Aluminum-lithium alloy forging mechanical property space distribution prediction method

Abstract

The application discloses a kind of aluminum lithium alloy forgings mechanical property space distribution prediction methods, belong to the field of forgings mechanical property space distribution prediction, this method includes obtaining the XRD organization characterization sample of aluminum lithium alloy different equivalent strain value target area, EBSD organization characterization sample, TEM organization characterization sample and tensile sample;Based on the XRD, EBSD, TEM characterization result and tensile test result of each equivalent strain value target area, equivalent strain-T1 phase diameter relationship and equivalent strain-T1 phase thickness relationship are constructed, and then equivalent strain-yield strength relationship and equivalent strain-elongation relationship are obtained, and a finite element operation solver is compiled by secondary development;Mechanical property space distribution prediction of the forgings to be measured is carried out using the finite element operation solver.The application solves the problem that the internal mechanical property space distribution of aluminum lithium alloy forgings cannot be accurately predicted and predicted.

Description

Technical Field

[0001] This invention belongs to the field of spatial distribution prediction of mechanical properties of forgings, and particularly relates to a method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings. Background Technology

[0002] Aluminum-lithium alloy forgings possess the combined advantages of low density, good corrosion resistance, and high elastic modulus, making them highly promising for applications in aircraft fuselage accessories, wings, and other primary load-bearing aerospace components. The manufacturing process for aluminum-lithium alloy forgings generally involves melting and casting, homogenization heat treatment, free forging, die forging, solution treatment, quenching, cold pressing pre-deformation, and aging. Due to the ability to introduce dislocations and promote heterogeneous nucleation and dispersed precipitation of strengthening phases, cold pressing pre-deformation has a particularly significant impact on mechanical properties; the difference in yield strength between aluminum-lithium alloys that have undergone effective cold pressing deformation and those that have not can exceed 100 MPa.

[0003] Currently, in the process design for cold-pressing pre-deformation of aluminum-lithium alloys, production typically pre-sets a compression amount of 3-5% based on experience. However, aluminum-lithium alloy forgings often have irregular structures. After cold pressing according to the experienced compression amount, the actual strain distribution and spatial distribution of mechanical properties inside the forging lack accurate prediction. Due to this unpredictability, aluminum-lithium alloy forgings are prone to exhibiting discrepancies in yield strength and elongation that fail to meet standard requirements, becoming a major factor leading to forging scrap.

[0004] Finite element method (FEM) simulation provides a platform for predicting the spatial distribution of state variables in forgings, such as temperature and strain. However, there is still a technological gap for predicting the spatial distribution of mechanical properties in aluminum-lithium alloy forgings. Therefore, to ensure the reliability of the mechanical properties of aluminum-lithium alloy forgings and improve the yield, it is necessary to develop a finite element method for predicting the spatial distribution of mechanical properties in aluminum-lithium alloy forgings. Summary of the Invention

[0005] To address the aforementioned shortcomings in the existing technology, the present invention provides a method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings, which solves the problem of inaccurate prediction and unpredictability of the actual strain distribution and spatial distribution of mechanical properties inside the forgings.

[0006] To achieve the aforementioned objectives, the present invention employs the following technical solution: a method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings, comprising:

[0007] Experimental and numerical simulation analysis of cold pressing pre-deformation process of aluminum-lithium alloy were carried out to obtain the mean equivalent strain of target regions with different equivalent strain values, XRD microstructure specimens, EBSD microstructure specimens, TEM microstructure specimens and tensile specimens.

[0008] Based on the mean equivalent strain of each equivalent strain target region, XRD microstructure characterization sample, EBSD microstructure characterization sample and TEM microstructure characterization sample, the equivalent strain-dislocation density relationship, the average value of Taylor factor M, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship are obtained.

[0009] Based on the average value of Taylor factor M in each equivalent strain target region, tensile specimen, equivalent strain-dislocation density relationship, equivalent strain-T1 phase diameter relationship and equivalent strain-T1 phase thickness relationship, construct equivalent strain-yield strength relationship and equivalent strain-elongation relationship.

[0010] Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, secondary development of finite element simulation software was carried out, and a finite element calculation solver was compiled.

[0011] The spatial distribution prediction results of the verification alloy yield strength, elongation, T1 phase diameter and T1 phase thickness were obtained by using a finite element method solver.

[0012] Based on the spatial distribution prediction results of the verification alloy, determine whether the finite element method solver meets the fitting termination condition. If it does, then the spatial distribution prediction of the mechanical properties of the verification alloy is realized; otherwise, return to retrain the finite element method solver for fitting.

[0013] The beneficial effects of this invention are as follows: Based on finite element simulation, this invention clarifies the mapping relationship between equivalent strain and mechanical properties at different spatial locations of the sample, and accordingly constructs a mathematical model of yield strength, elongation, T1 phase characteristics, and equivalent strain. This enables finite element simulation prediction of the spatial distribution of yield strength, elongation, and T1 phase characteristics during the cold pressing process of the alloy forging. Furthermore, process experiments on complex aluminum-lithium alloy forgings were conducted, and combined with mechanical property analysis, the simulation prediction results were verified, thus ensuring the effectiveness of the prediction method of this invention.

