A method for quantitatively revealing a grain size deformation mechanism starting amount

Abstract

This invention discloses a method for quantitatively revealing the initiation amount of grain-scale deformation mechanisms, belonging to the field of microscopic plastic deformation and crystal plasticity finite element simulation technology. This method combines in-situ / quasi-in-situ electron backscattering diffraction characterization with crystal plasticity finite element simulation. It obtains accurate initial grain orientation distribution and grain morphology evolution information through experiments and incorporates it into the finite element model to achieve precise quantitative analysis of deformation mechanisms such as slip and twinning. Compared with traditional methods, this method overcomes the limitations of experiments in quantitatively characterizing the initiation amount of grain-scale deformation mechanisms, while also overcoming the problem of large errors in conventional simulation methods at the grain scale. Through the deep integration of experiments and simulations, this method significantly improves the accuracy of quantitative analysis of deformation mechanisms, providing strong technical support for the study of microscopic plastic deformation mechanisms.

Description

Technical Field

[0001] This invention relates to the field of microscopic plastic deformation and finite element simulation of crystal plasticity, specifically to a method for quantitatively revealing the initiation amount of grain-scale deformation mechanisms. Background Technology

[0002] The macroscopic mechanical properties of materials, such as strength, plasticity, and formability, are essentially determined by the initiation and evolution of their microscopic plastic deformation mechanisms (such as slip, twinning, and phase transformation).

[0003] Currently, research on the plastic deformation mechanism of materials mainly relies on two methods: experimental characterization and numerical simulation. In terms of experimental characterization techniques, advanced methods such as electron backscatter diffraction (EBSD), synchrotron X-ray diffraction, high-resolution transmission electron microscopy (HRTEM), and atomic force microscopy (AFM) can qualitatively reveal the initiation type of deformation mechanism. However, these methods can only qualitatively study the activation of deformation mechanisms and cannot quantitatively analyze the activation degree of each deformation mechanism and its contribution to material properties. As for numerical simulation methods, methods such as viscoplastic self-consistent model (VPSC) and crystal plasticity finite element method (CPFEM) can predict the initiation amount of deformation mechanisms. However, different grain orientations tend to initiate different deformation mechanisms, and due to differences in the strength and shape of each grain, there is a severe strain localization behavior at the grain scale. This leads to significant deformation inhomogeneity at the grain scale during plastic deformation. Simulations based on macroscopic deformation conditions often cannot accurately reflect the local deformation behavior at the grain scale, resulting in large errors in the predicted initiation amount.

[0004] This technological bottleneck severely restricts the quantitative study of deformation mechanisms at the grain scale, and also limits the in-depth understanding of the relationship between plastic deformation mechanisms and material mechanical and processing properties. Therefore, it is urgent to develop a quantitative method that can combine real experimental data with high-precision simulations to accurately reveal the initiation behavior of deformation mechanisms at the grain scale and their impact on material properties. Summary of the Invention

[0005] To address the aforementioned shortcomings of existing technologies, the present invention aims to provide a method for quantitatively revealing the initiation amount of grain-scale deformation mechanisms, thereby solving the problem that existing technologies cannot accurately reflect local deformation behavior at the grain scale, leading to significant errors in the prediction results of the initiation amount.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for quantitatively revealing the initiation amount of grain-scale deformation mechanisms includes the following steps:

[0008] (1) According to the experimental requirements, cut in-situ / quasi-in-situ samples, then grind each surface corresponding to the area to be deformed of the sample flat, and according to the experimental requirements, select a certain surface corresponding to the area to be deformed of the sample as the observation surface, and polish the observation surface.

[0009] (2) Select a scanning area on the sample observation surface, use EBSD to scan the scanning area, and collect the initial state grain orientation distribution data of the scanning area;

[0010] (3) The sample is subjected to several plastic deformation treatments. After each plastic deformation, the scanning area described in step (2) is scanned again using EBSD to obtain the grain orientation distribution data of different deformation morphologies in the scanning area.

[0011] (4) Noise reduction and grain division are performed on the grain orientation distribution data of the initial state and different deformation states to determine the grain boundary distribution and the average orientation of each grain;

[0012] (5) Derive the average orientation and position distribution information of the initial state grains; the position distribution information is arranged in a matrix dataset containing several identical cells by the grain number, the same grain number represents the same grain, the size of the matrix dataset is the same as the size of the scanning area, and the side length of each cell in the matrix dataset is the same as the scanning step length of EBSD in step (2);

[0013] (6) Process the grain orientation distribution data of different deformation morphologies to preserve the initial state grain boundaries, and use the tri-point grain boundary as a feature point to record the coordinates of the tri-point grain boundary of the initial state and different deformation morphologies.

