Slip transfer prediction method considering Taylor factor
By introducing Taylor factor information and a dual threshold criterion, and combining EBSD data with slip traces, the problem of insufficient accuracy and versatility in slip transfer prediction in existing technologies is solved, achieving higher prediction accuracy and robustness.
Patent Information
- Application Number
- CN202610115100.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-28
- Publication Date
- 2026-03-03
- Estimated Expiration
- 2046-01-28
AI Technical Summary
Existing slip transfer prediction methods have limited accuracy under different material systems and loading conditions, and fail to fully reflect the differences in the ease of deformation caused by grain orientation, resulting in insufficient prediction accuracy and versatility.
Taylor factor information is introduced. By jointly acquiring and registering the deformed EBSD data with grain boundary/slip traces, and combining the geometric compatibility of the slip system and the residual Burgers vector, slip pairs are classified using a dual threshold criterion (ΔM≤ΔM and ΔM>ΔM), and different prediction criteria are fitted within each classification.
It significantly improves the accuracy and engineering applicability of slip transfer prediction, enhances the reproducibility and portability of the method, and provides higher prediction accuracy and robustness.
Smart Images
Figure CN121601119A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of materials analysis technology, and in particular to a slip transfer prediction method that takes into account the Taylor factor. Background Technology
[0002] Plastic deformation of materials essentially originates from the movement of dislocations within crystals along specific slip systems. For polycrystalline metals, when dislocations move to grain boundaries, they may undergo cross-grain boundary slip propagation or be blocked at the grain boundaries. Slip propagation / blocking behavior directly affects key failure mechanisms such as deformation uniformity, strain localization, and crack initiation and propagation. Therefore, predicting slip propagation at grain boundaries has always been a core issue in materials analysis and strengthening design.
[0003] Existing studies mostly rely on electron backscatter diffraction (EBSD) to obtain information on grain orientation and grain boundary geometry, and combine this with imaging results of the surface morphology or slip traces after deformation to characterize cross-boundary slip behavior. To achieve prediction, existing studies have proposed two types of parameters to predict the slip propagation behavior of dislocations: (1) Luster–Morris geometric compatibility factor (2) Residual Burgers vector Due to the large This alters the structure and energy of grain boundaries, inducing strain accumulation and promoting the nucleation of microcracks at grain boundaries; therefore, a smaller residual Burgers vector favors slip transfer. However, depending on... and Threshold criteria often have limited predictive accuracy and poor versatility across different material systems and loading conditions; furthermore, relying solely on the geometric matching of slip pairs to activate slip systems cannot fully reflect the differences in deformation "ease" corresponding to grain orientation. On the other hand, the Taylor factor can reflect the overall grain's response to macroscopic stress under loading conditions, but existing slip propagation prediction methods do not introduce the Taylor factor difference (ΔM) between adjacent grains to characterize the inconsistency in mechanical response between grains on both sides. This inconsistency may alter the stress-strain distribution and dislocation accumulation at grain boundaries, thereby affecting whether slip can be successfully propagated across boundaries. Summary of the Invention
[0004] The purpose of this invention is to provide a slip transfer prediction method that considers the Taylor factor, while maintaining... While ensuring geometrical compatibility of the iso-slip system, Taylor factor information is introduced to differentiate slip transfer prediction strategies under different ΔM conditions. By jointly acquiring and registering EBSD data after deformation with grain boundary / slip traces, reliable labeling of slip transfer and slip blockage is achieved. Based on the classification, criteria are fitted separately to obtain higher prediction accuracy and better engineering applicability under different microstructures and loading conditions.
[0005] To achieve the above objectives, the present invention provides a slip-transfer prediction method considering Taylor factors, comprising the following steps: S1. Obtain EBSD data and corresponding grain boundary morphology after deformation, and extract slip transfer, slip blockage relationship and Euler angle parameters of grain pairs during actual stretching process; S2. Calculate the Taylor factor M of each grain under a given stress state and obtain the Schmidt factor. S3. Combine the slip trace and the Schmidt factor to determine the actual activated slip system and identify the slip system pair; S4. For candidate slip pairs between adjacent grains, calculate the geometric compatibility index, including the geometric compatibility factor. With residual Burgh's vector ; S5. Introduce Taylor factors and classify them according to the Taylor factor difference ΔM of the slip pairs; S6. Fit different slip transfer prediction criteria to the slip pairs of the classification to improve prediction ability.
