Crystal grain progressive rotation visualization method and system based on crystal plasticity finite element

Abstract

The invention belongs to the field of material plastic deformation, and particularly discloses a crystal grain progressive rotation visualization method and system based on a crystal plasticity finite element, and the method comprises the steps: constructing a crystal plasticity constitutive model, and employing an index method to describe the relation between a crystal grain Euler angle and a Miller index; a crystal plasticity finite element model is constructed, the crystal plasticity finite element model comprises a plurality of crystal grains with random orientation, and deformation of each crystal grain is controlled by a crystal plasticity constitutive model; performing contact constraint on the crystal plasticity finite element model through a mold in Abaqus; performing multidirectional compression simulation on the crystal plasticity finite element model to reflect a real multidirectional forging process; finite element grid node coordinates and Euler angle data of a concerned observation surface in the crystal plasticity finite element model are obtained, an EBSD interaction file is constructed, then an IPF graph is drawn, and grain progressive rotation visualization is achieved. According to the invention, dynamic simulation and visual analysis of crystal orientation in the multidirectional forging process are realized, and a grain progressive rotation mechanism is revealed from a microscopic scale.

Description

Technical Field

[0001] The present invention belongs to the field of material plastic deformation, and more specifically, relates to a method and system for visualizing progressive rotation of grains based on crystal plastic finite element. Background Art

[0002] Crystal plasticity theory is a method based on describing the physical mechanism of material deformation at the microscale. In this method, the group dislocation motion in the slip system is represented as a continuous plastic shear strain, thereby combining the continuum theory with the discrete crystal motion to quantify the deformation of the metal. Crystal plasticity theory is widely used to understand and predict the potential microstructural evolution of crystalline materials and the anisotropic stress-strain response associated with large plastic strains, and has important applications in mechanics and materials science research.

[0003] The crystal plasticity finite element method (CPFEM) has developed rapidly in recent years by combining crystal plasticity theory with the finite element method. By introducing parameter information such as grain size, grain number, crystal anisotropic elastic modulus, grain orientation, slip system and hardening modulus, the crystal unit is divided into small units, and macro-micro coupling is achieved. It can accurately simulate the stress-strain distribution, texture evolution, grain distortion and slip system initiation of crystals during plastic deformation. It can also predict the mechanical properties of face-centered cubic, body-centered cubic and hexagonal close-packed crystals during plastic processing deformation such as tension, compression, rolling and stamping. The crystal plasticity finite element method can explain the inhomogeneous deformation behavior from the perspective of microscopic slip system and is suitable for multi-directional forging mechanism analysis. However, conventional crystal plasticity models, such as the RVE model, can usually only achieve tension and compression simulation of small deformations. Inhomogeneous deformation easily leads to local distortion of the finite element mesh, and it is usually difficult to apply to large deformation processes. Constructing a crystal plasticity model suitable for multi-directional cyclic deformation is of great significance for its application in the fields of large deformation and multi-pass deformation and for revealing the dynamic evolution of grain orientation during multi-directional forging.

[0004] In addition, electron backscatter diffraction (EBSD) is an advanced technology used in materials science research. It obtains the crystal structure and orientation information of the sample through the interaction between the backscattered electrons in the scanning electron microscope and the sample lattice. The combination of crystal plasticity finite element and electron backscatter diffraction technology provides a powerful tool for research in the field of materials science, especially in simulating the microstructure and performance changes of materials. By combining crystal plasticity finite element and EBSD technology, dynamic simulation and visual analysis of material microstructure and performance changes can be achieved. At present, the processing method combining the two technologies is mostly to initialize the crystal plasticity model with the grain orientation and morphology data obtained in EBSD. There has been no in-depth study on the analysis of the results after crystal plasticity simulation, especially the conversion of it into dynamic visualization EBSD results. Summary of the invention

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a method and system for visualizing progressive grain rotation based on crystal plasticity finite element, which aims to realize dynamic simulation and visual analysis of crystal orientation in multi-directional forging process and reveal the mechanism of progressive grain rotation from a microscopic scale.

