; T Ω is the temperature on the boundary; T ∞ is the ambient temperature.

[0035] As a preferred solution, in the step of setting the moving path of the heat source between different cladding layers, planar Gaussian heat source is used for cladding, and the Fortran code is used to define the moving path of the heat source. The different starting points of the heat source are set through the iF time loop to achieve the movement of the heat source between different cladding layers. The heat source expression is as follows:

[0036]

[0037] In the formula: q is the heat flux density; A is the laser absorption rate; P is the laser power; r is the laser radius; v x is the scanning speed of the laser along the x direction; v y is the scanning speed of the laser along the y direction; t is the moving time of the heat source.

[0038] As a preferred solution, the method for predicting stress and deformation in the hybrid additive and subtractive manufacturing of metal thin-walled components further includes meshing the metal thin-walled component specimen and the machining tool, including using sweep meshing for the metal thin-walled component specimen and setting it as hexahedral element C3D8R, and setting the machining tool mesh as free meshing using tetrahedral meshes;

[0039] In the step of calculating the additive temperature field, when performing heat transfer analysis, the solution results of the temperature field are discretized to the nodes of each element, and the temperature at each position inside the element is extended to the entire element through the interpolation function of the corresponding element;

[0040] For the finite element solution of the heat conduction differential equation, the temperature field distribution within each discrete solution domain is expressed as:

[0041] {T} = [N]{T} e

[0042] where {T} is the temperature at any point within the element; [N] is the shape function; {T} e is the temperature value of each node on the element;

[0043] For the overall temperature field, there is:

[0044] [K][T] = [F]

[0045] where:

[0046] [K] = ∑([K1] e + [K2] e )

[0047]

[0048]

[0049] where [K] is the heat conduction matrix; [K1] e is the heat conduction term; [B] is the heat conduction matrix of the shape function; [D e is the elastic matrix in stress and strain; [K2] e is the convective heat transfer term;

[0050] Import the additive temperature field calculation result file into the Abaqus engineering simulation finite element software in the form of a predefined field, and convert the temperature field elements into hexahedral elements C3D8R.

[0051] As a preferred solution, the step of obtaining the geometric matrix for converting the displacement of the unit nodes into node strains according to the structural unit to obtain the additive stress field is specific to the heat balance equation of each unit, and the expression is as follows:

[0052] {dF} e + {dR}e = [K] e {dδ} e

[0053] where {dF} e is the incremental element nodal load; {dR} e is the incremental element nodal force caused by temperature; [K] e is the element stiffness matrix; {dδ} e is the incremental element nodal displacement;

[0054] where:

[0055] {dF} e + {dR} e = [K] e {dδ} e

[0056]

[0057] where [B] is the geometric matrix that converts element nodal displacements into nodal strains, and the calculation expression is as follows:

[0058] {dε} e = [B]{dδ} e

[0059] By combining the above equations, as the load is applied, the element nodal displacement is calculated, and then the geometric matrix [B] that converts the element nodal displacement into nodal strain is used to obtain the nodal strain, thereby obtaining the final stress field.

[0060] As a preferred solution, in the step of extracting the additive simulation stress data from the additive stress field according to all the element integration points of the structural element, the stress state of a point in space is determined by 9 stress components. Based on the theorem of reciprocal shear stresses, the stress state of the corresponding element point is determined by defining the normal stresses in 3 directions and the shear stresses in 3 directions of the element integration point; six-direction stresses σ x 、σ y 、σ z 、τ x 、τ y 、τ z are extracted at all the element integration points in the resulting odb file, where the first three stresses represent the normal stresses in three directions respectively, and the last three terms are shear stresses. The integral point residual stress expression is as follows:

[0061]

[0062] As a preferred solution, in the step of defining the material constitutive property using the constitutive equation and setting the number of steps and machining time for the milling process analysis, the Johnson-Cook constitutive equation is used to define the material constitutive property. The expression of the Johnson-Cook constitutive equation is as follows:

[0063]

[0064] In the formula: ε is the equivalent plastic strain; is the equivalent plastic strain rate; is the equivalent plastic strain rate and the reference plastic strain rate; T is the temperature of the cutting part of the workpiece; T r is the melting point of the material; T m is the ambient temperature; n is the strain hardening index; m is the thermal softening index; A is the yield strength; B is the hardening modulus; C is the strain rate hardening parameter.

[0065] As a preferred solution, in the step of setting the material failure criterion to simulate the milling process, the J-C damage model is used. The expression of the equivalent plastic strain at damage of the J-C damage model is as follows:

[0066]

[0067] In the formula: is the equivalent plastic strain at material failure; d1 - d5 are the failure parameters of the material at room temperature; η is the dimensionless deviatoric stress ratio; is the plastic strain rate; is the reference plastic strain rate;

[0068] Set the slip and adhesion friction model existing between the rake face of the tool and the chip in the actual milling process. The expression is as follows:

[0069]

[0070] In the formula: τ f is the friction stress; μ is the friction coefficient; σ n is the contact direction stress; τ s is the shear stress;

[0071] When using the solver to calculate the stress distribution and deformation of the specimen, an ALE adaptive mesh is divided in the part that needs to be milled, allowing the mesh to be independently adjusted relative to the movement of the material.