[0006] Preferably, S1 specifically includes the following: S11. After tensile deformation, the sample is characterized by EBSD and Hough calibration is completed. The data is denoised using the confidence threshold. The grains are divided according to the orientation difference angle, and the grain number, average orientation and Euler angle are output. S12. High-resolution morphology imaging was performed on the tensile-deformed sample in the region consistent with the EBSD analysis, focusing on acquiring grain boundary morphology and slip traces to form joint grain boundary-slip trace data corresponding one-to-one with the EBSD grain pairs for subsequent analysis; imaging equipment included optical microscope, scanning electron microscope, confocal microscope, and atomic force microscope. S13. Compare the deformed surface morphology and slip trace images with the IPF diagram drawn by EBSD. For slip traces that are continuous across grain boundaries, they are determined to be "transmission" and slip traces that terminate at the boundary are determined to be "blockage". Then, they are associated with the corresponding grain pairs one by one.
[0007] Preferably, S2 specifically includes the following: S21. Based on the given stress state, convert the grain Euler angles into an orientation matrix; for the material crystal structure, enumerate candidate slip systems, calculate the Schmitt factor of each slip system, and sort them. S22. Under the applied load / strain conditions, determine the Taylor factor M of the grains to obtain the M value for each grain; calculate the value for adjacent grain pairs (G1, G2). For use in subsequent classification.
[0008] Preferably, the specific operation in S3 is as follows: the active slip surface is determined by matching the slip trace direction with the slip line direction predicted by crystal orientation; the slip direction with the largest Schmitt factor in the slip surface is selected as the actual active slip system.
[0009] Preferably, in S4, the geometric compatibility factor Calculated according to the Luster–Morris definition, the expression is: ; in for and The angle between them for and The angle between them , These are the sliding direction and the normal to the sliding surface, respectively. Residual Burgers vector The calculation expression is: .
[0010] Preferably, step S5 specifically includes the following steps: S51. Plot the distribution of the Taylor factor difference for the slip transfer pair and the Taylor factor difference for the slip blockage pair respectively. S52. Analyze the differences in Taylor factor distribution caused by slip transfer and slip blockage, analyze the differences in their central tendency, dispersion, peak position and overlapping interval, identify the ΔM value characteristics corresponding to slip transfer and slip blockage, and provide a basis for threshold selection; S53. Based on the analysis results in S52, set the Taylor factor difference threshold ΔM. And in subsequent processing, this threshold is kept unchanged, and all sliding pairs are processed according to ΔM≤ΔM. With ΔM>ΔM The data were divided into two categories for subsequent fitting of slip transfer prediction criteria.
[0011] Preferably, step S6 specifically includes the following steps: S61. For slip pairs of different classifications, respectively using the geometric compatibility factor... With residual Burgh's vector magnitude Using the characteristic quantity, the slip transfer criterion is fitted to establish a system based on ( , () represents the determination relation of the independent variable; S62. Set the slip transfer criterion: When > a and < b If the condition is met, it is determined to be slip transfer; otherwise, it is determined to be slip blockage. a, b The threshold parameter that needs to be determined; S63. Fit the classified data separately, and find the optimal parameter combination that satisfies the form of S62 within each dataset. a , b ); S64. Within each category, different ( a , b The combination of methods is used to evaluate the effectiveness, and the combination with the highest accuracy is selected as the final slip transfer criterion for the classification.
[0012] Therefore, the slip propagation prediction method considering Taylor factors described above, as used in this invention, has the following beneficial effects: 1) For the first time, the Taylor factor difference ΔM between adjacent grains is introduced into the slip transfer determination, which compensates for the shortcomings of relying solely on Taylor factor difference. and The limitations of geometric matching.
[0013] 2) Set the threshold ΔM based on ΔM By classifying the slip pairs and fitting criteria within each category, prediction accuracy is significantly improved.
[0014] 3) Establish an objective process of "ΔM distribution - difference analysis - threshold locking", and determine the fixed threshold ΔM by using the central tendency and overlapping interval of the two types of ΔM distributions: propagation and blocking. This improves the reproducibility and portability of the method.
[0015] 4) Propose > a and < b The dual threshold criterion can be optimized separately within different ΔM categories. a , b This enables higher overall prediction accuracy and robustness.