[0014] (7) Match the coordinates of the three-point grain boundary of the initial state and the grains with different deformation forms, calculate the displacement of the three-point grain boundary of the grains with different deformation forms relative to the corresponding initial state grain three-point grain boundary, and derive the coordinate position of the three-point grain boundary of the initial state grain and the displacement of the three-point grain boundary of the grains with different deformation forms relative to the corresponding initial state grain three-point grain boundary.

[0015] (8) Use finite element software to build a three-dimensional finite element model according to the size of the scanning area described in step (2), and divide the surface of the finite element model into several finite element elements of the same size, wherein the size of the finite element elements is the same as that of the cells in the matrix dataset;

[0016] (9) Overlap the matrix dataset with grain numbers arranged in step (5) with the finite element model. After overlapping, set the finite element elements with the same grain number as a set to obtain several sets. Then, assign material properties to these sets based on the average orientation of the corresponding initial grains to construct a finite element model based on the real microstructure.

[0017] (10) Use the coordinate position of the three-point grain boundary of the initial state grain in step (7) to query the corresponding element node in the finite element model, and assign the displacement of the grains with different deformations relative to the initial state grain to the corresponding element node.

[0018] (11) Submit the finite element model obtained in step (10) in the finite element software for calculation. Select the activation amount of each deformation mechanism in the calculation result file to obtain the cumulative shear strain distribution map of each deformation mechanism under different strain. The activation amount of each deformation mechanism at the grain scale can be read from the obtained distribution map.

[0019] Furthermore, in step (4), the grain division is carried out based on a grain boundary orientation difference of 10 degrees.

[0020] Furthermore, the EBSD scanning parameters are the same in steps (2) and (3).

[0021] Furthermore, in step (3), the plastic deformation includes stretching, compression, bending, or torsion.

[0022] Furthermore, in step (1), the sample is a polycrystalline material.

[0023] Furthermore, in step (7), the three-point grain boundary coordinate matching method includes manual matching, matching based on shape context method or Hungarian algorithm code writing.

[0024] Furthermore, in step (7), after matching, the triangular grain boundaries of the initial state and different deformed grains are centered, and then the displacement of the triangular grain boundaries of different deformed grains relative to the corresponding initial state grain triangular grain boundaries is calculated. Through centering, the overall morphology of the deformed grains can be roughly in the original position, making it easier for researchers to observe.

[0025] Furthermore, the centering process involves overlapping the triangular grain boundary distribution maps of the initial state and grains with different deformation forms, and then using rigid body rotation and translation to bring the coordinates of the triangular grain boundaries of the initial state and grains with different deformation forms closer together as a whole. By using rigid body rotation and translation, the relative displacement of the sample before and after deformation can be changed without affecting the strain distribution (i.e., without affecting the relative positional relationship of the triangular grain boundaries in the same state).

[0026] Furthermore, in step (8), the finite element software includes ABAQUS, ANASYS, or DEFORM.

[0027] Furthermore, the deformation mechanism includes one or more of slip, twinning, or phase transition.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] This invention provides an innovative method for quantitatively studying the initiation amount of grain-scale deformation mechanisms by deeply integrating in-situ / quasi-in-situ electron backscatter diffraction (EBSD) experiments with crystal plasticity finite element simulation (CPFEM). Compared with conventional experimental methods, this invention can not only directly obtain the quantitative initiation amount of various deformation mechanisms (such as slip, twinning, and phase transformation), but also construct a finite element model by introducing real grain deformation data (such as grain orientation and triple grain boundary displacement). This fully considers the non-uniformity of grain-scale deformation and can more realistically reflect the deformation behavior at the grain scale. It provides reliable quantitative support for the study of microscopic deformation mechanisms, solves the problem that existing technologies cannot accurately reflect the local deformation behavior at the grain scale, resulting in large errors in the prediction of initiation amount. This provides a high-precision theoretical basis for the optimized design of material mechanical properties and processing performance, and has important scientific significance and application value. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating the overall process of the method of the present invention.

