A method for quantitatively predicting the work hardening ability of aluminum alloys by precipitate phase morphology

Abstract

The present invention discloses a method for quantitatively predicting the work hardening ability of aluminum alloys by using the morphology of precipitated phases, and belongs to the technical field of prediction of mechanical properties of metal materials. According to the dislocation slip mode of the second phase-dominated aluminum alloy leading to dislocation annihilation and redistribution, the present invention proposes a second phase annihilation coefficient k to parameterize this influence, and establishes a quantitative prediction method for the work hardening ability of materials containing the second phase. The present invention obtains the morphological information of the precipitated phase through transmission photographs, which can achieve quantitative prediction of the work hardening ability of aluminum alloys, saving the experimental costs and time consumed by tensile tests, and providing a simple, fast and reliable prediction method that does not require tensile testing to destroy service components, which has important guiding significance for the material selection and design of aluminum alloy engineering components. At the same time, the accuracy of the prediction method further verifies the influence mechanism of the precipitate phase on dislocation annihilation, enriches the work hardening theory, and has important reference significance for the establishment of the tensile constitutive relationship of aluminum alloys.

Description

Technical Field

[0001] The invention relates to the technical field of prediction of mechanical properties of metal materials, and specifically designs a method for quantitatively predicting the work hardening ability of aluminum alloys through precipitate phase morphology. Background Art

[0002] With the introduction of concepts such as localization of key components and lightweight vehicle bodies, as well as the rapid development of high-speed railways and aerospace, the requirements for their structural parts are becoming increasingly stringent. Aluminum alloys have excellent specific strength, specific stiffness, corrosion resistance, good welding performance and cold working formability in the material family, and are recyclable compared to composite materials. Therefore, they have become the most widely used type of non-ferrous metal material in transportation, aerospace and other fields.

[0003] In engineering applications, aluminum alloys primarily focus on 2-series, 6-series, and 7-series heat-treatable (primarily precipitation-hardened) aluminum alloys. These are typically used in load-bearing structural components such as aircraft fuselage and wing skins, long stringers, and high-speed train traction beams and bolsters. Therefore, the material's strength and plasticity are crucial. According to the Considére criterion, necking occurs when the work hardening rate equals the true stress. The stress and strain at this point correspond to the material's tensile strength and uniform elongation, respectively. Therefore, work hardening is a fundamental mechanical property of aluminum alloys, determining their static mechanical properties, such as strength, plasticity, hardness, and toughness. It also directly impacts the material's service performance during end-use, such as fatigue strength and life. Therefore, testing and predicting the work hardening capacity of aluminum alloys is crucial for the engineering applications and long-term service safety of engineering aluminum alloy components.

[0004] The relationship between flow stress and strain after yielding a material generally follows an exponential form, where the strain hardening exponent n quantitatively reflects the material's work-hardening ability. Conventional methods for quantitatively evaluating work-hardening ability involve mechanically preparing tensile specimens and conducting tensile tests to obtain the tensile true stress-strain curve fitting parameter n. However, conventional tensile testing requires material destruction to obtain a complete tensile curve, requiring a large amount of sample and time. Mechanically preparing tensile specimens for in-service equipment is sometimes impossible, while microstructure characterization testing is simpler, far less expensive than tensile testing, and can provide a comprehensive range of microstructural information without destroying in-service equipment. Currently, no method exists to determine the work-hardening ability of aluminum alloys without tensile testing. Therefore, establishing a general relationship between aluminum alloy microstructure and work-hardening ability and providing a reliable estimate of a material's work-hardening ability through microstructure characterization will be crucial for improving the operational quality of critical aluminum alloy equipment and accelerating the independent research and development of key aluminum alloy components in my country, as well as product upgrades. Summary of the Invention

[0005] To address the current problem of lacking an effective quantitative relationship for predicting the work-hardening ability of aluminum alloys based on microstructure, the present invention aims to provide a method for quantitatively predicting the work-hardening ability of aluminum alloys based on precipitate morphology. This method establishes a quantitative relationship between microstructure and work-hardening ability based on the microscopic deformation mechanism of aluminum alloys. Based on this quantitative relationship, the work-hardening ability of aluminum alloys can be quantitatively predicted using microstructural information without the need for tensile testing.