[0072] In a second aspect, a stress and deformation prediction system for additive and subtractive composite manufacturing of metal thin-walled components is provided, including:

[0073] A three-dimensional model establishment module for three-dimensionally modeling the metal thin-walled component specimen and the machining tool;

[0074] A finite element software import module for importing the established 3D model into the finite element software and completing the assembly of the metal thin-walled component specimen and the machining tool;

[0075] A finite element software parameter setting module for establishing a thermo-elastoplastic constitutive equation for the additive process in the finite element software and setting the material properties of the metal thin-walled component specimen;

[0076] A laser cladding process simulation module for using the finite element software to set up birth and death elements to simulate the material forming behavior during the actual laser cladding process;

[0077] A heat source movement path setting module for setting the movement path of the heat source between different cladding layers;

[0078] An additive temperature field calculation and conversion module for calculating the additive temperature field, importing the additive temperature field into the finite element software and converting it into structural elements;

[0079] An additive stress field acquisition module for obtaining the geometric matrix that converts the nodal displacements of the unit nodes into nodal strains according to the structural elements to obtain the additive stress field;

[0080] A stress data extraction and loading module for extracting and loading the additive simulation stress data from the additive stress field according to all the unit integration points of the structural elements;

[0081] A milling process setting module for defining the material constitutive properties using the constitutive equation and setting the number of steps and processing time for the milling process analysis;

[0082] A specimen stress distribution and deformation calculation module for setting the material failure criterion to simulate the milling process and using the solver to calculate the specimen stress distribution and deformation.

[0083] Compared with the prior art, the present invention has at least the following beneficial effects:

[0084] The present invention proposes a full-process multi-physical field dynamic evolution modeling method for laser additive and subtractive hybrid manufacturing of metal thin-walled components. By establishing a real-time coupling simulation system for additive deposition and subtractive milling, seamless connection of the process chain is achieved. Based on the thermo-mechanical coupling constitutive and material constitutive models, accurate calculation of the residual stress distribution and structural machining deformation behavior in the whole process can be implemented. Based on the simulation method of the present invention, process optimization of the machining process can be carried out, thereby reducing the magnitude of the residual stress and machining deformation of the specimen, and then preparing high-precision workpieces with excellent mechanical properties and fully meeting the actual application requirements.

[0085] Furthermore, the present invention is based on the thermo-mechanical coupling constitutive model, the birth-death element technology in the Abaqus engineering simulation finite element software, and the Johnson-Cook constitutive model, and develops an algorithm for extracting the stress of inter-process elements. Through this algorithm, the six stress components of each element in the simulation of the additive process can be extracted into a csv file, and then the stress document is imported into the subsequent milling process INP file by using the initial conditions function to achieve seamless connection of the stress field evolution in the additive and subtractive manufacturing process chains. The present invention can solve the problem that it is difficult to accurately measure the stress and deformation of the additive and subtractive specimens at present, can more conveniently capture the stress evolution during the additive and subtractive process and the deformation of the thin-walled specimens. In addition, using the method of the present invention to optimize the process during machining can reduce the residual stress and machining deformation of the specimens, and then prepare high-precision workpieces with excellent mechanical properties and fully meeting the actual application requirements. Description of the Drawings

[0086] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and those of ordinary skill in the art can also obtain other relevant drawings without creative efforts based on these drawings.

[0087] Figure 1 Schematic diagram of the assembly model of the end mill and the 316L stainless steel thin-walled sample in the embodiment of the present invention;

[0088] Figure 2 Material property diagram of 316L stainless steel in the embodiment of the present invention;

[0089] Figure 3 Code diagram of the heat source subroutine in the embodiment of the present invention;

[0090] Figure 4 Schematic diagram of the mesh division of the additive and subtractive model of the 316L stainless steel thin-walled sample and the end mill in the embodiment of the present invention;

[0091] Figure 5 Flow chart of the extraction and import of additive residual stress in the embodiment of the present invention;

[0092] Figure 6 Flow chart of the simulation calculation of metal laser additive manufacturing in the embodiment of the present invention;

[0093] Figure 7 Flow chart of the simulation of the milling process of the additive specimen in the embodiment of the present invention;

[0094] Figure 8 Simulation calculation result diagram of the additive and subtractive stress field of 316L stainless steel in the embodiment of the present invention;

[0095] Figure 9The simulation calculation result diagram of the deformation of 316L stainless steel in the additive and subtractive manufacturing process in the embodiments of the present invention. Detailed implementation manners

[0096] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, those of ordinary skill in the art can also obtain other embodiments without making creative efforts.

