Method for predicting tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation method
By combining digital image correlation methods with in-situ SEM technology, the strain distribution law of ferrite and pearlite was obtained, and a ferrite-pearlite two-phase tensile prediction model was established. This solved the problem of low prediction accuracy in the existing technology and achieved high-precision tensile curve prediction and material property evaluation.
Patent Information
- Application Number
- CN202511462277.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-14
- Publication Date
- 2025-12-12
AI Technical Summary
Existing methods for predicting tensile curves of ferrite-pearlite low-alloy high-strength steels are not very accurate and cannot reflect the influence of complex microstructures and interphase interactions during deformation.
The strain distribution in the ferrite and pearlite regions was obtained by using digital image correlation (DIC) combined with in-situ scanning electron microscopy (SEM). A two-phase tensile prediction model of ferrite-pearlite was established by the mixing rule, and combined with the single-phase tensile curve, the micro-strain distribution law was reflected.
It significantly improves the prediction accuracy of macroscopic tensile curves of ferrite-pearlite low-alloy high-strength steel, especially the accuracy of yield behavior and work hardening behavior. The model has clear physical meaning, is computationally efficient, and is suitable for material design and performance evaluation.
Smart Images
Figure CN121122484A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application relates to a ferrite-pearlite low-alloy high-strength steel tensile curve prediction method. BACKGROUND
[0002] Ferrite-pearlite low-alloy high-strength steel (such as QStE420, SAPH440, S355, etc.) is widely used in the fields of automobiles, buildings and the like due to its good strength, plasticity and formability. Accurate prediction of the macro tensile mechanical behavior (i.e. the tensile curve) is crucial for material design, process optimization and component service performance evaluation. Existing empirical / semi-empirical models are based on empirical formulas of composition or simple organizational parameters (such as pearlite fraction), and the prediction accuracy is limited, and it is difficult to reflect the influence of complex microstructure and interphase interaction in the deformation process. The simple single-phase model superposition method ignores the significant strain partition phenomenon (i.e. non-uniform distribution of strain in two phases) caused by the difference in mechanical properties of two phases (ferrite is soft and pearlite is hard) in the dual-phase material, resulting in a large deviation between the predicted results and the experimental values. SUMMARY
[0003] The application aims to solve the technical problems of the existing ferrite-pearlite low-alloy high-strength steel tensile curve prediction method, which has low prediction accuracy and is difficult to reflect the influence of complex microstructure and interphase interaction in the deformation process, and provides a ferrite-pearlite low-alloy high-strength steel tensile curve prediction method based on a digital image correlation method.
[0004] The ferrite-pearlite low-alloy high-strength steel tensile curve prediction method based on the digital image correlation method of the application is performed according to the following steps:
[0005] S1, obtaining in-situ scanning electron microscope (SEM) photos of a ferrite-pearlite low-alloy high-strength steel under different tensile deformations by an in-situ SEM;
[0006] S2, after uniform cropping and grayscale processing of the SEM images obtained in S1, performing DIC analysis on the grayscale-processed images by using an open-source digital image correlation software Ncorr, identifying ferrite regions and pearlite regions, and respectively obtaining ferrite average strains ε xx, Ferrite , pearlite average strains ε xx, Pearlite and global average strains ε xx, global , dividing the ferrite average strain corresponding to the same global average strain by the value of the pearlite average strain to define a strain ratio SP, fitting a curve of the strain ratio SP with respect to the global average strain, with the horizontal coordinate being the global average strain and the vertical coordinate being the strain ratio SP;
[0007] S3. Establish single-phase tensile curves of ferrite and pearlite based on the composition and microstructure of the test materials (existing method).
[0008] S4. Using the mixing rule, the variation curve of strain ratio SP fitted in S2 with global average strain is combined with the single-phase tensile curves of ferrite and pearlite obtained in S3 to establish a ferrite-pearlite two-phase tensile prediction curve.
[0009] All strains in this invention are horizontal strains.