[0006] To achieve the above objectives, the theoretical derivation and technical route of the present invention are as follows:

[0007] Theoretical derivation: For face-centered cubic metals, the tensile stress-strain constitutive relation generally satisfies the Voce index form [E. Voce, The relationship between stress and strain for homogeneous deformation[J], J. Inst. Met. 74 (1948) 537-562.], which can be simplified to formula (1):

[0008] (1)

[0009] In formula (1), σ s , σ rand n correspond to the residual strength, saturation strength and strain hardening exponent of the material respectively. It can be seen that the work hardening ability of the material depends on the strain hardening exponent n. Therefore, the work hardening ability of the material can be quantitatively predicted according to the size of the n value. Formula (1) was proposed by Voce et al. and subsequently verified by Kocks et al., who also gave relevant theoretical derivations [UF Kocks, H. Mecking, Physics and phenomenology of strain hardening:the FCC case[J], Prog. Mater. Sci. 48(3) (2003) 171-273.]. Based on the research results of Kocks et al. and the dislocation annihilation theory of Deschamps et al. [A. Deschamps, Y. Brechet, CJ Necker,S. Saimoto, JD Embury, Study of large strain deformation of dilute solidsolutions of A1-Cu using channel-die compression[J], Mater. Sci. Eng. A 207(1996) 143 152.], it can be further deduced that the hardening exponent n is related to the equivalent dislocation annihilation distance y. e Directly related, satisfying formula (2):

[0010] (2);

[0011] In formula (2), M is the Taylor factor, which is generally taken as 3.1; b is the material's Burgers vector, and for aluminum alloys, b=0.286nm; formula (2) was later used by a large number of researchers to study the relationship between the work hardening ability of materials and their microstructures [for example: A. Simar, Y. Brechet, B. de Meester, A. Denquin, T. Pardoen, Sequential modeling of local precipitation, strength and strain hardening infriction stir welds of an aluminum alloy 6005A-T6, Acta Mater. 55(18) (2007)6133-6143.]. However, for deformed aluminum alloys containing a second phase in the matrix, the presence of the second phase will lead to the redistribution of dislocation annihilation, that is, before a sliding dislocation encounters a forest dislocation of the opposite sign, a part of the dislocation will be annihilated on the second phase, and the other part of the dislocation will undergo cross-slip annihilation with the forest dislocation. Therefore, this patent proposes a new dislocation annihilation model, such as Figure 1 As shown in the figure, this model shows that there are two typical second phases in the aluminum alloy matrix. The second phase will increase the dislocation annihilation distance around it, so that the matrix dislocations are absorbed and annihilated on the second phase. This patent proposes that the second phase increases the annihilation distance of the matrix by an average coefficient k, so the dislocation annihilation distance y around the second phase is s It can be expressed as formula (3):

[0012] y s = ky m (3);

[0013] In formula (3), y m is the intrinsic dislocation annihilation distance of the matrix, and y s is the forced annihilation distance caused by the second phase, and k can be defined as the second phase annihilation coefficient, which represents the average effect of the second phase on the matrix dislocation annihilation distance, which depends on the type of second phase (cutting through or bypassing) and the phase interface characteristics (e.g., phase interface energy). It is further proposed to regard the deformed aluminum alloy as the matrix dislocation interaction region and the forced dislocation annihilation region affected by the second phase f aff Therefore, according to the mixing criterion, in aluminum alloy, the annihilation distance y of the equivalent dislocation is e Needs to be corrected to formula (4):

[0014] (4);

[0015] In formula (4), f affrepresents the volume fraction affected by the second phase. Combining equations (2), (3) and (4), we can obtain the modified equation (5) for the strain hardening exponent n of the material containing the second phase:

[0016] (5);

[0017] In formula (5), n0 corresponds to the hardening index when there is no second phase (single-phase solid solution), which is related to the composition of the alloy; it is further proposed that the influence area of the second phase is an ellipsoid centered on the second phase, such as Figure 1 As shown, then f aff It can be expressed as the following formula (6):

[0018] (6);

[0019] In formula (6), d and l are the diameter and length of the second phase. The characteristics of the second phase are generally described by the aspect ratio ω and the typical size (i.e., the major axis size, which is the length l for a rod-like or plate-like slender second phase and the diameter d for a disk-like or spherical flat second phase). For the two typical second phases, the aspect ratio is expressed in different forms, namely ω = l / d (for a rod-like or plate-like slender second phase) and d / l (for a disk-like or spherical flat second phase), as shown in Figure 6. Figure 1 (a) and Figure 1 (b). Therefore, for the matrix containing a volume fraction of f sp and two typical second phases with aspect ratio ω, f aff There are different expressions. For the rod-shaped or plate-shaped slender second phase, they can be expressed as formula (7a):

[0020] (7a);

[0021] For disk-shaped or spherical flat second phases, they can be expressed as formula (7b):

[0022] (7b).