[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description
[0017] Figure 1 This is a flowchart of a method according to an embodiment of the present invention; Figure 2 This is an implementation architecture diagram of an embodiment of the present invention; Figure 3 These are the IPF diagrams and grain numbers of embodiments of the present invention; Figure 4 These are partial grain Euler angle data from embodiments of the present invention; Figure 5The images of grain boundaries / slip traces obtained in the same region in this embodiment of the invention only show the range of 2-3 grains; Figure 6 This is a histogram of the frequency distribution of Taylor factor difference for the slip transfer pair according to an embodiment of the present invention. Figure 7 This is a histogram of the frequency distribution of Taylor factor difference for the slip-blocking pair according to an embodiment of the present invention; Figure 8 This is a comparison diagram of the theoretical and actual slip surface traces according to an embodiment of the present invention. The selected range is... Figure 5 The area within the red box; Figure 9 This is a calculation of the slip pair in an embodiment of the present invention. With Δ b Screenshot of some data; Figure 10 This is the implementation result of the slip transfer prediction method in this embodiment of the invention. Detailed Implementation
[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.
[0019] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0020] Example 1 This invention provides a slip transfer prediction method considering Taylor factors, the process of which is as follows: Figure 1 , Figure 2 As shown, the basic idea is to use the traditional geometric compatibility factor. With residual Burgh's vector Based on this, the Taylor factor difference between adjacent grains is introduced. To characterize the difference in load response on both sides of the grain boundary; based on the registration of the deformed EBSD and slip traces, "transmission / blockage" samples are obtained, and the actual active slip system is determined and calculated under a given stress state. , , ΔM); Select the threshold ΔM based on ΔM Classify the samples, and within each category, use... > a and < b Double threshold optimization ( a , b This enables highly accurate and generalizable prediction of cross-grain boundary slip transfer.
[0021] First, let's explain some concepts that are similar in form: Slip system: A slip system is the basic unit of crystal slip deformation, composed of slip planes and slip directions on them, representing the possible spatial orientations that a crystal may choose during plastic deformation. Activation of a slip system will produce slip traces on the grain surface. If the slip traces can cross grain boundaries and enter adjacent grains, it is called slip transfer; if they are blocked at grain boundaries, it is called slip blockage.
[0022] Slip pairs: also known as slip transfer pairs or slip blocking pairs. During stretching, the relationship between two adjacent grains will eventually lead to two results: slip transfer and slip blocking. Therefore, these two grains and their relationship can be collectively referred to as slip pairs, specifically slip transfer pairs and slip blocking pairs. Slip system pair: After determining the actual active slip system of the grain through S3 below, the slip pair is described more specifically as a slip system pair. Compared with the slip pair, the slip system pair adds one piece of information, namely the actual active slip system of each grain.
[0023] The specific process of the method in this embodiment is as follows: Figure 1 , Figure 2 As shown, it includes the following steps: S1. Obtain EBSD data and corresponding grain boundary morphology after deformation, and extract slip transfer, slip blocking relationships, and Euler angle parameters of grain pairs during the actual tensile process; specifically including the following: S11. After tensile deformation, the sample is characterized by EBSD and Hough calibration is completed. The data is denoised using the confidence threshold. The grains are divided according to the orientation difference angle, and the grain number, average orientation and Euler angle are output. S12. High-resolution morphology imaging was performed on the tensile-deformed sample in the region consistent with the EBSD analysis, focusing on acquiring grain boundary morphology and slip traces to form joint grain boundary-slip trace data corresponding one-to-one with the EBSD grain pairs for subsequent analysis; imaging equipment included optical microscope, scanning electron microscope, confocal microscope, and atomic force microscope. S13. Compare the deformed surface morphology and slip trace images with the IPF diagram drawn by EBSD. For slip traces that are continuous across grain boundaries, they are determined to be "transmission" and slip traces that terminate at the boundary are determined to be "blockage". Then, they are associated with the corresponding grain pairs one by one.
[0024] The IPF diagrams, grain numbers, partial grain Euler angle data, and grain boundary / slip trace images of the same region obtained in this embodiment are as follows: Figures 3-5 As shown.
[0025] S2. Calculate the Taylor factor M for each grain under a given stress state and determine the Schmidt factor; specifically, this includes the following: S21. Based on the given stress state, convert the grain Euler angles into an orientation matrix; for the material crystal structure, enumerate candidate slip systems, calculate the Schmitt factor of each slip system, and sort them. S22. Under the applied load / strain conditions, determine the Taylor factor M of the grains to obtain the M value for each grain; calculate the value for adjacent grain pairs (G1, G2). For use in subsequent classification.