[0006] To achieve the above object, according to one aspect of the present invention, a method for visualizing the progressive rotation of grains based on crystal plasticity finite element is proposed, comprising the following steps:

[0007] A crystal plasticity constitutive model is constructed, wherein an index method is used to describe the relationship between the grain Euler angle and the Maitreya index, wherein the grain Euler angle is used to represent the grain orientation;

[0008] A crystal plasticity finite element model is constructed, wherein the crystal plasticity finite element model includes a plurality of randomly oriented grains, and the deformation of each grain is controlled by the crystal plasticity constitutive model; and contact constraints are applied to the crystal plasticity finite element model through a mold in Abaqus;

[0009] Multi-directional compression simulation is performed on the crystal plasticity finite element model to reflect the real multi-directional forging process;

[0010] The spatial coordinates and Euler angle data of the finite element mesh nodes of the observation surface of interest in the crystal plasticity finite element model are obtained and constructed as an EBSD interaction file; the IPF diagram is drawn based on the EBSD interaction file to realize the visualization of the progressive rotation of the grains.

[0011] As a further preferred embodiment, an exponential method is used to describe the relationship between the grain Euler angle and the Maitreya index, and the expression is:

[0012]

[0013] Where Θ is the Euler angle matrix, Φ, They respectively represent the angles of rotation of the crystal along the normal direction, new rolling direction, and new normal direction of the sample reference coordinate system, and u, v, w, h, k, and l are the Maitreya indices.

[0014] As further preferred, the expression of shear slip rate in the crystal plasticity constitutive model is:

[0015]

[0016] in, is the shear slip rate of the αth slip system, m is the rate sensitivity index, τ α is the critical decomposed shear stress of the αth slip system, sgn is the sign function, is the reference shear slip rate, g αis the slip resistance of the αth slip system.

[0017] As a further preferred embodiment, the expression of the sliding resistance change rate in the crystal plasticity constitutive model is:

[0018]

[0019] in, is the slip resistance change rate of the αth slip system, is the shear slip rate of the βth slip system, h αβ is the hardening modulus of slip.

[0020] As further preferred, the calculation formula of the hardening modulus of slip is:

[0021]

[0022] Among them, h0 is the fitting coefficient, h αβ is the hardening modulus, δ αβ is the Kronecker delta function, a h is the hardening index, g s is the saturation value of sliding resistance, g β is the slip resistance of the βth slip system, and q represents the interaction strength ratio between slip systems.

[0023] As a further preferred embodiment, the crystal plasticity finite element model is subjected to contact constraints by means of a mold, specifically:

[0024] According to the volume invariance principle, two adjacent sides of the crystal plasticity finite element model are contact constrained by two mutually perpendicular molds; and symmetric constraints are applied to the other two sides of the mold to prevent the grains from moving to these two sides.

[0025] As a further preferred embodiment, a multi-directional compression simulation is performed on the crystal plasticity finite element model, specifically:

[0026] The crystal plasticity finite element model is subjected to two cycles of loading; one cycle of loading is: two adjacent sides of the crystal plasticity finite element model are subjected to compression simulations respectively and successively through two molds.

[0027] As a further preferred embodiment, a Gleeble thermal simulation experiment is performed on a standard hot compression sample in advance to obtain a true stress-strain curve, and the crystal plasticity constitutive model parameters are calibrated based on the true stress-strain curve.

[0028] As a further preferred embodiment, the EBSD interaction file is plotted into an IPF map by using the Mtex toolkit in MATLAB and large and small angle grain boundaries are added to the IPF map.

[0029] According to another aspect of the present invention, a system for visualizing progressive rotation of grains based on crystal plasticity finite element is provided, comprising a processor for executing the method for visualizing progressive rotation of grains based on crystal plasticity finite element.

[0030] In general, the above technical solution conceived by the present invention has the following technical advantages compared with the prior art:

[0031] 1. The present invention constructs a multi-directional forging crystal plasticity finite element model through a die contact constraint method, which can realize multi-directional compression simulation with large deformation, and then extracts the node space coordinates and Euler angle data of the observation surface of interest based on the calculation results of the model. Combined with the EBSD technology, dynamic simulation and visualization analysis of the crystal orientation in the multi-directional forging process are realized, which can reveal the progressive rotation mechanism of grains from a microscopic scale, providing an important reference for materials science research and engineering design and manufacturing.