[0023] Technical route: Based on the above theoretical derivation, the method for quantitatively predicting the work hardening ability of aluminum alloys by precipitate phase morphology includes the following steps:

[0024] (1) The target aluminum alloy is subjected to complete solution treatment to obtain a single-phase solid solution of the corresponding alloy composition; an aging treatment is performed at a certain temperature and for a certain time to obtain an aging state with the same composition but different microstructure (i.e., containing a second phase);

[0025] (2) Performing room temperature axial tensile tests, converting the tensile engineering stress-strain curve into a true stress-strain curve, and performing exponential fitting on the true stress-strain work hardening curve segment to obtain the strain hardening exponent n0 of the complete solid solution state and the strain hardening exponent n of the corresponding aging state;

[0026] (3) Prepare the transmission sample to observe the morphology of the second phase in the aging state, and calculate the volume fraction f of the second phase based on the transmission photograph. sp , aspect ratio ω, and size (length l for elongated second phases in the form of rods or plates; diameter d for flat second phases in the form of disks or spheres).

[0027] (4) According to the n and second phase morphology characteristics (f of the corresponding aging state obtained in steps (2) and (3) sp , ω, l, d) into formula (5) and formula (7) to obtain a quartic equation about k. This type of equation has four solutions, of which two imaginary solutions can be directly eliminated. In addition, according to k≥1, the second phase annihilation coefficient k of the corresponding material can be obtained.

[0028] (5) According to the hardening index n0 of the single-phase solid solution (excluding the second phase) and the second phase annihilation coefficient k obtained in steps (2) and (4), the method of step (3) is used to obtain the morphological photographs of the precipitated phase for any aging state of the target aluminum alloy and the morphological characteristics of the second phase (f sp , ω, l, d) into formula (5) and formula (7), the strain hardening index n of the corresponding material can be quantitatively predicted, and the work hardening ability of different tissue states can be measured according to the size of the strain hardening index n.

[0029] The solution treatment in step (1) should ensure that the precipitated phase can be completely dissolved in the matrix; the aging treatment temperature should be lower than the recrystallization temperature of the aluminum alloy to prevent grain growth; the aging time should be as long as possible longer than the peak aging time of the aluminum alloy to ensure that the second phase is bypassed by dislocations; this aged alloy and the solid solution alloy and the predicted aged alloy should have the following characteristics: the same composition, the same grain size, the same initial dislocation density as much as possible, and different precipitate morphology.

[0030] In step (2), the strain rate of the tensile test is 10 -3 s -1 The following are all feasible. The exponential fitting of the true stress-strain curve adopts the form of formula (1), that is: The fitting of n value should be carried out in the complete dislocation strengthening section of the true stress-strain curve, that is, the fitting interval should be as large as possible from the yield strength of the material and smaller than the tensile strength of the material.

[0031] In step (3), the transmission sample should be prepared using the standard double-jet electrolytic polishing technique to avoid the introduction of dislocations and other artifacts during sample preparation. The geometric characteristics of the second phase are statistically analyzed by coloring the second phase using Image-Pro Plus software. The number of second phases in quantitative statistics should be more than 500. The volume fraction of the second phase is calculated using the modified projection method of formula (8), which is:

[0032] (8)

[0033] In formula (8), r is the radius of the flat second phase in the form of a disk or sphere; it is half the average half length of the elongated second phase in the form of a rod or plate; H is the thickness of the sample in the statistical area, obtained by the convergent beam diffraction technique; P A is the area fraction occupied by the second phase projection in the statistical area;

[0034] In step (4), for the same alloy with the same composition and second phase characteristics, k should be a constant. Therefore, in order to avoid experimental errors, two or three aging states, i.e. repeated experiments, should be selected to obtain the corresponding k values, and the average value should be calculated to determine the final k value.