[0097] The embodiments of the present invention propose a method for predicting the stress and deformation of an additive and subtractive composite manufacturing of a metal thin-walled component, including:

[0098] S1. Perform three-dimensional modeling on the metal thin-walled component specimen and the machining tool;

[0099] S2. Import the established three-dimensional model into the finite element software and complete the assembly of the metal thin-walled component specimen and the machining tool;

[0100] S3. Establish a thermo-elastoplastic constitutive equation for the additive process in the finite element software and set the material properties of the metal thin-walled component specimen;

[0101] S4. Use the finite element software to set up birth and death elements to simulate the behavior of material forming in the actual laser cladding process;

[0102] S5. Set the movement path of the heat source between different cladding layers;

[0103] S6. Calculate the additive temperature field, import the additive temperature field into the finite element software and convert it into structural elements;

[0104] S7. Obtain the geometric matrix for converting the unit node displacement to node strain according to the structural elements to obtain the additive stress field;

[0105] S8. Extract and load the additive simulation stress data from the additive stress field according to all the unit integration points of the structural elements;

[0106] S9. Define the material constitutive properties using the constitutive equation and set the number of steps and machining time for the milling process analysis;

[0107] S10. Set the material failure criterion to simulate the milling process and use the solver to calculate the stress distribution and deformation of the specimen.

[0108] In a possible implementation manner, in the process of performing three-dimensional modeling on the metal thin-walled component specimen and the machining tool in step S1, the three-dimensional model is established using mm as the unit.

[0109] In the embodiment of the present invention, the finite element software adopts Abaqus (Advanced Simulation for Engineering and Sciences), an engineering simulation finite element software. The step of importing the established three-dimensional model into the finite element software, and the file formats of the three-dimensional models imported into Abaqus include IGES (*.igs), STEP (*.stp), or SA (*.sat), etc.

[0110] In the step of establishing the thermo-elastoplastic constitutive equation for the additive process and setting the material properties of the metal thin-walled component specimen in the finite element software, the material property parameters of the metal thin-walled component specimen include any one or a combination of multiple ones among density, Young's modulus, Poisson's ratio, specific heat capacity, thermal conductivity, coefficient of thermal expansion, and yield strength of the material at different temperatures.

[0111] The expression of the thermo-elastoplastic constitutive equation for the additive process described in step S3 is as follows:

[0112] {dσ} = [D]{dε} - {C}dT

[0113] [D] = [D] e

[0114]

[0115] In the formula, [D] is the elastic or elastoplastic matrix; {C} is the vector related to temperature; {α} is the linear expansion coefficient of the material.

[0116] In a possible implementation manner, in step S4, the Model change function of the Abaqus engineering simulation finite element software is used to set the birth and death elements to simulate the behavior of the material from nothing to something in the actual laser cladding process. The Deactivate command is "kill", and the Reactivate command is "activate"; in the initial analysis step, when the heat source has not been loaded yet, all elements are "killed" within a very short time. The analysis property (stiffness or conduction and other analysis properties) matrix of the elements in the "killed" state is multiplied by a weakening factor (the elastic modulus is close to 0), making its influence on the structure extremely small. Then, as the heat source moves, the "killed" elements are gradually "activated" and reactivated as "live elements", and the stiffness, mass, element load, etc. are restored to their original values.

[0117] In a possible implementation manner, before the step of setting the movement path of the heat source between different cladding layers, setting the thermal boundary conditions of the material is also included; the calculation of the temperature field of metal laser direct energy deposition usually includes the following types of boundary conditions:

[0118] The physical meaning of the first type of boundary condition is to specify the temperature value on the boundary of the object, and the expression is as follows:

[0119] T Ω = T(x, y, z, t)

[0120] The second type of boundary condition specifies the heat flux density on the boundary of the object, and the expression is as follows:

[0121]

[0122] The physical meaning of the third type of boundary condition is that heat convection and heat exchange continuously occur outside the object, and the expression is as follows:

[0123]

[0124] In the formula, h is the heat transfer coefficient; T Ω is the temperature on the boundary; T ∞ is the temperature of the surrounding environment.

[0125] In a possible implementation manner, in step S5, a planar Gaussian heat source is used for cladding, and the movement path of the heat source is defined by Fortran code. By setting different starting points of the heat source through the iF time loop, the movement of the heat source between different cladding layers is achieved; the expression of the heat source is as follows:

[0126]

[0127] In the formula: q is the heat flux density; A is the laser absorption rate; P is the laser power; r is the laser radius; v x is the scanning speed of the laser along the x direction; v y is the scanning speed of the laser along the y direction; t is the movement time of the heat source.

[0128] In a possible implementation manner, it also includes meshing the metal thin-walled component specimen and the machining tool considering calculation accuracy and calculation efficiency. Specifically, it includes using sweep meshing for the metal thin-walled component specimen and setting it as a hexahedral element C3D8R, and setting the machining tool mesh as free meshing using tetrahedral meshes.

[0129] In a possible implementation manner, in step S6, in the step of calculating the additive temperature field, when performing heat transfer analysis, the solution result of the temperature field is discretized to the nodes of each element, and at the same time, the temperature at each position inside the element is extended to the entire element through the interpolation function (i.e., the shape function) of the corresponding element; for the finite element solution of the heat conduction differential equation, the temperature field distribution in each discrete solution domain is expressed as:

[0130] {T} = [N]{T} e

[0131] where {T} is the temperature at any point within the element; [N] is the shape function; {T} e is the temperature value at each node on the element;

[0132] For the overall temperature field, we have:

[0133] [K][T] = [F]

[0134] Among them:

[0135] [K] = ∑([K1] e + [K2] e )

[0136]

[0137]

[0138] In the formula, [K] is the heat conduction matrix; [K1] e is the heat conduction term; [B] is the heat conduction matrix of the shape function; [D e is the elastic matrix in stress and strain; [K2] e is the convective heat transfer term; The load vector includes three terms. Among them, the first term is the load generated by the internal heat source, the second term is the load generated by the heat flux density, and the third term is the load generated by the convective heat transfer.