[0032] 2. The present invention solves the problem that the crystal plasticity model is prone to uneven deformation and grid distortion during large deformation and cyclic deformation: the deformation of a conventional crystal plasticity model usually cannot exceed 20%. The present invention limits the large deformation of local grains through a die contact constraint method, ensuring that the overall deformation of the model can reach 30% per pass, and carries out four-pass cyclic compression simulation, reflecting the real multi-directional forging process.

[0033] 3. The present invention solves the problem of visualization of the dynamic evolution of grain orientation in crystal plasticity finite element calculations: crystal plasticity finite element can calculate grain orientation, but cannot visualize and analyze the grain orientation according to the simulated material phase components; the present invention converts finite element node data into coordinate point data of an EBSD format file, and further converts it into a standard IPF diagram in the format of the simulated material phase components through the Mtex toolkit, and draws large and small angle grain boundaries, thereby realizing dynamic visualization simulation of EBSD results under arbitrary crystal plastic deformation.

[0034] 4. The present invention is applicable to a wide range of processing technologies and materials: For any crystal plasticity constitutive model with Euler angle calculation function, the present invention is applicable to all its deformation conditions and processing technologies, and the crystal plasticity simulation results of any metal material can be processed and converted. A series of data mapping methods that can be implemented in experimental EBSD data, such as crystal orientation and texture evolution, can all be implemented under the simulated EBSD data converted by the present invention.

[0035] 5. The analysis results of the present invention are scientific and accurate, the storage volume is small, and the pictures are beautiful: the observation surface at any deformation time can be selected, which is convenient; in addition, compared with hundreds of thousands or millions of data points of conventional experimental EBSD data, the EBSD data converted from grid nodes in the present invention usually only requires a few thousand data points to draw an IPF map with uniform color block distribution, clear grain orientation, and clearly visible grain boundaries of large and small angles. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of a method for visualizing progressive rotation of grains based on crystal plasticity finite element according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of crystal plasticity model parameter calibration according to an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of mold contact constraints and loading conditions according to an embodiment of the present invention;

[0039] Figure 4 This is a data diagram of polycrystalline nodes arranged in EBSD format according to an embodiment of the present invention;

[0040] Figure 5 This is an IPF diagram of progressive rotation of grain orientation based on multi-directional forging according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0042] The embodiment of the present invention provides a method for visualizing the progressive rotation of grains based on crystal plasticity finite element, such as Figure 1 As shown, the following steps are included:

[0043] (1) Construct a crystal plasticity constitutive model and calibrate material parameters; the established crystal plasticity constitutive model includes the Euler angle calculation function, which is specifically coded in Abaqus-vuamt.

[0044] (1-1) The crystal plasticity constitutive model can describe the inhomogeneous deformation caused by the activation of different slip systems of the material, and study the influence of cumulative multidirectional deformation on the microstructural evolution mechanism from a mesoscopic scale.

[0045] The crystal plasticity constitutive model used, the shear slip rate is defined as:

[0046]

[0047] In the formula, is the shear slip rate of the αth slip system, m is the rate sensitivity index, τ α is the critical decomposed shear stress of the αth slip system, is the reference shear slip rate; g α is the slip resistance of the αth slip system, which is mainly caused by the fixed dislocation of the slip system. The slip resistance g α The rate of change is described by the following formula:

[0048] In the formula, h αβ is the hardening modulus of slip, which reflects the increase in slip resistance caused by the proliferation and interaction of dislocations during deformation. Represents the shear slip rate of the βth slip system. Hardening modulus h αβ The following formula is used to describe:

[0049]

[0050] Where h0 is the fitting coefficient; when α is equal to β, h αβ Convert to h αα , is the self-hardening modulus, when α is not equal to β, h αβ is the latent hardening modulus; δ αβ is the Kronecker delta function, a h is the hardening index. The sliding resistance gradually increases from the initial value g0 to the saturation value g s , g β Represents the slip resistance of the βth slip system. q represents the interaction strength ratio between slip systems, which is generally set to 1.0 for coplanar slip systems and 1.4 for non-coplanar slip systems. In order to calculate the evolution of grain orientation, the exponential method is used to describe the conversion relationship between the grain Euler angle and the Maitreya index, as shown in Formula 4.