[0035] In step (5), the prediction of work hardening for any aging state of the target aluminum alloy should be applicable to different aging temperatures and aging times, but the second phase characteristics should remain similar, with only the evolution of the second phase distribution, size, and shape. The prediction method does not consider yield strength and can only predict the work hardening ability, but cannot measure the strength and plasticity of the material.

[0036] The design mechanism and beneficial effects of the present invention are as follows:

[0037] 1. Based on the deformation mechanism of redistribution of dislocation annihilation caused by the dislocation slip mode dominated by the second phase in aluminum alloy, the present invention proposes the annihilation coefficient k of the second phase to parameterize the microstructure of aluminum alloy. Combining dislocation theory and exponential hardening model, a quantitative prediction equation for the microstructure and work hardening ability of materials containing second phase is established.

[0038] 2. The physical meaning of the relevant parameters of the present invention is clear, which quantitatively reveals the relationship between material organization and microscopic deformation mechanism, enriches the work hardening theory, and has important scientific significance for the establishment of the tensile constitutive relationship of aluminum alloy.

[0039] 3. The present invention takes into account the influence of the second phase type, shape, volume fraction and size on the work hardening ability of the material, and provides the direction of second phase optimization, which has important guiding significance for improving the work hardening performance of deformed aluminum alloys and even metal materials containing second phases.

[0040] 4. The present invention obtains the morphology information of the precipitated phase through transmission photography, and can achieve quantitative prediction of the work hardening ability of aluminum alloy without the need for tensile testing.

[0041] 5. The present invention is easy to use and greatly saves the experimental cost and time consumed by tensile testing. It provides a simple, fast and reliable prediction method that does not require destroying service components, and has important guiding role and reference significance for the material design of aluminum alloy engineering components. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 These are dislocation annihilation models of two typical second phases, illustrating the dislocation annihilation redistribution caused by the second phase; among them: (a) and (b) are two typical second phases.

[0043] Figure 2 is the strain hardening exponent that varies with the rod-like second phase annihilation coefficient k and volume fraction f sp , aspect ratio ω and size l.

[0044] Figure 3 is the strain hardening exponent n with the second phase annihilation coefficient k and the second phase volume fraction f sp , the second phase aspect ratio ω and the second phase size l (or d); where: (a) the strain hardening exponent n changes with the second phase annihilation coefficient k; (b) the strain hardening exponent n changes with the second phase volume fraction f sp (c) Variation trend of strain hardening exponent n with the aspect ratio ω of the second phase; (d) Variation trend of strain hardening exponent n with the size l (or d) of the second phase.

[0045] Figure 4 True stress-strain curves of three types of deformed aluminum alloys (2024, 6A01 and 7075 aluminum alloys) at different aging states and the strain hardening exponent n obtained by exponential fitting; among them: (a) aluminum alloy 2024; (b) aluminum alloy 6A01; (c) aluminum alloy 7075.

[0046] Figure 5 These are the tensile true stress-strain curves of the three types of alloys in complete solid solution state and pure aluminum.

[0047] Figure 6 The second phase morphology of three types of alloys in different aging states under transmission electron microscopy.

[0048] Figure 7 Comparison of the actual strain hardening exponent results obtained by calculation and experiment for the second phase morphology. DETAILED DESCRIPTION

[0049] The present invention is described in more detail below with reference to examples. These examples are merely descriptions of the best mode of carrying out the present invention and are not intended to limit the scope of the present invention in any way.

[0050] (1) The present invention is highly consistent with currently known related research, and these related research examples can be used to illustrate the rationality and reliability of the present invention. First, taking the rod-shaped second phase as an example, Figure 2 The strain hardening exponent n is shown to vary with the second phase annihilation coefficient k and the second phase volume fraction f. sp , the three-dimensional variation trend of the second phase aspect ratio ω and the second phase size l (or d) is shown in Figure 2. Figure 3 The strain hardening exponent n is further presented with the second phase annihilation coefficient k, the second phase volume fraction f sp , the second phase aspect ratio ω and the second phase size l (or d) change trend, from which we can clearly see the strain hardening exponent n and the second phase annihilation coefficient k, the second phase volume fraction f sp , the second phase aspect ratio ω is positively correlated, and negatively correlated with the second phase size l (or d). The research on the improvement of the work hardening ability of deformed aluminum alloys or other alloys containing second phases is in good agreement with these changing trends and formula (4), mainly including the following aspects:

[0051] i) The present invention shows that the improvement of work hardening ability can be achieved by reducing the cross-slip ability of the matrix by changing the alloy composition, that is, reducing y m This is consistent with the idea of related research work that alloying is used to reduce the stacking fault energy of the material and thus improve the work hardening ability.