[0031] Figure 2 The grain orientation distribution diagrams are shown for the initial state (a) and the modified state (b) in the embodiments of the present invention;

[0032] Figure 3 This is a schematic diagram of the three-pointed grain boundary matching in an embodiment of the present invention (a: initial state, b: transformed state, c: matching relationship, d: displacement modulus).

[0033] Figure 4 The following are schematic diagrams of the finite element model and the three-pointed grain boundary displacement loading in the embodiments of the present invention: (a) Finite element model of the actual microstructure, (b) Schematic diagram of the actual three-pointed grain boundary displacement loading.

[0034] Figure 5 The cumulative shear strain of each deformation mechanism at 3% strain in the example are: (a) basal slip, (b) cylindrical slip, (c) conical slip, and (d) tensile twinning.

[0035] Figure 6 The following are comparative analysis figures of the results of the method of the present invention (a, b) and the experimental results of the prior art (c, d) in the embodiments: (a) Distribution of basal slip shear strain obtained by the method of the present invention, (b) Identification results of basal slip variants of grains within the white box in (a) obtained by the method of the present invention, (c) Identification results of slip traces in the scanning image of the in-situ experimental results of the prior art, and (d) Identification results of basal slip variants of grains within the white box in (a) obtained by the experimental results of the prior art. Detailed Implementation

[0036] The specific embodiments of the present invention will be described in further detail below with reference to specific examples. Example

[0037] This embodiment provides a method for quantitatively studying the initiation amount of grain-scale deformation mechanisms. Taking the study of the deformation mechanism initiation during the stretching process of AZ31 magnesium alloy hot-rolled plate along the rolling direction as an example, the specific implementation of the invention is described in detail. The flowchart of the method implementation is as follows: Figure 1 As shown, it includes the following steps:

[0038] S1. Experimental Procedure

[0039] (1) Cutting samples: In-situ tensile samples were cut from AZ31 magnesium alloy rolled plates; the gauge length of the tensile sample was 27 mm × 3 mm × 2 mm, and the tensile deformation direction was consistent with the rolling direction of the rolled plate.

[0040] (2) Polishing the sample: Polish each surface corresponding to the area to be deformed of the tensile sample to ensure that each surface corresponding to the area to be deformed is flat and smooth; then, according to the experimental needs, select a certain surface (the side with the larger area) corresponding to the area to be deformed of the sample as the observation surface, and perform electrolytic polishing on the observation surface so as to obtain good EBSD characterization results in the future; the polishing fluid is commercial ACII polishing fluid, and the polishing parameters are: voltage 20V; temperature -20℃. o C; Polishing time 90 s. The larger side was chosen as the observation surface mainly because the tensile sample is thin and prone to necking during deformation. Its side (smaller side) will deform drastically and show obvious pits during the test. In contrast, the front side (larger side) of the tensile sample deforms more uniformly.

[0041] (3) Initial state EBSD calibration: The sample is installed on the in-situ stretching stage, the scanning area is selected on the sample observation surface, and the scanning area is scanned by EBSD to collect the initial state grain orientation distribution data of the scanning area; the EBSD scanning parameters are: scanning step size is 1 μm, and the scanning area is 300 μm × 300 μm.

[0042] (4) Plastic deformation: The sample is subjected to tensile deformation, with the tensile direction consistent with the rolling direction of the sheet, and the tensile rate is 10. -3 mm / s, with a strain of 3%.

[0043] (5) EBSD calibration of deformed morphology: The observation surface is scanned again using EBSD, and the grain orientation distribution data of the deformed morphology is collected when the strain is 3%; the scanning area and scanning parameters are the same as in step (3). Although it has undergone stretching deformation, the change caused by stretching is very small. Therefore, the change in the area of ​​the original scanning area caused by stretching is negligible. The scanning area in this step is still the same as in step (3).

[0044] S2, Data Processing Flow

[0045] (1) Use the MTEX ​​toolbox of MATLAB to denoise the grain orientation distribution data of the initial state and the transformed state, and then divide the grains according to the standard of 10 degrees of grain boundary orientation difference to determine the grain boundary distribution and the average orientation of each grain.