[0010] The method of this invention acquires images of ferrite-pearlite low-alloy high-strength steel at different macroscopic deformation stages using in-situ scanning electron microscopy (SEM), and quantitatively obtains the strain distribution law between ferrite and pearlite by combining it with digital image correlation (DIC) analysis. Then, it combines this law with existing or available single-phase physical models of ferrite and pearlite to establish a macroscopic tensile curve prediction model for low-alloy high-strength steel. In this model, the local stress of each phase is calculated by its single-phase constitutive model and the local strain corresponding to the macroscopic strain determined by the strain distribution law.
[0011] This invention significantly improves the prediction accuracy of macroscopic tensile curves, particularly yield behavior and work hardening behavior, of ferrite-pearlite low-alloy high-strength steel by introducing real microscopic strain nonuniformity (strain distribution) information. The model has clear physical meaning and is relatively efficient in calculation, providing a powerful tool for understanding the deformation mechanism of low-alloy high-strength steel and guiding material design.
[0012] This invention can accurately reflect the mechanical interaction between ferrite and pearlite phases in low-alloy high-strength steel. The predicted results are in high agreement with the measured curves. It has the advantages of high computational efficiency, clear physical meaning and strong universality, and is suitable for material design, performance evaluation and process optimization.
[0013] This invention combines advanced microscopic deformation observation technology and single-phase physical models to achieve efficient and accurate prediction of the tensile curves of ferrite-pearlite low-alloy high-strength steel.
[0014] The beneficial effects of this invention are:
[0015] 1. Significantly improved prediction accuracy: The method of this invention directly introduces the micro-strain distribution law (strain ratio SP change curve with global strain) obtained by in-situ SEM-DIC technology, which can truly reflect the interaction between ferrite and pearlite phases and the load transfer mechanism during the deformation process of low alloy high strength steel. It only fits once in S2, which improves the accuracy and the prediction curve has a high degree of agreement with the experimental curve.
[0016] 2. The model of this invention is based on microscopic deformation observation and has clear physical meaning. It reveals the key influence of microscopic strain distribution on macroscopic mechanical properties and helps to deepen the understanding of the deformation mechanism of low-alloy high-strength steel.
[0017] 3. Compared with complex finite element simulation based on real structures, the model structure constructed by the method of this invention is relatively simple and has high computational efficiency. After obtaining the necessary single-phase physical model parameters and strain distribution law, the tensile curves of ferrite-pearlite low alloy high-strength steels with different compositions / structures can be quickly predicted, which is suitable for material design and performance prediction.
[0018] 4. This invention ingeniously combines advanced in-situ SEM-DIC micro-deformation observation technology with single-phase tensile curves, providing an effective way to connect microstructure evolution with macroscopic mechanical properties;
[0019] 5. The model of this invention reveals the core role of strain distribution in the mechanical behavior of low-alloy high-strength steel, providing a theoretical basis and quantitative tool for optimizing material properties (such as strength-plasticity matching) by controlling the microstructure. Attached Figure Description
[0020] Figure 1 SEM images of the three pause points in S1 of Experiment 1;
[0021] Figure 2 The coordinate correspondence diagram of the average local strain of the ferrite region, the average local strain of the pearlite region, and the global average strain at the three pause points obtained in S2 of Experiment 1.
[0022] Figure 3 The curve showing the variation of strain ratio SP with global average strain fitted in S2 of Experiment 1;
[0023] Figure 4 Single-phase tensile curves of ferrite and pearlite in S3 of Experiment 1;
[0024] Figure 5 The predicted and measured stress curves for the ferrite-pearlite biphase tensile stress were established in S4 of Experiment 1. Detailed Implementation
[0025] Specific Implementation Method 1: This implementation method is a prediction method for the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation, specifically carried out according to the following steps:
[0026] S1. In-situ SEM images of ferrite-pearlite low-alloy high-strength steel under undeformed and different tensile deformations were obtained by in-situ scanning electron microscopy.