[0139] Import the calculation result file of the additive temperature field into the Abaqus engineering simulation finite element software in the form of a predefined field, and convert the temperature field elements into hexahedral elements C3D8R. The C3D8R element is a commonly used three-dimensional eight-node hexahedral linear reduced integration element in Abaqus. Compared with the fully integrated element, the linear reduced integration element only contains one integration point at the center of the element.

[0140] In a possible implementation manner, the step of calculating the additive stress field in step S8, specifically for the heat balance equation of each element, is expressed as follows:

[0141] {dF} e + {dR} e = [K] e {dδ} e

[0142] In the formula, {dF} e is the increment of the element node load; {dR} e is the increment of the element node force caused by temperature; [K] e is the element stiffness matrix; {dδ} e is the increment of the element node displacement;

[0143] Among them:

[0144] {dF}e +{dR} e =[K] e {dδ} e

[0145]

[0146] In the formula, [B] is the geometric matrix that converts the element nodal displacement into nodal strain, and the calculation expression is as follows:

[0147] {dε} e =[B]{dδ} e

[0148] By combining the above formulas, with the application of the load, the element nodal displacement is calculated, and then the geometric matrix [B] that converts the element nodal displacement into nodal strain is used to obtain the nodal strain, thereby obtaining the final stress field.

[0149] In a possible implementation manner, when step S8 extracts the additive simulation stress data for loading, the stress state of a point in space is determined by 9 stress components. Based on the theorem of shear stress reciprocity, only the normal stresses in 3 directions and the shear stresses in 3 directions at the element integration points need to be defined to determine the stress state of the corresponding element points; in the embodiment of the present invention, the six-direction stresses σ x 、σ y 、σ z 、τ x 、τ y 、τ z at all element integration points in the extracted result ODB file are obtained. The ODB file is an output database file generated by the Abaqus finite element analysis software for storing analysis results, including model information, analysis steps, field variable outputs (such as displacements, stresses, strains, etc.) and historical variable outputs (such as energies, reaction forces, etc.). The first three stresses respectively represent the normal stresses in three directions, and the last three items are shear stresses. The integral point residual stress expression is as follows:

[0150]

[0151] The specific implementation method in Abaqus is as follows: First, extract the stress values in 6 directions of the elements in the odb result file of the numerical simulation of the laser directed energy deposition stress field distribution, and centrally save the values to a csv document, and then make necessary format modifications. After the document modification is completed, write the keyword 'INITIAL CONDITIONS,TYPE=STRESS' in the milling simulation inp file, and call the modified stress document to complete the import of the laser directed energy deposition residual stress field.

[0152] In a possible implementation, step S9 uses the Johnson-Cook constitutive equation to define the material constitutive properties and sets the number of steps and machining time for the milling process analysis. The Johnson-Cook (J-C) constitutive model is a mathematical model used to describe the non-linear stress-strain relationship of metallic materials under complex environments such as high temperature and high strain rate.

[0153] The expression of the Johnson-Cook constitutive equation is:

[0154]

[0155] Where: ε is the equivalent plastic strain; is the equivalent plastic strain rate; is the equivalent plastic strain rate and the reference plastic strain rate; T is the temperature of the cutting part of the workpiece; T r is the melting point of the material; T m is the ambient temperature; n is the strain hardening exponent; m is the thermal softening exponent; A is the yield strength; B is the hardening modulus; C is the strain rate hardening parameter.

[0156] In step S10, during actual milling, as the milling cutter feeds and rotates, the material on the workpiece continuously detaches from the specimen in the form of chips. In milling simulation, it is necessary to set a material failure criterion for simulation.

[0157] The step of setting the material failure criterion to simulate the milling process uses the J-C damage model. The expression of the equivalent plastic strain at damage of the J-C damage model is as follows:

[0158]

[0159] Where: is the equivalent plastic strain at material failure; d1 - d5 are the failure parameters of the material at room temperature; η is the dimensionless deviatoric stress ratio; is the plastic strain rate; is the reference plastic strain rate;

[0160] When performing actual milling simulation, in order to improve the simulation accuracy, it is necessary to define a reasonable friction model between the tool and the workpiece. An unreasonable friction model will cause numerical instability and non-convergence in the finite element calculation. Therefore, a slip and adhesion friction model existing between the rake face of the tool and the chip in actual milling is set, and the expression is as follows:

[0161]

[0162] Where: τ f is the friction stress; μ is the friction coefficient; σ n is the stress in the contact direction; τ sis the shear stress;

[0163] In another possible embodiment, the tool-workpiece contact property is set to node-to-node contact, and the normal and tangential contact properties between the two are defined.