[0046] Figure 2 The diagram shows the grain orientation distribution in the initial and modified states, from... Figure 2 It can be seen that the sample exhibits a typical equiaxed grain structure, with different orientation relationships among the grains. Trifid grain boundaries are formed at the intersection of three grains, and the relative positions of the trifid grain boundaries and grains remain unchanged before and after deformation. In addition, twins are formed within some grains after plastic deformation, and new trifid grain boundaries are also generated.

[0047] (2) Export the average orientation and grain distribution information of the 128 grains in the initial state from the MATLAB software to a txt file respectively; wherein, the average orientation of the grains is represented by Euler angles, and the grain distribution information is represented by a 300 × 300 matrix dataset with grain numbers arranged, the same grain number represents the same grain, and the size of the matrix dataset is the same as the size of the scanning area.

[0048] (3) Merge the twins of the deformed grains with the parent grains to avoid creating new triplet grain boundaries. Use MATLAB software to export the coordinates of the triplet grain boundaries of the initial state and the deformed grains. The merging method can be to manually delete the generated twins directly in MATLAB software, or to write a small program, embed it in MATLAB software, and merge it through program execution; or other existing merging methods can be used.

[0049] Figure 3 (a) and (b) are the distribution diagrams of the three-pointed grain boundaries of the initial and modified grains, respectively.

[0050] (4) Use MATLAB software to write code based on the shape context method to realize the corresponding matching of the initial state and the deformed state of the three-point grain boundaries. In specific implementation, the corresponding matching of the initial state and the deformed state of the three-point grain boundaries can also be realized by manual matching. The specific operation is as follows: First, mark the coordinate value of each three-point grain boundary in the distribution map of the initial state and the deformed state three-point grain boundaries. Then, overlap the three-point grain boundaries in the two states. Since the relative position relationship of the grains in the sample does not change before and after the sample is deformed, the matching relationship of each three-point grain boundary can be identified by the naked eye after overlapping, so as to obtain the corresponding relationship of the coordinates of the three-point grain boundaries before and after deformation.

[0051] The matching relationship between the initial state and the modified state of the three-pointed grain boundary is as follows: Figure 3As shown in (c), most of the initial state triangular grain boundaries (red circles) are matched one-to-one with the transformed triangular grain boundaries (blue squares) (the matching relationship is represented by a short green line), indicating that the correct matching relationship was obtained through the above process.

[0052] (5) Center the initial and deformed triangular grain boundaries, and calculate the displacement of the deformed triangular grain boundary based on the coordinate positions of the initial and deformed triangular grain boundaries after processing. Then, derive the coordinate positions of each triangular grain boundary in the initial state and the displacement of the triangular grain boundary caused by deformation. The centering method is as follows: after overlapping the distribution maps of the initial and deformed triangular grain boundaries, align the initial and deformed triangular grain boundaries as much as possible through rigid body rotation and translation.

[0053] Figure 3 (d) is the displacement modulus caused by deformation, derived from... Figure 3 (d) It can be seen that the displacement of each triplet grain boundary can be obtained through the above process, and the displacement of each triplet grain boundary is significantly different. Conventional finite element simulation methods are difficult to accurately simulate this phenomenon.

[0054] S3. Crystal Plasticity Finite Element Model Construction and Simulation Process

[0055] (1) Establish a three-dimensional crystal plastic finite element model (size is 300 μm × 300 μm × 3 μm) in ABAQUS finite element software and divide it into C3D8 elements with a side length of 1 μm.

[0056] (2) Based on the initial state grain distribution information derived in step S2, the finite element elements are divided into 128 element sets; and 128 material properties are established based on the average orientation of each initial state grain. Then, the material properties are assigned to the corresponding element sets to construct a finite element model based on the real microstructure. The specific implementation method for dividing the element sets is as follows: the 300*300 matrix dataset with grain numbers obtained in step S2-(2) is overlapped with the finite element model. After overlap, the finite element elements with the same grain number are set as a single element set, named the grain number, for a total of 128 element sets. The specific implementation method for establishing material properties based on the average orientation of the initial state grains is as follows: the material properties include grain orientation, elastic constant, deformation system shear plane and shear direction. Among them, only the grain orientation is different between different grains, and the other material parameters are consistent. The grain orientation is obtained in step S2-(2), and the other material parameters can be obtained from relevant literature. A set of grain orientations and other material parameters are integrated and input into the ABAQUS software to obtain the material properties of a single grain, named after its grain number. Then, the created material properties are copied sequentially, and the grain orientations are modified to obtain the material properties of another grain. In this way, a total of 128 grain material properties are generated. Finally, in the ABAQUS software, each material property is assigned to a set of grain units with the same grain number, thus completing the model establishment based on the actual microstructure.