[0027] S2. After uniformly cropping and grayscale processing of the SEM images obtained in S1, DIC analysis is performed on the grayscale images using the open-source digital image processing software Ncorr to identify ferrite and pearlite regions, and the average strain ε of ferrite under multiple deformation values is obtained. xx, Ferrite Pearlite average strain ε xx, Pearlite and global average strain ε xx, global The strain ratio SP is defined as the average strain of ferrite divided by the average strain of pearlite corresponding to the same global average strain. The curve of strain ratio SP versus global average strain is fitted, with the global average strain on the horizontal axis and the strain ratio SP on the vertical axis.
[0028] S3. Establish single-phase tensile curves for ferrite and pearlite based on the composition and microstructure of the test materials;
[0029] S4. Using the mixing rule, the variation curve of strain ratio SP fitted in S2 with global average strain is combined with the single-phase tensile curves of ferrite and pearlite obtained in S3 to establish a ferrite-pearlite two-phase tensile prediction curve.
[0030] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that S1 includes the following steps:
[0031] S11. Cut tensile samples for in-situ tensile testing from the plate, and grind, polish and lightly etch their surfaces in sequence.
[0032] S12. The sample is mounted on the in-situ tensile stage and placed in the sample chamber of a scanning electron microscope, and subjected to uniaxial tensile testing at a quasi-static rate. During the tensile process, the loading is paused at a preset key local strain to maintain load stability. At the pause point, secondary electron images are acquired in the region of interest using SEM. The rest is the same as in Specific Implementation Method 1.
[0033] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that S2 includes the following steps:
[0034] S21. Use Photoshop to crop the images taken in S1 to a uniform size and convert them to grayscale.
[0035] S22. Import the processed series of images into the open-source digital image processing software Ncorr, set the size of the region of interest, the radius of the sub-region, the step size of the sub-region, and the strain radius, and then perform DIC processing to obtain the strain distribution map of the region of interest.
[0036] S23. Based on the corresponding pearlite and ferrite regions in the SEM, extract local data from the analyzed strain distribution map and calculate the average ferrite strain ε.xx, Ferrite Pearlite average strain ε xx, Pearlite and the global average strain ε in the region of interest xx, global ; Calculate the average strain of ferrite divided by the average strain of pearlite and define it as the strain ratio SP;
[0037] S24. Use Origin software to plot the strain ratio SP as a function of the global average strain ε in the region of interest. xx, global The scatter plot was fitted to obtain the strain ratio SP as a function of the global average strain ε. xx, global The curve showing the changing pattern. Other aspects are the same as in specific implementation method one or two.
[0038] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that the selection of parameters for the single-phase stretching curve in S3 includes the dislocation propagation rate, Taylor factor, and constant. Everything else is the same as in Specific Implementation Methods One to Three.
[0039] Specific Implementation Method Five: This implementation method differs from Specific Implementation Method Four in that: the method in S4 that combines the strain ratio SP fitted in S2 with the global average strain variation curve with the single-phase tensile curves of ferrite and pearlite obtained in S3 using the mixing rule to establish the ferrite-pearlite two-phase tensile prediction curve is as follows:
[0040] (1)
[0041] (2)
[0042] in For global average strain, For the average strain of ferrite, The average strain of pearlite is given by F, and F is the volume fraction of pearlite single phase.
[0043] (3)
[0044] Solving the equations simultaneously using formulas (2) and (3) yields the following results: corresponding and Then, the corresponding single-phase tensile curves of ferrite and pearlite were obtained. and Then, the stress is obtained using Formula 1. Finally, a ferrite-pearlite two-phase tensile prediction curve was established, with the horizontal axis representing the global average strain and the vertical axis representing the stress. Everything else is the same as in Specific Implementation Method Four.