[0164] When using the solver to calculate the stress distribution and deformation of the specimen, an ALE (Arbitrary Lagrangian-Eulerian adaptive meshing) adaptive mesh is divided in the part that needs to be milled. The ALE adaptive mesh technology allows the mesh to be independently adjusted relative to the movement of the material. This flexibility can also improve the accuracy and reliability of the calculation results, and improve the control ability of element distortion during large deformations, making the model easier to converge.

[0165] Furthermore, the adaptive mesh only needs to be set in the part that needs to be milled to reduce the calculation time.

[0166] Finally, milling simulation is performed, and the solver is used to calculate the stress distribution and deformation of the specimen based on the J-C constitutive model.

[0167] The embodiment of the present invention proposes a full-process multi-physical field dynamic evolution modeling method for laser additive and subtractive composite manufacturing of metal thin-walled components. By establishing a real-time coupling simulation system for additive deposition and subtractive milling, seamless connection of the process chain is achieved. Based on the thermo-mechanical coupling constitutive and J-C constitutive models, accurate calculation of the residual stress distribution and structural machining deformation behavior in the whole process can be implemented. The simulation method based on the embodiment of the present invention can optimize the process during the machining process to reduce the residual stress and machining deformation of the specimen, and then prepare high-precision workpieces with excellent mechanical properties and fully meeting the actual application requirements.

[0168] Please refer to Figures 5 to 7 , in another embodiment, the stress and deformation calculation method for laser additive and subtractive composite manufacturing of metal thin-walled components includes the following steps:

[0169] (1) Establishment of the three-dimensional models of the deposited specimen and the milling cutter: According to the typical characteristics of the thin-walled component, the modeling of the deposited specimen is completed in Abaqus; its size is 42×4.2×16 mm; the modeling of the end mill is completed in Solidworks;

[0170] (2) Model import and assembly: The three-dimensional models established in are imported into the Abaqus software and assembled; Figure 1 The figure shows a schematic diagram of the assembly model of the end mill and the 316L stainless steel thin-walled sample;

[0171] (3) Material property settings: Set the density, Young's modulus, Poisson's ratio, specific heat capacity, thermal conductivity, coefficient of thermal expansion, and yield strength of 316L stainless steel at different temperatures. Figure 2 The specific parameters are shown.

[0172] (4) Additive analysis step settings: Set the number of simulation analysis steps and related parameters, and set the output of the analysis step field, where the analysis step type is set to thermo-mechanical coupling; considering the need for cooling after processing, the cooling time of 1800 s is set for the last step of the analysis step.

[0173] (5) Birth and death element settings: In the Abaqus interaction module, use the Model change function to set the birth and death elements. Further, use a Python script to complete the division of the birth and death elements of the 316L stainless steel specimen model.

[0174] (5) Thermal boundary condition settings: Set the heat convection coefficient between the 316L stainless steel specimen and the outside world to 0.055 mw / mm 2 in the Abaqus interaction module, and set the environmental temperature to room temperature of 20 °C.

[0175] (6) Mobile heat source settings and loading: Set the laser absorption rate to 0.6, the laser heat source radius to 1 mm, and the scanning speed to 6 mm / s. Figure 3 The heat source subroutine code of the embodiment of the present invention is shown.

[0176] (7) Mesh generation: Use sweep meshing for the 316L workpiece, and locally refine the milling area. The mesh size of the embodiment of the present invention is 0.15 mm; the total number of meshes is 290,000; assuming the material is isotropic, all use C3D8R eight-node hexahedral thermal transfer elements, as Figure 4 shown.

[0177] (8) Additive temperature field calculation: Submit the job in Abaqus and use the Standard solver to solve the temperature field distribution.

[0178] (9) Import of additive temperature field and conversion of structural elements: Import the temperature field result file in the form of a predefined field, and then convert the temperature field elements to structural elements C3D8R.

[0179] (10) Additive stress field calculation: Submit the job in Abaqus and still use the Standard solver to solve the stress field distribution.

[0180] (11) Additive manufacturing simulation stress data extraction and loading: The stress state of a point in space is determined by nine stress components. Due to the shear stress reciprocity theorem, therefore, only the normal stresses in three directions and the three shear stresses at the element integration points need to be defined to determine the stress state of the element point. An embodiment of the present invention proposes a method for extracting the six-direction stresses at all element integration points in the result odb file, namely σ x σ y σ z τ x τ y τ z , where the first three stresses represent the normal stresses in three directions respectively, and the last three terms are shear stresses. The integral point residual stress expression is specifically as follows:

[0181]

[0182] Its specific implementation method in Abaqus is to first extract the stress values in six directions of the elements in the odb result file of the laser directed energy deposition stress field distribution numerical simulation, and centrally save the values to a csv document, and then make necessary format modifications. After the document modification is completed, write the keyword 'INITIAL CONDITIONS,TYPE=STRESS' in the milling simulation inp file, and call the modified stress document to complete the import of the laser directed energy deposition residual stress field.