[0052] ii) The present invention shows that the improvement of work hardening capacity can be achieved by reducing the second phase annihilation coefficient k by selecting a second phase that can be cut through (e.g. Figure 3 (a) is consistent with the idea of related research work to use coherent strengthening or introduce atomic clusters to improve the work hardening ability of materials.

[0053] iii) The present invention shows that the improvement of work hardening ability can be achieved by selecting spherical or disc-shaped equiaxed dispersion strengthening phases (as shown in 3 (c) , under the same second phase characteristics and distribution, the spherical second phase has better work hardening ability). This is consistent with the idea that related research work shows that the spherical second phase has better work hardening ability.

[0054] iv) The present invention demonstrates that the improvement of work hardening capacity can be achieved by reducing the volume fraction of bypassable second phases (e.g. Figure 3 (b) is consistent with the fact that the single-phase solid solution has better work hardening ability.

[0055] v) The present invention demonstrates that work hardening capacity can be improved by reducing the aspect ratio of the elongated second phase in the form of rods or plates (e.g. Figure 3 (b) is consistent with the idea in related research work that the larger the aspect ratio of the second phase, the worse the work hardening performance.

[0056] vi) The present invention demonstrates that work hardening capacity can be improved by increasing the size of the bypassable second phase (e.g. Figure 3 (d) is consistent with the experimental results of Zhao et al. who designed second phases of different sizes and found that coarse second phases have better work hardening ability than fine dispersed second phases [Q. Zhao, B. Holmedal, Y. Li, Influence of dispersoidson microstructure evolution and work hardening of aluminium alloys during tension and cold rolling[J], Philos. Mag. 93(22) (2013) 2995-3011.].

[0057] The above-mentioned related research works all demonstrate the rationality and reliability of the present invention. At the same time, these research works can be embodied in the present invention. In other words, the present invention can completely unify these methods for improving work hardening ability, which illustrates the innovativeness of the present invention. Therefore, the work hardening performance of the deformed aluminum alloy can be combined with the present invention to comprehensively consider the relevant methods to achieve the optimization of the work hardening performance of the deformed aluminum alloy. Secondly, although the above optimization strategies can optimize the work hardening performance, they do not consider its impact on the yield strength. For example, the coarsening of the second phase size will reduce the yield strength of the material. Therefore, in order to achieve the optimization of the strength and plasticity of the deformed aluminum alloy, strength and work hardening must be balanced.

[0058] (2) The present invention further combines examples and selects three typical deformed aluminum alloys (2024, 6A01 and 7075) to implement the method of quantitatively predicting the work hardening ability of aluminum alloys by precipitate phase morphology, which mainly includes the following steps:

[0059] (1) 2024, 6A01, and 7075 aluminum alloys were solution treated at 500℃, 530℃, and 480℃ for 4h, 1h, and 3h, respectively. Then, they were aged at 180℃, 175℃, and 140℃ for different times. 2024 aluminum alloy was aged for 16h, 20h, 24h, and 120h, 6A01 aluminum alloy was aged for 12h, 48h, 96h, and 168h, and 7075 aluminum alloy was aged for 20h, 48h, 72h, and 264h. Through aging treatment, four aging states with the same composition but different microstructures (i.e., different second phase morphologies) were obtained in the three types of deformed aluminum alloys. Two of them were used to solve the relevant parameters, and two were used for experimental verification.