[0045] The invention was verified using the following experiments:
[0046] Experiment 1: This experiment presents a method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation. The specific steps are as follows:
[0047] S1. Select hot-rolled finished steel plates from a steel plant. The microstructure of the test steel consists of ferrite and a small amount of pearlite. In-situ tensile samples are cut from the plates, and their surfaces are ground, polished, and lightly etched. The samples are then mounted on an in-situ tensile stage and placed in the scanning electron microscope (SEM) sample chamber for uniaxial tensile testing at a quasi-static rate. During the tensile process, loading is paused at preset key local strain values to maintain load stability. At the pause points (a total of 3 points), secondary electron images (e.g., ...) are acquired using SEM within the region of interest. Figure 1 (As shown), used for subsequent DIC calculations;
[0048] S2. After uniformly cropping and grayscale processing of the SEM images obtained in S1, DIC analysis is performed on the grayscale images using the open-source digital image processing software Ncorr. Based on the natural texture features of the SEM images of the etched samples, ferrite and pearlite regions in the images are identified and segmented, generating a two-phase mask. The average local strain ε of the ferrite region at three pause points is extracted using the two-phase mask. xx, Ferrite The average local strain ε in the pearlite region xx, Pearlite and global average strain ε xx, global (like Figure 2 As shown), the ferrite strain divided by the pearlite strain at the three pause points is calculated and defined as the strain ratio SP. A curve is fitted showing the variation of the strain ratio SP with the global average strain, where the horizontal axis represents the global average strain and the vertical axis represents the strain ratio SP (as shown). Figure 3 (as shown)
[0049] S3. Establish single-phase tensile curves for ferrite and pearlite based on the composition and microstructure of the test materials (e.g., ...). Figure 4 (As shown), this section describes the existing method, and the specific process is as follows:
[0050] During the elastic deformation stage, the strain (ε)-stress (σ) relationship for both ferrite and pearlite is:
[0051] (1)
[0052] In the formula, E is the elastic modulus (210 GPa).
[0053] During the plastic deformation stage, the strain (ε)-stress (σ) relationships of ferrite and pearlite are as follows:
[0054] Ferrite single-phase model:
[0055] Yield stage (ε) UY<ε<ε LY ):
[0056] (2)
[0057] (3)
[0058] (4)
[0059] In the formula, τ0 is the initial decomposed shear stress;
[0060] Deformation rate;
[0061] n——constant (35);
[0062] d—grain size;
[0063] b——Bergård vector (2.48×10 -8 cm);
[0064] σ UY —Upper yield strength;
[0065] σ0—Lattice resistance;
[0066] σ ss —Solid solution strengthening;
[0067] σ g —Refining of grains;
[0068] σ p —Precipitation enhancement;
[0069] σ dis —Dislocation reinforcement;
[0070] k1 — dislocation increment rate;
[0071] M—Taylor factor (3);
[0072] G – Shear modulus (80 GPa);
[0073] α — constant (0.33);
[0074] ρ0 — Initial dislocation density.
[0075] Work hardening stage (ε>ε) LY ):
[0076] (5)
[0077] (6)
[0078] (7)
[0079] In the formula, σ LY —Lower yield strength;
[0080] b——Bergård vector (2.48×10 -8 cm);
[0081] L—mean free path of dislocation density, which can be approximated by the ferrite grain size d;
[0082] ρ(ε) — dislocation density, a function of strain;
[0083] k2 — dislocation annihilation rate;
[0084] p — constant (0.66);
[0085] Pearlite single-phase model:
[0086] Work hardening stage:
[0087] (8)
[0088] In the formula, s is the pearlite lamellar spacing, which is a fixed value;
[0089] k — Material parameter;
[0090] g—Material parameter;
[0091] G – Shear modulus (80 GPa);
[0092] S4. Using the mixing principle, the curve of strain ratio SP as a function of global strain obtained in S2 is combined with the single-phase tensile curves of ferrite and pearlite obtained in S3 to establish a two-phase tensile prediction curve of ferrite-pearlite. The specific process is as follows:
[0093] (1)
[0094] (2)
[0095] in The global average strain is a known quantity. For the average strain of ferrite, Let F be the average strain of pearlite, and F be the volume fraction of the single-phase pearlite (a known quantity, obtained through...). Figure 1 get);
[0096] (3)
[0097] Solving the equations simultaneously using formulas (2) and (3) yields the following results: corresponding and Then, through the single-phase stretching curves of ferrite and pearlite ( Figure 4 The corresponding stress is obtained. and Then, the stress is obtained using Formula 1. Finally, the ferrite-pearlite two-phase tensile prediction curve was established (e.g. Figure 5 (As shown by the black line), the horizontal axis represents the global average strain, and the vertical axis represents the stress. ;
[0098] The tensile curve predicted by the model is compared with the actual curve obtained from the standard tensile test of the same material, such as... Figure 5 As shown, the red line represents the measured stress. It can be seen that the predicted curve and the measured curve have a high degree of agreement. The above steps can be repeated for low-alloy high-strength steels with different compositions / structures.