[0183] (12) Milling analysis step and constitutive model setting: Use the Johnson-Cook constitutive equation to define the constitutive properties of 316L stainless steel, and set the number of steps of the milling process analysis step to 1, and the processing time is set to 14 s; the Johnson-Cook constitutive equation is:

[0184]

[0185] In the formula: ε is the equivalent plastic strain; is the equivalent plastic strain rate; is the equivalent plastic strain rate and the reference plastic strain rate; T is the temperature of the workpiece cutting part / K; T r is the melting point of the material / K; T m is the ambient temperature / K; n is the strain hardening index; m is the thermal softening index; A is the yield strength / MPa; B is the hardening modulus; C is the strain rate hardening parameter.

[0186] (13) Material failure separation criterion setting: Use the J-C damage constitutive model;

[0187] (14) Friction model and contact setting: Use the penalty function in the Abaqus interaction module to set the contact between the tool and the workpiece as hard contact, and the friction coefficient is set to 0.25;

[0188] (15) ALE Adaptive Mesh Generation: The ALE adaptive mesh technology allows the mesh to be independently adjusted relative to the material movement. This flexibility can also improve the accuracy and reliability of the calculation results, enhance the control ability of element distortion during large deformations, and make the model more prone to convergence. Set the mesh area that needs to be adapted in the analysis step;

[0189] (16) Milling Simulation: Submit the job in Abaqus and use the Explicit solver to solve the milling stress and deformation distribution.

[0190] Figure 8 The simulation calculation results of the additive and subtractive stress fields of 316L stainless steel in the embodiments of the present invention are shown. Figure 9 The simulation calculation results of the additive and subtractive processing deformations of 316L stainless steel in the embodiments of the present invention are shown. From Figure 8 and Figure 9 it can be seen that the present invention can achieve seamless connection of the process chain by establishing a real-time coupling simulation system for additive deposition and subtractive milling. Based on the thermo-mechanical coupling constitutive and J-C constitutive models, the residual stress distribution and structural processing deformation behavior in the whole process can be accurately solved. In addition, based on this simulation method, the processing process can be optimized to reduce the residual stress and processing deformation of the specimen, and then a high-precision workpiece with excellent mechanical properties and fully meeting the actual application requirements can be prepared.

[0191] Another embodiment of the present invention also proposes a system for predicting the stress and deformation of additive and subtractive composite manufacturing of metal thin-walled components, including:

[0192] A three-dimensional model establishment module for three-dimensionally modeling the metal thin-walled component specimen and the processing tool;

[0193] A finite element software import module for importing the established three-dimensional model into the finite element software and completing the assembly of the metal thin-walled component specimen and the processing tool;

[0194] A finite element software parameter setting module for establishing a thermo-elastoplastic constitutive equation in the finite element software and setting the material properties of the metal thin-walled component specimen;

[0195] A laser cladding process simulation module for using the finite element software to set the birth and death elements to simulate the behavior of material forming during the actual laser cladding process;

[0196] A heat source movement path setting module for setting the movement path of the heat source between different cladding layers;

[0197] An additive temperature field calculation and conversion module for calculating the additive temperature field, importing the additive temperature field into the finite element software and converting it into structural elements;

[0198] The additive stress field acquisition module is used to obtain the geometric matrix that converts the node displacements of unit nodes into node strains according to structural units, and obtain the additive stress field;

[0199] The stress data extraction and loading module is used to extract and load the additive simulation stress data from the additive stress field according to all the element integration points of the structural units;

[0200] The milling process setting module is used to define the material constitutive properties using the constitutive equation, and set the number of steps and processing time of the milling process analysis;

[0201] The specimen stress distribution and deformation calculation module is used to set the material failure criterion to simulate the milling process, and use the solver to calculate the specimen stress distribution and deformation.

[0202] Another embodiment of the present invention proposes an electronic device, including:

[0203] A memory storing at least one instruction; and a processor that executes the instruction stored in the memory to implement the method for predicting the stress and deformation of the additive and subtractive composite manufacturing of metal thin-walled components.

[0204] Another embodiment of the present invention proposes a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the method for predicting the stress and deformation of the additive and subtractive composite manufacturing of metal thin-walled components.

[0205] Exemplarily, the instruction stored in the memory can be divided into one or more modules / units, and the one or more modules / units are stored in the computer-readable storage medium and executed by the processor to complete the method for predicting the stress and deformation of the additive and subtractive composite manufacturing of metal thin-walled components of the present invention. The one or more modules / units can be a series of computer-readable instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the server.

[0206] The electronic device can be a computing device such as a smart phone, a notebook, a palm computer, and a cloud server. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the electronic device may further include more or fewer components, or combine certain components, or different components. For example, the electronic device may further include input / output devices, network access devices, a bus, etc.

[0207] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0208] The memory may be an internal storage unit of the server, such as the hard disk or memory of the server. The memory may also be an external storage device of the server, such as a plug-in hard disk equipped on the server, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory may also include both the internal storage unit and the external storage device of the server. The memory is used to store the computer-readable instructions and other programs and data required by the server. The memory may also be used to temporarily store data that has been output or will be output.

[0209] It should be noted that for the information interaction, execution process, etc. between the above-mentioned module units, since it is based on the same concept as the method embodiment, for its specific functions and the technical effects brought, reference may be specifically made to the method embodiment part, and details will not be elaborated here.