[0060] (2) The three types of alloys were subjected to room temperature axial tensile tests at four aging states. The strain rate of the tensile test was 10 -3 s -1 , the tensile engineering stress-strain curve is converted into the true stress-strain curve, and the exponential fitting of the true stress-strain work hardening curve segment is performed to obtain the strain hardening index n of the corresponding aging state. The exponential fitting of the true stress-strain curve adopts the form of formula (1), that is: The fitting of n value selects the complete dislocation strengthening section of the true stress-strain curve for fitting, that is, the fitting interval is greater than the yield strength of the material and less than the tensile strength of the material. The specific results are as follows Figure 4 As shown in the figure, the three types of alloys in the complete solid solution state were subjected to axial tensile tests at room temperature. The strain rate of the tensile test was 10 -3 s -1 , convert the tensile engineering stress-strain curve into the true stress-strain curve, as shown in Figure 5. Exponential fitting of the true stress-strain work hardening curve segment can obtain the n0 of the three types of alloys. The n0 values of 2024, 6A01 and 7075 aluminum alloys are 8.5, 9.2 and 9, respectively. At the same time, we also compared the strain hardening exponents of the three types of alloys with that of pure aluminum. The n0 value of pure aluminum is 9. The n0 values of the three types of alloys are similar to those of pure aluminum. In addition, the alloying elements have little effect on the work hardening of aluminum alloys and are mainly affected by the second phase. Therefore, n0 can be determined to be 9 for the three types of alloys.

[0061] (3) Prepare the transmission sample to observe the second phase morphology of the material. The transmission sample should be prepared using the standard double-jet electrolytic polishing technology to avoid the introduction of dislocations and other artifacts during the sample preparation process. The second phase morphology of the three types of alloys in different aging states is as follows: Figure 6 As shown. The second phase was dyed by coloring the transmission photograph and then counted by Image-ProPlus software. The number of second phases counted quantitatively should be more than 500. The volume fraction of the second phase was calculated by the modified projection method of formula (8), which is:

[0062] (8);

[0063] In formula (8), r is the radius of the flat second phase in the form of a disk or sphere; it is half the average half length of the elongated second phase in the form of a rod or plate; H is the thickness of the sample in the statistical area, obtained by the convergent beam diffraction technique; P A is the area fraction of the second phase projection in the statistical area; the specific statistical volume fraction of the second phase f sp , aspect ratio ω and size (length l for rod-shaped or plate-shaped slender second phase; diameter d for disk-shaped or spherical flat second phase) are shown in Table 1.

[0064] (4) According to the n and second phase morphology characteristics (f) of the corresponding aging state obtained in steps (2) and (3) sp , ω, l, d), and substitute them into formula (5) and formula (7), where 16h and 120h are selected for 2024 aluminum alloy. By eliminating the two imaginary solutions and according to k≥1, the k values of the two aging states can be obtained, which are k （16h-2024） =4.5, k （120h-2024） =4.35, so for 2024, k can be selected as 4.425. For 6A01 aluminum alloy, 12h and 168h are selected and substituted. By eliminating the two imaginary solutions and according to k≥1, the k values of the two aging states can be obtained, which are k （12h-6A01） =1.72, k （168h-6A01） =1.88, so for 7075, k can be selected as 1.8. For 7075 aluminum alloy, 20h and 264h are selected and substituted. By eliminating the two imaginary solutions and according to k≥1, the k values of the two aging states can be obtained, which are k （20h-7075） =1.1, k （264h-7075） =1.3, so for 7075, k can be selected as 1.2.

[0065] (5) Based on the hardening exponent n0 of the single-phase solid solution (excluding the second phase) obtained in steps (2) and (4) and the second-phase annihilation coefficient k, the strain hardening exponent formula for any aging state of the three types of deformed aluminum alloys can be obtained. For any aging state of 2024, which is solution-treated at 500°C for 4 hours and then aged at 180°C, the strain hardening exponent satisfies the following formula:

[0066] (9);

[0067] For any aging state of 6A01 aluminum alloy solutionized at 530℃ for 1h and then aged at 180℃, the strain hardening exponent satisfies the following formula:

[0068] (10);

[0069] For any aging state of 7075 aluminum alloy solutionized at 480℃ for 3h and then aged at 140℃, the strain hardening exponent satisfies the following formula:

[0070] (11);

[0071] The second phase characteristics (f) of the 2024 aluminum alloy aged for 20h and 24h, the 6A01 aluminum alloy aged for 48h and 96h, and the 7075 aluminum alloy aged for 48h and 72h obtained in step 3 were further analyzed. sp , ω, l, d (see Table 1) are substituted into formula (9), formula (10), and formula (11) to obtain the strain hardening index n of the corresponding aging state. The strain hardening index calculated based on the second phase morphology is compared with the true strain hardening index obtained from the experimental tensile curve. It is found that the difference between the two is very small, as shown in Figure 7 As shown, it shows that the prediction results of the present invention are consistent with the experimental results. For any aging state of the target aluminum alloy, the method of step (3) is used to obtain the morphology of the precipitation phase and to calculate the morphology characteristics of the second phase (f sp , ω, l, d), the strain hardening exponent n of the corresponding material can be quantitatively predicted according to formula (5) and formula (7).