[0057] Figure 4 (a) Finite element model of real microstructure, by Figure 4 (a) It can be seen that a finite element model consistent with the real microstructure was successfully established by the above method.

[0058] (3) Based on the initial state triple grain boundary coordinate information in steps S2-(5), find the corresponding triple grain boundary node in the finite element model, and assign the actual measured deformation triple grain boundary displacement to the node. In specific implementation, the search method is as follows: overlap the initial state triple grain boundary coordinate information map with the finite element model. After the overlap, the position corresponding to the initial state triple grain boundary on the finite element model is the corresponding node.

[0059] like Figure 4 As shown in (b), the finite element node displacement based on the actual triplet grain boundary displacement was successfully established, and different displacements were applied to each triplet grain boundary.

[0060] (4) Submit the complete crystal plastic finite element model with the UMAT subroutine for calculation. Select the activation amount of each deformation mechanism in the calculation result file to obtain the cumulative shear strain distribution map of each deformation mechanism under 3% strain. The activation amount of each deformation mechanism at the grain scale can be read from the distribution map. The UMAT subroutine can be a self-written UMAT subroutine or an open source UMAT subroutine in the prior art.

[0061] Figure 5 The cumulative shear strain distributions of four deformation mechanisms (basal slip, cylindrical slip, conical slip, and tensile twinning) are presented when the tensile strain is 3%. The figures show that plastic deformation is mainly dominated by basal slip, with its cumulative shear strain significantly higher than the other mechanisms. Simultaneously, a small amount of tensile twinning initiation is observed in some grain boundary regions, a result consistent with theoretical understanding and literature reports on the plastic deformation of magnesium alloys. Furthermore, the simulation results quantitatively reveal the non-uniformity of shear strain distribution at the grain scale in basal slip, reflecting the significant influence of grain orientation differences and local stress concentrations on the initiation of the deformation mechanism.

[0062] To further verify the accuracy of the method of the present invention, Figure 6 The simulation results of the method of the present invention were compared and analyzed with the results of conventional experiments (scanning electron microscopy (SEM)). Figure 6 (a) shows the simulated base slip shear strain distribution. Figure 6 (c) shows the slip trace identification results based on scanning electron microscopy (SEM). The experimental results show that basal slip is the dominant deformation mechanism, and the simulation results of this invention and conventional experimental results show a high degree of consistency in slip distribution: the large number of grains that initiate basal slip in the simulation are consistent with the conventional experimental results, and the shear strain distribution characteristics of the simulation results are consistent with the slip trace angle distribution observed in conventional experiments.

[0063] The basal plane slip has three slip systems, and because they share the same slip surface, their slip traces are morphologically indistinguishable. To further analyze the initiation of the slip variants, Figure 6 (b) and Figure 6 (d) respectively showed Figure 6(a) Simulation and conventional experimental results of slip variant identification for a single grain within the white box. Based on the lattice rotation analysis method with slip trace correction, the slip trace is first identified using SEM images to confirm that the grain has initiated basal plane slip. Then, three possible directions of basal plane slip orientation rotation are plotted according to the grain's average orientation, and superimposed analysis is performed in conjunction with the local orientation distribution. The results show that the grain simultaneously initiated basal plane slip variants with slip directions of [-2110] and [-12-10]. The results from conventional experiments and simulations are consistent, verifying that the method of this invention can not only accurately identify the deformation mechanism type but also precisely reveal the actually initiated slip variant.