[0210] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, and details will not be elaborated here.

[0211] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device capable of carrying the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc.

[0212] In the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0213] The above-described embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for predicting stress and deformation in the hybrid manufacturing of metal thin-walled components by additive and subtractive processes, characterized in that, Including: Performing 3D modeling on the metal thin-walled component specimen and the machining tool; Importing the established 3D model into finite element software and completing the assembly of the metal thin-walled component specimen and the machining tool; Establishing a thermo-elastoplastic constitutive equation for the additive process in the finite element software and setting the material properties of the metal thin-walled component specimen; Using the finite element software to set birth and death elements to simulate the material forming behavior in the actual laser cladding process; Setting the movement path of the heat source between different cladding layers; Calculating the additive temperature field, importing the additive temperature field into the finite element software and converting it into structural elements; Obtaining the geometric matrix for converting the unit node displacement to node strain according to the structural elements to obtain the additive stress field; Extracting and loading the additive simulation stress data from the additive stress field according to all the unit integration points of the structural elements; Defining the material constitutive properties using the constitutive equation and setting the number of steps and machining time for the milling process analysis; Setting the material failure criterion to simulate the milling process and using the solver to calculate the stress distribution and deformation of the specimen.

2. The stress and deformation prediction method for the additive and subtractive composite manufacturing of thin-walled metal components according to claim 1, wherein In the step of performing 3D modeling on the metal thin-walled component specimen and the machining tool, the 3D model is established using mm as the unit; The finite element software uses Abaqus engineering simulation finite element software. In the step of importing the established 3D model into the finite element software, the file formats of the 3D models imported into Abaqus include IGES (*.igs), STEP (*.stp), or SA (*.sat); In the step of establishing a thermo-elastoplastic constitutive equation for the additive process in the finite element software and setting the material properties of the metal thin-walled component specimen, the material property parameters of the metal thin-walled component specimen include any one or a combination of density, Young's modulus, Poisson's ratio, specific heat capacity, thermal conductivity, coefficient of thermal expansion, and yield strength of the material at different temperatures; The expression of the thermo-elastoplastic constitutive equation for the additive process is as follows: {dσ} = [D]{dε} - {C}dT [D] = [D] e In the formula, [D] is the elastic or elastoplastic matrix; {C} is the vector related to temperature; {α} is the linear expansion coefficient of the material.

3. The stress and deformation prediction method for additive and subtractive composite manufacturing of thin-walled metal components according to claim 1, characterized in that, When using the finite element software to set birth and death elements to simulate the material forming behavior in the actual laser cladding process, use the Model change function of Abaqus engineering simulation finite element software to set birth and death elements. The Deactivate command is "kill", and the Reactivate command is "activate"; in the initial analysis step, the heat source has not been loaded yet. All elements are "killed" within the set time. The analysis characteristic matrix of the elements in the "killed" state is multiplied by a weakening factor. Then, as the heat source moves, the "killed" elements are gradually "activated" one by one, and the analysis characteristics of the corresponding elements are restored to the original values; Before the step of setting the movement path of the heat source between different cladding layers, it also includes setting the thermal boundary conditions of the material; The physical meaning of the first type of boundary condition is to specify the temperature value on the boundary of the object, and the expression is as follows: T Ω = T(x, y, z, t) The second type of boundary condition specifies the heat flux density on the boundary of the object, and the expression is as follows: The physical meaning of the third type of boundary condition is that heat convection and heat exchange continuously occur outside the object, and the expression is as follows: Where h is the heat transfer coefficient; T Ω is the temperature at the boundary; T ∞ is the ambient temperature.

4. The stress and deformation prediction method for the hybrid additive and subtractive manufacturing of thin-walled metal components according to claim 1, wherein In the step of setting the movement path of the heat source between different cladding layers, a planar Gaussian heat source is used for cladding, and the movement path of the heat source is defined using Fortran code. The different starting points of the heat source are set through the iF time loop to achieve the movement of the heat source between different cladding layers. The heat source expression is as follows: Where: q is the heat flux density; A is the laser absorption rate; P is the laser power; r is the laser radius; v x is the laser scanning speed in the x direction; v y is the laser scanning speed in the y direction; t is the heat source moving time.

5. The stress and deformation prediction method for hybrid additive and subtractive manufacturing of thin-walled metal components according to claim 1, characterized in that It also includes meshing the metal thin-walled component specimen and the machining tool. For the metal thin-walled component specimen, swept meshing is used and set as hexahedral element C3D8R, and the machining tool mesh is set as free meshing using tetrahedral mesh. In the step of calculating the additive temperature field, when performing heat transfer analysis, the solution results of the temperature field are discretized to the nodes of each element, and the temperature at each position inside the element is extended to the entire element through the interpolation function of the corresponding element. For the finite element solution of the heat conduction differential equation, the temperature field distribution within each discrete solution domain is expressed as: {T} = [N]{T} e Where, {T} is the temperature at any point within the element; [N] is the shape function; {T} e is the temperature value at each node on the element; For the overall temperature field, there is: [K][T] = [F] Where: [K] = ∑([K1] e + [K2] e ) In the formula, [K] is the heat conduction matrix; [K1] e is the heat conduction term; [B] is the heat conduction matrix of the shape function; [D e is the elastic matrix in stress and strain; [K2] e is the convective heat transfer term; The additive temperature field calculation result file is imported into the Abaqus engineering simulation finite element software in the form of a predefined field, and the temperature field elements are converted into hexahedral elements C3D8R.