[0051]

[0052] Where Θ is the Euler angle matrix, is the specific Euler angle, Φ, They represent the angles of rotation of the crystal along the normal, new rolling direction, and new normal direction of the sample reference coordinate system, respectively. u, v, w, h, k, and l are Maitreya indices, which represent the orientation of the crystal. The grain orientation is the relative position of the three crystal axes of the crystal in the sample coordinate system. The static position relationship of the crystal orientation can be determined by the Euler angle, that is, the angle relationship between the axes of the two coordinate systems and each other.

[0053] (1-2) Calibrate the parameters of the crystal plasticity constitutive model.

[0054] The above crystal plasticity constitutive model was encoded into Abaqus software through the Vuamt subroutine, and the Euler angles were represented by state variables. By comparing the simulation results with the experimental results, the material constants in the model were calibrated.

[0055] Specifically, in the experiment, a Gleeble thermal simulation experiment was carried out using a standard hot compression sample to obtain the true stress-strain curve at the temperature and strain rate corresponding to the multi-directional forging experiment. In the simulation, a hot compression sample model of the same size was established and the same boundary conditions were applied, the load and stroke were extracted, and the strain and stress were calculated. Then, the crystal plasticity constitutive model parameters can be calibrated by trial and error or enumeration method according to the degree of overlap between the simulation and experimental curves. The crystal plasticity model parameters to be calibrated include lattice constants, such as the BCC structure including C 11 , C 12 , C 44 , and other parameters included in the above constitutive model: m, g0, h0, g s 、a h .

[0056] (2) In Abaqus, a multi-directional forging crystal plasticity finite element model is constructed through die contact constraints, and the displacement boundary conditions of the die are applied.

[0057] (2-1) Constructing a crystal plasticity finite element model, the crystal plasticity finite element model includes a plurality of grains, which includes a plurality of finite element mesh nodes, giving each grain a random orientation, and using Euler angles Represents that the deformation of each grain is controlled by the crystal plasticity constitutive model.

[0058] Since the local deformation of the crystal plasticity model is very uneven under severe deformation, in order to avoid mesh distortion caused by excessive local deformation, the mold is used for contact constraint according to the volume invariance principle. In addition, the use of symmetric constraints on the blank can reduce the number of molds used. When one side of the mold is fed, the blank is compressed in that direction, and the other direction is stretched; at the same time, at the stretching end, the other side of the mold is synchronously started to move along the material flow direction, leaving sufficient space for metal plastic flow, and at the same time, it can block the local excessive flow of the blank, ensuring that the blank remains a regular body after deformation.

[0059] (2-2) Perform multi-directional compression simulation on the crystal plasticity finite element model: assign forced displacement boundary conditions and cyclic loading paths to the die, and preferably set the deformation of the die in each pass to 30% of the height of the blank in the current deformation direction. For a quarter-symmetrical quasi-three-dimensional deformation, only two-side dies need to be designed to achieve the above deformation process; preferably, compression and stretching are performed twice on each side, and a total of four multi-directional compression simulations are performed to reflect the real multi-directional forging process.

[0060] (3) In the obtained result file, all nodes of the plane of interest under any deformation state are selected, and the node spatial coordinates and Euler angle data are exported to form a file containing EBSD information.

[0061] (3-1) Before calculation, select coordinate (x, y, z) output and Euler angle in the software field variable output Output. After the calculation is completed, select all finite element mesh nodes of the observation surface of interest in a certain deformation state, and export the node space coordinates and Euler angle data. The selected observation surface can be the deformed section at any time and any calculation sub-step. It should be noted that if the plane of interest should be parallel to the plane of the three-dimensional coordinate system, for example, if the selected observation surface is parallel to the XY plane, the (x, y) coordinates are retained, and if the observation surface is parallel to the XZ plane, the (x, z) coordinates are retained.