[0072] Table 1 Second phase characteristic parameters (second phase volume fraction f) of three types of alloys at different aging states according to the second phase morphology sp , second phase aspect ratio ω and second phase size l or d)

[0073]

Claims

1. A method for quantitatively predicting the work hardening ability of aluminum alloys by using precipitate phase morphology, characterized by: For face-centered cubic metals, the tensile stress-strain constitutive relation satisfies the Voce index form, which can be simplified to formula (1): s = s s -s r e -nε (1); In formula (1), σ s , σ r and n correspond to the saturation strength, residual strength and strain hardening index of the material respectively. It can be seen that the work hardening ability of the material depends on the strain hardening index n. Therefore, the work hardening ability of the material can be quantitatively predicted according to the value of n. The strain hardening index n is related to the equivalent dislocation annihilation distance y. e Directly related, satisfying formula (2): In formula (2), M is the Taylor factor, which is taken as 3.1; b is the Burgers vector of the material, and for aluminum alloy b = 0.286nm; formula (2) is used to study the relationship between the work hardening ability of the material and the microstructure; but for deformed aluminum alloys containing a second phase in the matrix, the existence of the second phase will lead to the redistribution of dislocation annihilation, that is, before the sliding dislocation encounters the opposite-sign forest dislocation, a part of the dislocation will be annihilated on the second phase, and the other part of the dislocation will undergo cross-slip annihilation with the forest dislocation; for the case where the aluminum alloy matrix contains a second phase, the second phase will increase the dislocation annihilation distance around it, so that the matrix dislocation is absorbed and annihilated on the second phase; therefore, it is proposed to use a coefficient k to reflect the average influence of the second phase on the annihilation distance of the matrix, then the dislocation annihilation distance y around the second phase is s It can be expressed as formula (3): yes s =ky m (3); In formula (3), y m is the intrinsic dislocation annihilation distance of the matrix, and y s is the forced annihilation distance caused by the second phase, and k is defined as the second phase annihilation coefficient, which represents the average effect of the second phase on the matrix dislocation annihilation distance, which depends on the type of the second phase and the phase interface characteristics; It is further proposed to regard the deformed aluminum alloy as a matrix forest dislocation interaction region and a forced dislocation annihilation region affected by the second phase. aff Therefore, according to the mixing criterion, in aluminum alloy, the annihilation distance y of the equivalent dislocation is e Needs to be corrected to formula (4): yes e =(1-f aff )y m +f aff ky m (4); In formula (4), f aff represents the volume fraction affected by the second phase; combining equations (2), (3) and (4), we can obtain the modified equation (5) for the strain hardening exponent n of the material containing the second phase: n=n0+n0(k-1)f aff (5); Formula (5) corresponds to the case where there is no second phase, that is, the strain hardening exponent of a single-phase solid solution, which is related to the composition of the alloy. It is further proposed that the influence area of the second phase is an ellipsoid centered on the second phase, so f aff It can be expressed as the following formula (6): In formula (6), d and l are the diameter and length of the second phase; f sp is the volume fraction of the second phase; the characteristics of the second phase are described by the aspect ratio ω and the typical size. The typical size is the major axis size. For the elongated second phase in the shape of a rod or plate, it is the length l; for the flat second phase in the shape of a disk or sphere, it is the diameter d. For the two typical second phases, the aspect ratio is expressed in different forms. The elongated second phase in the shape of a rod or plate is expressed as ω = l / d, and the flat second phase in the shape of a disk or sphere is expressed as ω = d / l. Therefore, for the matrix containing a volume fraction of f sp and two typical second phases with aspect ratio ω, f aff There are different expressions. For the rod-shaped or plate-shaped slender second phase, it can be expressed as formula (7a): For disc-shaped or spherical flat second phase, it can be expressed as formula (7b): On this basis, the method for quantitatively predicting the work hardening ability of aluminum alloys by precipitate phase morphology includes the following steps: (1) Performing a complete solid solution treatment on the target aluminum alloy to obtain a single-phase solid solution of the corresponding alloy composition; performing an aging treatment at a certain temperature and for a certain time to obtain an aging state with the same composition but different microstructure; The solution treatment should ensure that the precipitated phase is completely dissolved in the matrix; the aging treatment temperature should be lower than the recrystallization temperature of the aluminum alloy to prevent grain growth; the aging time should be greater than the peak aging time of the aluminum alloy to ensure that the secondary phase is bypassed by dislocations; the aged alloy, the solution alloy, and the predicted aged alloy should have the following characteristics: the same composition, the same grain size, the same initial dislocation density, and different precipitate morphologies; (2) Performing room temperature axial tensile tests, converting the tensile engineering stress-strain curve into a true stress-strain curve, and performing exponential fitting on the true stress-strain work hardening curve segment to obtain the strain hardening exponent n0 of the complete solid solution state and the strain hardening exponent n of the corresponding aging state; (3) Prepare the transmission sample to observe the morphology of the second phase in the aging state, and calculate the volume fraction of the second phase f based on the transmission photograph sp , aspect ratio ω and typical dimensions: length l for elongated second phases in the form of rods or plates; diameter d for flat second phases in the form of disks or spheres; (4) According to steps (2) and (3), the corresponding aging state n and second phase morphology characteristics are obtained: f sp Substituting ω, l and d into formula (5) and formula (7a) and (7b) can obtain a quartic equation about k. This type of equation has four solutions, of which two imaginary solutions can be directly eliminated. In addition, according to k≥1, the second phase annihilation coefficient k of the corresponding material can be obtained; (5) According to the hardening index n0 of the single-phase solid solution and the second-phase annihilation coefficient k obtained in steps (2) and (4), the method of step (3) is used to obtain the precipitated phase morphology photos and statistically analyze the second-phase morphology characteristics for any aging state of the target aluminum alloy: f sp By substituting ω, l, and d into formula (5) and formulas (7a) and (7b), the strain hardening exponent n of the corresponding material can be quantitatively predicted, and the work hardening ability of different tissue states can be measured according to the size of the strain hardening exponent n.