6. The stress and deformation prediction method for the hybrid additive and subtractive manufacturing of thin-walled metal components according to claim 1, wherein, The step of obtaining the additive stress field by obtaining the geometric matrix that converts the element node displacement into node strain according to the structural element is specific to the heat balance equation of each element, and the expression is as follows: {dF} e +{dR} e =[K] e {dδ} e where {dF} e is the incremental element nodal load; {dR} e is the incremental element nodal force caused by temperature; [K] e is the element stiffness matrix; {dδ} e is the incremental element nodal displacement; Where: {dF} e +{dR} e =[K] e {dδ} e In the formula, [B] is the geometric matrix that converts the element node displacement into node strain, and the calculation expression is as follows: {dε} e = [B]{dδ} e By combining the above formulas, as the load is applied, the element node displacement amount is calculated, and then the geometric matrix [B] that converts the element node displacement into node strain is used to obtain the node strain, thereby obtaining the final stress field.

7. The method for predicting stress and deformation in the hybrid additive and subtractive manufacturing of thin-walled metal components according to claim 1, wherein In the step of extracting the additive simulation stress data loaded from the additive stress field according to all unit integration points of the structural unit, the stress state of a point in space is determined by 9 stress components. Based on the theorem of reciprocal shear stresses, the stress state of the corresponding unit point is determined by defining the normal stresses in 3 directions and the shear stresses in 3 directions of the unit integration point; extract the six-direction stresses σ x 、σ y 、σ z 、τ x 、τ y 、τ z at all unit integration points in the extracted result odb file, where the first three stresses respectively represent the normal stresses in three directions, and the last three items are shear stresses. The expression of the residual stress at the integration point is as follows:

8. The stress and deformation prediction method for the additive and subtractive composite manufacturing of thin-walled metal components according to claim 1, wherein In the step of using the constitutive equation to define the material constitutive properties and setting the number of steps and machining time of the milling process analysis, the Johnson-Cook constitutive equation is used to define the material constitutive properties. The expression of the Johnson-Cook constitutive equation is: Where: ε is the equivalent plastic strain; is the equivalent plastic strain rate; is the equivalent plastic strain rate and the reference plastic strain rate; T is the temperature of the cutting part of the workpiece; T r is the melting point of the material; T m is the ambient temperature; n is the strain hardening index; m is the thermal softening index; A is the yield strength; B is the hardening modulus; C is the strain rate hardening parameter.

9. The stress and deformation prediction method for the additive and subtractive composite manufacturing of thin-walled metal components according to claim 1, characterized in that In the step of setting the material failure criterion to simulate the milling process, the J-C damage model is used. The expression of the equivalent plastic strain at damage of the J-C damage model is as follows: In the formula: is the equivalent plastic strain of material failure; d1 - d5 are the failure parameters of the material at room temperature; η is the dimensionless deviator stress ratio; is the plastic strain rate; is the reference plastic strain rate; Set the slip and adhesion friction model existing between the rake face of the tool and the chip in actual milling, and the expression is as follows: where: τ f is the frictional stress; μ is the coefficient of friction; σ n is the contact direction stress; τ s is the shear stress; When using the solver to calculate the stress distribution and deformation of the specimen, ALE adaptive meshing is divided in the part that needs to be milled, allowing the mesh to be independently adjusted relative to the movement of the material.

10. A stress and deformation prediction system for additive and subtractive composite manufacturing of metal thin-walled components, characterized in that, It includes: A three-dimensional model establishment module for three-dimensional modeling of the metal thin-walled component specimen and the machining tool. A finite element software import module for importing the established three-dimensional model into the finite element software and completing the assembly of the metal thin-walled component specimen and the machining tool. A finite element software parameter setting module for establishing the thermo-elastoplastic constitutive equation of the additive process in the finite element software and setting the material properties of the metal thin-walled component specimen. A laser cladding process simulation module for using the finite element software to set up dead and live elements to simulate the behavior of material forming in the actual laser cladding process. A heat source movement path setting module for setting the movement path of the heat source between different cladding layers. Additive temperature field calculation and conversion module, which is used to calculate the additive temperature field, import the additive temperature field into finite element software and convert it into structural elements; Additive stress field acquisition module, which is used to obtain the geometric matrix that converts the nodal displacements of the elements into nodal strains according to the structural elements, and obtain the additive stress field; Stress data extraction and loading module, which is used to extract and load the additive simulation stress data from the additive stress field according to all the element integration points of the structural elements; Milling process setting module, which is used to define the material constitutive properties using the constitutive equation, and set the number of steps and processing time of the milling process analysis; Specimen stress distribution and deformation calculation module, which is used to set the material failure criterion to simulate the milling process, and use the solver to calculate the specimen stress distribution and deformation.

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