[0026] The statistical results calculated in this embodiment are as follows: Figures 6-7 As shown, 85.54% of the slip pairs have a Taylor factor difference of less than 0.6, while the Taylor factor difference of the slip blocking pairs shows a uniform distribution.
[0027] S3. Determine the actual active slip system by combining the slip trace and the Schmitt factor, and identify the slip system pair; specifically, match the slip trace direction with the slip line direction predicted by crystal orientation to determine the active slip surface; select the slip direction with the largest Schmitt factor from the slip surface as the actual active slip system. In this embodiment, the specific steps are as follows: Figure 8 As shown, the selected range is Figure 5 As shown in the red box, the four red lines represent four different slip surfaces, which are calculated. Compared with the traces of the actual sample, the red traces parallel to the traces of the actual grains are the actual activated slip surfaces.
[0028] S4. For candidate slip pairs between adjacent grains, calculate the geometric compatibility index, including the geometric compatibility factor. With residual Burgh's vector Geometric compatibility factor Calculated according to the Luster–Morris definition, the expression is: ; in for and The angle between them for and The angle between them , These are the sliding direction and the normal to the sliding surface, respectively. Residual Burgers vector The calculation expression is: The specific data used in this embodiment is as follows: Figure 9 As shown.
[0029] S5. Introduce Taylor factors and classify the slip pairs based on the Taylor factor difference ΔM; specifically, this includes the following steps: S51. Plot the distribution of the Taylor factor difference for the slip transfer pair and the Taylor factor difference for the slip blockage pair respectively. S52. Analyze the differences in Taylor factor distribution caused by slip transfer and slip blockage, analyze the differences in their central tendency, dispersion, peak position and overlapping interval, identify the ΔM value characteristics corresponding to slip transfer and slip blockage, and provide a basis for threshold selection; S53. Based on the analysis results in S52, set the Taylor factor difference threshold ΔM. And in subsequent processing, this threshold is kept unchanged, and all sliding pairs are processed according to ΔM≤ΔM. With ΔM>ΔM The data is divided into two categories for subsequent fitting of slip transfer prediction criteria. In this embodiment, the classification threshold ΔM is determined based on the results obtained in S2. The value is set to 0.6, and based on this, all slip pairs are divided into... and Two categories.
[0030] S6. Fit different slip transfer prediction criteria to the slip pairs of the classification to improve predictive power. Specifically, this includes the following steps: S61. For slip pairs of different classifications, respectively using the geometric compatibility factor... With residual Burgh's vector magnitude Using the characteristic quantity, the slip transfer criterion is fitted to establish a system based on ( , () represents the determination relation of the independent variable; S62. Set the slip transfer criterion: When > a and < b If the condition is met, it is determined to be slip transfer; otherwise, it is determined to be slip blockage. a , b The threshold parameter that needs to be determined; S63. Fit the classified data separately, and find the optimal parameter combination that satisfies the form of S62 within each dataset. a , b ); S64. Within each category, different ( a , b The combination of methods is used to evaluate the effectiveness, and the combination with the highest accuracy is selected as the final slip transfer criterion for the classification.
[0031] In this embodiment, for group 1: The fitting accuracy was 91.01%. >0.968589 and Values <0.187593 are considered "transmitted," otherwise "blocked." For group 2, The fitting accuracy was 96.85%. >0.888307 and Values <0.321873 are considered "transmitted," otherwise "blocked." The overall accuracy rate is 92.85%. (Details follow...) Figure 10 As shown.
[0032] Therefore, this invention employs the aforementioned slip propagation prediction method that considers the Taylor factor, incorporating the Taylor factor difference ΔM between adjacent grains into the slip propagation determination, thus overcoming the limitations of relying solely on... and Geometric matching limitations; setting a threshold ΔM based on ΔM By classifying the slip pairs and fitting criteria within each category, prediction accuracy is significantly improved. An objective process of "ΔM distribution - difference analysis - threshold locking" is established, and a fixed threshold ΔM is determined by utilizing the central tendency and overlap interval of the propagation / blocking ΔM distributions. To improve the reproducibility and portability of the method; to propose > a and < b The dual threshold criterion can be optimized separately within different ΔM categories. a , b This method achieves higher global prediction accuracy and robustness. It not only enhances the accuracy of slip transfer analysis, but also provides new ideas and tools for the field of materials science, with broad application prospects and engineering value.
[0033] 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 them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.