2. The method for quantitatively predicting the work hardening ability of aluminum alloys by using precipitate phase morphology according to claim 1, characterized in that: In step (2), the strain rate of the tensile test is 10 -3 s -1 In the following, the exponential fitting of the true stress-strain curve adopts the form of formula (1), that is: σ = σ s -σ r e -nε ; The fitting of n value should select the complete dislocation strengthening section of the true stress-strain curve for fitting, that is, the fitting interval is greater than the yield strength of the material and less than the tensile strength of the material.

3. The method for quantitatively predicting the work hardening ability of aluminum alloys by using precipitate phase morphology according to claim 1, characterized in that: In step (3), the transmission sample should be prepared using the standard double-jet electrolytic polishing technique to avoid the introduction of dislocation artifacts during sample preparation. The second phase morphology statistics are performed by dyeing the second phase using the coloring method and then using Image-ProPlus software for statistics. The number of second phases in quantitative statistics should be more than 500. The statistics of the second phase volume fraction use the modified projection method of formula (8). In formula (8), r is the radius of the disc-shaped or spherical flat second phase, and is the average half-length 1 / 2 of the rod-shaped or plate-shaped elongated second phase; H is the thickness of the sample in the statistical area, obtained by the convergent beam diffraction technique; P A is the area fraction occupied by the second phase projection in the statistical area.

4. The method for quantitatively predicting the work hardening ability of aluminum alloys by using precipitate phase morphology according to claim 1, characterized in that: In step (4), for the same alloy with the same composition and second phase characteristics, k should be a constant. Therefore, in order to avoid experimental errors, two to three aging state experiments should be selected to obtain the corresponding k values, and the average value should be calculated to determine the final k value.

5. The method for quantitatively predicting the work hardening ability of aluminum alloys by using precipitate phase morphology according to claim 1, characterized in that: In step (5), the work hardening prediction of any aging state of the target aluminum alloy is applicable to different aging temperatures and aging times, but the second phase characteristics should remain similar, only the second phase distribution, size and shape evolve.

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