[0064] In the embodiments, by comparing the results obtained by the method of the present invention with conventional experimental characterization data, a high degree of consistency was found between the two in terms of the type and distribution of deformation mechanism initiation, verifying the reliability of the method of the present invention in revealing the initiation amount of grain-scale deformation mechanisms. Furthermore, the method of the present invention combines the advantages of experimentation and simulation, providing a more reliable quantitative tool for the study of microscopic plastic deformation mechanisms. This method not only compensates for the shortcomings of traditional experimental methods in quantitative analysis but also overcomes the error problem caused by conventional numerical simulation methods neglecting the non-uniformity of grain-scale deformation. In summary, the method of the present invention, through the deep integration of experimentation and simulation, achieves the accurate revelation of the initiation amount of grain-scale deformation mechanisms, providing reliable technical support for the study of the microscopic mechanical behavior and performance optimization of materials.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit the technical solutions. Those skilled in the art should understand that any modifications or equivalent substitutions to the technical solutions of the present invention without departing from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A method for quantitatively revealing the initiation amount of grain-scale deformation mechanisms, characterized in that, Includes the following steps: (1) According to the experimental requirements, cut in-situ / quasi-in-situ samples, then grind each surface corresponding to the area to be deformed of the sample flat, and according to the experimental requirements, select a certain surface corresponding to the area to be deformed of the sample as the observation surface, and polish the observation surface. (2) Select a scanning area on the sample observation surface, use EBSD to scan the scanning area, and collect the initial state grain orientation distribution data of the scanning area; (3) The sample is subjected to several plastic deformation treatments. After each plastic deformation, the scanning area described in step (2) is scanned again using EBSD to obtain the grain orientation distribution data of different deformation morphologies in the scanning area. (4) Noise reduction and grain division are performed on the grain orientation distribution data of the initial state and different deformation states to determine the grain boundary distribution and the average orientation of each grain; (5) Derive the average orientation and position distribution information of the initial state grains; the position distribution information is arranged in a matrix dataset containing several identical cells by the grain number, the same grain number represents the same grain, the size of the matrix dataset is the same as the size of the scanning area, and the side length of each cell in the matrix dataset is the same as the scanning step length of EBSD in step (2); (6) Process the grain orientation distribution data of different deformation morphologies to preserve the initial state grain boundaries, and use the tri-point grain boundary as a feature point to record the coordinates of the tri-point grain boundary of the initial state and different deformation morphologies. (7) Match the coordinates of the three-point grain boundary of the initial state and the grains with different deformation forms, calculate the displacement of the three-point grain boundary of the grains with different deformation forms relative to the corresponding initial state grain three-point grain boundary, and derive the coordinate position of the three-point grain boundary of the initial state grain and the displacement of the three-point grain boundary of the grains with different deformation forms relative to the corresponding initial state grain three-point grain boundary. (8) Use finite element software to build a three-dimensional finite element model according to the size of the scanning area described in step (2), and divide the surface of the finite element model into several finite element elements of the same size, wherein the size of the finite element elements is the same as that of the cells in the matrix dataset; (9) Overlap the matrix dataset with grain numbers arranged in step (5) with the finite element model. After overlapping, set the finite element elements with the same grain number as a set to obtain several sets. Then, assign material properties to these sets based on the average orientation of the corresponding initial grains to construct a finite element model based on the real microstructure. (10) Use the coordinate position of the three-point grain boundary of the initial state grain in step (7) to query the corresponding element node in the finite element model, and assign the displacement of the grains with different deformations relative to the initial state grain to the corresponding element node. (11) Submit the finite element model obtained in step (10) in the finite element software for calculation. Select the activation amount of each deformation mechanism in the calculation result file to obtain the cumulative shear strain distribution map of each deformation mechanism under different strain. The activation amount of each deformation mechanism at the grain scale can be read from the obtained distribution map.

2. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (4), the grain division is performed based on a grain boundary orientation difference of 10 degrees.

3. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, The EBSD scanning parameters are the same in steps (2) and (3).

4. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (3), the plastic deformation includes stretching, compression, bending or torsion.

5. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (1), the sample is a polycrystalline material.

6. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (7), the three-point grain boundary coordinate matching method includes manual matching, matching based on shape context method or Hungarian algorithm code writing.

7. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (7), after matching, the three-point grain boundaries of the initial state and different deformed grains are centered, and then the displacement of the three-point grain boundaries of different deformed grains relative to the corresponding initial state grain three-point grain boundaries is calculated.

8. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 7, characterized in that, The centering process involves overlapping the triangular grain boundary distribution maps of the initial state and grains with different deformed forms, and then using rigid body rotation and translation to bring the coordinates of the triangular grain boundaries of the initial state and grains with different deformed forms closer together as a whole.

9. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, In step (8), the finite element software includes ABAQUS, ANASYS, or DEFORM.

10. The method for quantitatively revealing the initiation amount of grain-scale deformation mechanism according to claim 1, characterized in that, The deformation mechanism includes one or more of slip, twinning, or phase transition.

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