Claims
1. A slip transfer prediction method considering Taylor factors, characterized in that, Includes the following steps: S1. Obtain EBSD data and corresponding grain boundary morphology after deformation, and extract slip transfer, slip blockage relationship and Euler angle parameters of grain pairs during actual stretching process; S2. Calculate the Taylor factor M of each grain under a given stress state and obtain the Schmidt factor. S3. Combine the slip trace and the Schmidt factor to determine the actual activated slip system and identify the slip system pair; S4. For candidate slip pairs between adjacent grains, calculate the geometric compatibility index, including the geometric compatibility factor. With residual Burgh's vector ; S5. Introduce Taylor factors and classify them according to the Taylor factor difference ΔM of the slip pairs; S6. Fit different slip transfer prediction criteria to the slip pairs of the classification to improve prediction ability.
2. The slip-transfer prediction method considering Taylor factors according to claim 1, characterized in that, S1 specifically includes the following: S11. After tensile deformation, the sample is characterized by EBSD and Hough calibration is completed. The data is denoised using the confidence threshold. The grains are divided according to the orientation difference angle, and the grain number, average orientation and Euler angle are output. S12. High-resolution morphology imaging was performed on the tensile-deformed sample in the region consistent with the EBSD analysis, focusing on acquiring grain boundary morphology and slip traces to form joint grain boundary-slip trace data corresponding one-to-one with the EBSD grain pairs for subsequent analysis; imaging equipment included optical microscope, scanning electron microscope, confocal microscope, and atomic force microscope. S13. Compare the deformed surface morphology and slip trace images with the IPF diagram drawn by EBSD. For slip traces that are continuous across grain boundaries, they are determined to be "transmission" and slip traces that terminate at the boundary are determined to be "blockage". Then, they are associated with the corresponding grain pairs one by one.
3. The slip-transfer prediction method considering Taylor factors according to claim 2, characterized in that, S2 specifically includes the following: S21. Based on the given stress state, convert the grain Euler angles into an orientation matrix; for the material crystal structure, enumerate candidate slip systems, calculate the Schmitt factor of each slip system, and sort them. S22. Under the applied load / strain conditions, determine the Taylor factor M of the grains to obtain the M value for each grain; calculate the value for adjacent grain pairs (G1, G2). For use in subsequent classification.
4. The slip-transfer prediction method considering Taylor factors according to claim 1, characterized in that, The specific operation in S3 is as follows: the active slip surface is determined by matching the slip trace direction with the slip line direction predicted by crystal orientation; the slip direction with the largest Schmitt factor in the slip surface is selected as the actual active slip system.
5. The slip-transfer prediction method considering Taylor factors according to claim 3, characterized in that, In S4, the geometric compatibility factor Calculated according to the Luster–Morris definition, the expression is: ； in for and The angle between them for and The angle between them , These are the sliding direction and the normal to the sliding surface, respectively. Residual Burgers vector The calculation expression is: .
6. The slip-transfer prediction method considering Taylor factors according to claim 5, characterized in that, S5 specifically includes the following steps: S51. Plot the distribution of the Taylor factor difference for the slip transfer pair and the Taylor factor difference for the slip blockage pair respectively. S52. Analyze the differences in Taylor factor distribution caused by slip transfer and slip blockage, analyze the differences in their central tendency, dispersion, peak position and overlapping interval, identify the ΔM value characteristics corresponding to slip transfer and slip blockage, and provide a basis for threshold selection; S53. Based on the analysis results in S52, set the Taylor factor difference threshold ΔM. And in subsequent processing, this threshold is kept unchanged, and all sliding pairs are processed according to ΔM≤ΔM. With ΔM>ΔM The data were divided into two categories for subsequent fitting of slip transfer prediction criteria.
7. The slippage propagation prediction method considering Taylor factors according to claim 6, characterized in that, S6 specifically includes the following steps: S61. For slip pairs of different classifications, respectively using the geometric compatibility factor... With residual Burgh's vector magnitude Using the characteristic quantity, the slip transfer criterion is fitted to establish a system based on ( , () represents the determination relation of the independent variable; S62. Set the slip transfer criterion: When > a and < b If the condition is met, it is determined to be slip transfer; otherwise, it is determined to be slip blockage. a , b The threshold parameter that needs to be determined; S63. Fit the classified data separately, and find the optimal parameter combination that satisfies the form of S62 within each dataset. a , b ); S64. Within each category, different ( a , b The combination of methods is used to evaluate the effectiveness, and the combination with the highest accuracy is selected as the final slip transfer criterion for the classification.
Citation Information
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