[0062] (3-2) Constructing EBSD interaction files: In addition to node coordinates and Euler angles, the complete EBSD file information also contains information such as measurement deviation and Kikuchi bands. These data can be replaced by random numbers. After the information is supplemented, the EBSD interaction file is exported in the universal ctf format that can be recognized by the EBSD analysis software.

[0063] (4) Draw the IPF map and large and small angle grain boundaries based on the EBSD interaction file.

[0064] (4-1) Import the EBSD interaction file into the Mtex toolkit in MATLAB, select the material phase and the corresponding sample coordinate system, and generate built-in parameters.

[0065] (4-2) Use the built-in code of the Mtex toolkit to draw and generate IPF diagrams and large and small angle grain boundaries to realize EBSD data conversion and visualization simulation based on crystal plasticity. By adding large and small angle grain boundaries to the IPF diagram, we can more clearly see the influence of grain orientation evolution on the evolution of grain boundary density and dislocation density. Generally, large angle grain boundaries are grain boundaries with an angle of more than 10°, and small angle grain boundaries are grain boundaries with an angle of between 2° and 10°. Since the multi-directional forging process is simulated, during the crystal plastic deformation, the Euler angle orientation of the grain changes continuously with the deformation. After the deformation is completed, the IPF diagram drawn can reveal the mechanism of progressive rotation of grain orientation under cumulative multi-directional deformation from a microscopic scale.

[0066] The following are specific embodiments:

[0067] A crystal plasticity constitutive model is established, which should have the function of calculating Euler angles and be encoded into the Abaqus-vuamt subroutine. The parameters of the crystal plasticity constitutive model are calibrated according to the matching degree between experimental data and simulation data.

[0068] In the experiment, a standard hot compression sample (8×12 mm cylinder) was used to carry out a thermal simulation experiment, and the temperature was 1150°C and the strain rate was 0.1s -1 In the simulation, a cylindrical model of the same size is established and the same boundary conditions are applied. The load and stroke are extracted, and the strain and stress are calculated, such as Figure 2 The determined parameters of the studied Ti-6554 alloy are shown in Table 1.

[0069] Table 1 Crystal plasticity model parameters of as-cast Ti-6554 alloy

[0070]

[0071] Based on the ABAQUS dynamics module, the VUAMT crystal plasticity subroutine is called. A multi-directional forging crystal plasticity finite element model with die contact constraints is established. It is a quasi-3D model containing two-side dies and 9 grains. Each grain is assigned different initial material parameters and Euler angles. The model is designed as a square plate with a side length of 6 mm, a thickness of 0.4 mm and four layers of mesh. A quarter-symmetric boundary condition is established, and the surface marked with the support symbol is the symmetry surface. Specifically, Figure 3 As shown, molds (long pressing plates) are set on both sides of the blank (polycrystalline square plate), and the two molds are respectively set along the X direction and Y direction perpendicular to each other, and the molds are movable; at the same time, symmetry constraints are adopted, that is, the two sides of the model without molds are equivalent to being blocked by supports, so that the grains cannot move in these two directions.

[0072] It is defined that compression along the X and Y axes is one cycle loading, and two cycles of loading are performed in total. The amount of compression in each pass is 30% of the length of the blank in the current direction. Two cycles of loading are performed, that is, 4 compressions are accumulated. First, in step 1, mold X compresses the blank by 1.8mm along the +X direction. According to the principle of constant volume, mold Y is synchronously extended by 2.57mm along the +Y direction. In step 2, mold Y compresses the blank by 2.57mm along the -Y direction, and the mold is synchronously extended by 1.8mm along the -X direction. At this time, a loading cycle is completed, and the mold and the blank return to their initial positions; then the next cycle loading is performed on this basis. The mold compression distance and displacement path of steps 3 and 4 are the same as those of steps 1 and 2.

[0073] After calculating the above model and obtaining the result file, select the plane node (1 to n) set of interest. Export the plane coordinates and Euler angles of the node set The data is exported in a common interactive format that can be recognized by EBSD analysis software. The core data includes the phase composition, node coordinates and Euler angle data of the material. Other unknown information such as measurement deviation and Kikuchi band are filled with random numbers. The filled interactive file is as follows: Figure 4 shown.