Claims
1. A method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation, characterized in that... The prediction method described herein is performed according to the following steps: S1. In-situ SEM images of ferrite-pearlite low-alloy high-strength steel under undeformed and different tensile deformations were obtained by in-situ scanning electron microscopy. S2. After uniformly cropping and grayscale processing of the SEM images obtained in S1, DIC analysis is performed on the grayscale images using the open-source digital image processing software Ncorr to identify ferrite and pearlite regions, and the average strain ε of ferrite under multiple deformation values is obtained. xx, Ferrite Pearlite average strain ε xx, Pearlite and global average strain ε xx, global The strain ratio SP is defined as the average strain of ferrite divided by the average strain of pearlite corresponding to the same global average strain. The curve of strain ratio SP versus global average strain is fitted, with the global average strain on the horizontal axis and the strain ratio SP on the vertical axis. S3. Establish single-phase tensile curves for ferrite and pearlite based on the composition and microstructure of the test materials; S4. Using the mixing rule, the variation curve of strain ratio SP fitted in S2 with global average strain is combined with the single-phase tensile curves of ferrite and pearlite obtained in S3 to establish a ferrite-pearlite two-phase tensile prediction curve.
2. The method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation according to claim 1, characterized in that... S1 includes the following steps: S11. Cut tensile samples for in-situ tensile testing from the plate, and grind, polish and lightly etch their surfaces in sequence. S12. The sample is installed on the in-situ tensile stage and placed in the sample chamber of the scanning electron microscope and subjected to uniaxial tensile testing at a quasi-static rate. During the tensile process, the loading is paused at the preset key local strain to maintain load stability. At the pause point, secondary electron images are acquired in the region of interest using SEM.
3. The method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation according to claim 1, characterized in that... The S2 includes the following steps: S21. Use Photoshop to crop the images taken in S1 to a uniform size and convert them to grayscale. S22. Import the processed series of images into the open-source digital image processing software Ncorr, set the size of the region of interest, the radius of the sub-region, the step size of the sub-region, and the strain radius, and then perform DIC processing to obtain the strain distribution map of the region of interest. S23. Based on the corresponding pearlite and ferrite regions in the SEM, extract local data from the analyzed strain distribution map and calculate the average ferrite strain ε. xx, Ferrite Pearlite average strain ε xx, Pearlite and the global average strain ε in the region of interest xx, global ; Calculate the average strain of ferrite divided by the average strain of pearlite and define it as the strain ratio SP; S24. Use Origin software to plot the strain ratio SP as a function of the global average strain ε in the region of interest. xx, global The scatter plot was fitted to obtain the strain ratio SP as a function of the global average strain ε. xx, global The curve showing the changing pattern.
4. The method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation according to claim 1, characterized in that... The selection of parameters for the single-phase stretching curve in S3 includes dislocation multiplication rate, Taylor factor, and constant.
5. The method for predicting the tensile curve of ferrite-pearlite low-alloy high-strength steel based on digital image correlation according to claim 1, characterized in that... The method described in S4, which combines the strain ratio SP fitted in S2 with the global average strain curve with the single-phase tensile curves of ferrite and pearlite obtained in S3, to establish the ferrite-pearlite two-phase tensile prediction curve, is as follows: （1） （2） in For global average strain, For the average strain of ferrite, The average strain of pearlite is given by F, and F is the volume fraction of pearlite single phase. （3） Solving the equations simultaneously using formulas (2) and (3) yields the following results: corresponding and Then, the corresponding single-phase tensile curves of ferrite and pearlite were obtained. and Then, the stress is obtained using Formula 1. Finally, a ferrite-pearlite two-phase tensile prediction curve was established, with the horizontal axis representing the global average strain and the vertical axis representing the stress. .