[0074] The interactive file is read through the MATLAB software Mtex toolkit, the material phase and the corresponding sample coordinate system are selected, and the built-in parameters are generated. The toolkit code is used to fill the color block according to the node Euler angle orientation to generate the IPF map and grain boundary, such as Figure 5 shown. Figure 5 The results of grain deformation and orientation evolution of four passes are included, indicating that the EBSD data conversion and grain orientation visualization simulation based on the crystal plastic deformation results are realized through the above method, and the progressive rotation mechanism of grains is revealed from the microscopic scale under the multi-directional forging model.

[0075] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for visualizing the progressive rotation of grains based on crystal plasticity finite element, characterized in that: The steps include: A crystal plasticity constitutive model is constructed, wherein an index method is used to describe the relationship between the grain Euler angle and the Maitreya index, wherein the grain Euler angle is used to represent the grain orientation; A crystal plasticity finite element model is constructed, wherein the crystal plasticity finite element model includes a plurality of randomly oriented grains, and the deformation of each grain is controlled by the crystal plasticity constitutive model; and contact constraints are applied to the crystal plasticity finite element model through a mold in Abaqus; Multi-directional compression simulation is performed on the crystal plasticity finite element model to reflect the real multi-directional forging process; The spatial coordinates and Euler angle data of the finite element mesh nodes of the observation surface of interest in the crystal plasticity finite element model are obtained and constructed as an EBSD interaction file; the IPF diagram is drawn based on the EBSD interaction file to realize the visualization of the progressive rotation of the grains.

2. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 1, characterized in that: The index method is used to describe the relationship between the grain Euler angle and the Miller index, and the expression is: Where Θ is the Euler angle matrix, Φ, They respectively represent the angles of rotation of the crystal along the normal direction, new rolling direction, and new normal direction of the sample reference coordinate system, and u, v, w, h, k, and l are the Maitreya indices.

3. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 1, characterized in that: The expression of shear slip rate in the crystal plasticity constitutive model is: in, is the shear slip rate of the αth slip system, m is the rate sensitivity index, τ α is the critical decomposed shear stress of the αth slip system, sgn is the sign function, is the reference shear slip rate, g α is the slip resistance of the αth slip system.

4. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 3, characterized in that: The expression of the sliding resistance change rate in the crystal plasticity constitutive model is: in, is the slip resistance change rate of the αth slip system, is the shear slip rate of the βth slip system, h αβ is the hardening modulus of slip.

5. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 4, characterized in that: The calculation formula of the hardening modulus of the slip is: Among them, h0 is the fitting coefficient, h αβ is the hardening modulus, δ αβ is the Kronecker delta function, a h is the hardening index, g s is the saturation value of sliding resistance, g β is the slip resistance of the βth slip system, and q represents the interaction strength ratio between slip systems.

6. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 1, characterized in that: The crystal plasticity finite element model is contact constrained by the mold, specifically: According to the volume invariance principle, two adjacent sides of the crystal plasticity finite element model are contact constrained by two mutually perpendicular molds; and symmetric constraints are applied to the other two sides of the mold to prevent the grains from moving to these two sides.

7. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 6, characterized in that: The crystal plasticity finite element model is subjected to multi-directional compression simulation, specifically: The crystal plasticity finite element model is subjected to two cycles of loading; one cycle of loading is: two adjacent sides of the crystal plasticity finite element model are subjected to compression simulations respectively and successively through two molds.

8. The method for visualizing the progressive rotation of grains based on crystal plasticity finite element as claimed in claim 1, characterized in that: A Gleeble thermal simulation experiment is carried out on the standard hot compression sample in advance to obtain the true stress-strain curve, based on which the parameters of the crystal plasticity constitutive model are calibrated.

9. The method for visualizing progressive grain rotation based on crystal plasticity finite element according to any one of claims 1 to 8, characterized in that: The EBSD interaction file was plotted into an IPF map using the Mtex toolkit in MATLAB and large and small angle grain boundaries were added to the IPF map.

10. A crystal plasticity finite element based grain progressive rotation visualization system, characterized in that: It comprises a processor, wherein the processor is used to execute the grain progressive rotation visualization method based on crystal plasticity finite element as described in any one of claims 1 to 9.

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