[0014] Furthermore, the process of obtaining the mean equivalent strain value, XRD microstructure characterization specimen, EBSD microstructure characterization specimen, TEM microstructure characterization specimen, and tensile specimen for different equivalent strain target regions specifically involves:

[0015] Cold compression tests were conducted on solution-quenched aluminum-lithium alloys using pressure equipment, and stress-strain curve data were collected simultaneously.

[0016] Based on the stress-strain curve data, Young's modulus and stress-strain curves are obtained. A flow stress model is constructed based on Young's modulus and stress-strain curves, and the flow stress model is imported into finite element software to construct a material model for simulation.

[0017] The geometric models of aluminum-lithium alloy forgings and pressure fixtures under the same cold compression test conditions were drawn using 3D modeling software. They were then imported into finite element simulation software to establish a cold compression simulation model based on the material model used for simulation, and the simulation results of the cold compression specimens were output.

[0018] Extract the equivalent strain spatial distribution data of the cold-compressed specimen from the simulation results, determine multiple equivalent strain target regions along the thickness direction of the cold-compressed specimen, and based on the equivalent strain spatial distribution data, randomly select several points in each equivalent strain target region to obtain the equivalent strain mean value of the corresponding equivalent strain target region.

[0019] XRD and EBSD microstructure characteristics of cold-compressed specimens were performed on the target regions of each equivalent variable value using wire cutting.

[0020] The cold-compression specimens were aged, and then TEM microstructure was performed on the target regions of each equivalent strain value using the wire cutting method. Specimen sampling and tensile specimen sampling were also performed.

[0021] The beneficial effects of the above-mentioned further scheme are as follows: This step collects stress-strain data through pressure equipment to construct a flow stress model, establishes a geometric model consistent with the pre-deformation test using 3D modeling software, imports it into finite element software for cold compression simulation, extracts equivalent strain spatial distribution data, scientifically locates the target area and takes samples, and obtains various characterization samples after aging treatment. This achieves precise control over the entire process from data acquisition and model construction to simulation analysis and sample sampling, ensuring the accuracy and reliability of the study on the mapping relationship between equivalent strain and mechanical properties, and providing a scientific and efficient technical path for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings.

[0022] Furthermore, the obtained equivalent strain-dislocation density relationship, the average value of the Taylor factor M, the equivalent strain-T1 phase diameter relationship, and the equivalent strain-T1 phase thickness relationship are specifically as follows:

[0023] The XRD-characterized samples were characterized based on the target regions of each equivalent strain value. The dislocation density value of each XRD-characterized sample was calculated. Based on the dislocation density value of each XRD-characterized sample and the mean equivalent strain value of each target region, the equivalent strain-dislocation density relationship was established:

[0024]

[0025] in, For equivalent effect Dislocation density at time; For equivalent change; , and All are equivalent strain-dislocation density fitting coefficients;

[0026] The EBSD tissue samples were characterized based on the target regions of each equivalent variable value. The distribution of the Taylor factor M was statistically analyzed, and the average value of the Taylor factor M was calculated.

[0027] The TEM microstructure of the samples was characterized based on the target regions of each equivalent strain value. The diameter and thickness of the T1 phase were statistically analyzed. Based on the T1 phase diameter, T1 phase thickness, and the mean equivalent strain of each target region of the TEM microstructure of the samples, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship were established.

[0028]

[0029]

[0030] in, For equivalent effect The diameter of phase T1 at that time; and All are equivalent strain-T1 phase diameter fitting coefficients; For equivalent effect The thickness of the T1 phase at that time; , and All are equivalent strain-T1 phase thickness fitting coefficients.

[0031] The beneficial effects of the above-mentioned further scheme are as follows: This step quantitatively calculates the dislocation density of the sample through XRD microstructure characterization and establishes the equivalent strain-dislocation density relationship; it uses the statistical Taylor factor M distribution of the sample through EBSD microstructure characterization to obtain the dislocation strength contribution model parameters; and it constructs the equivalent strain-T1 phase size relationship based on the T1 phase diameter and thickness measured by TEM microstructure characterization. A mathematical model is established through polynomial fitting, realizing cross-scale quantitative mapping between microstructure characteristics (dislocation density, strengthening phase size) and macroscopic deformation parameters. The constructed model can effectively characterize the dislocation multiplication and T1 phase evolution law during cold pressing deformation, providing a technical solution with multi-dimensional characterization, high-precision modeling, and engineering applicability for predicting the mechanical properties of aluminum-lithium alloy forgings.

[0032] Furthermore, the construction of the equivalent strain-yield strength relationship and the equivalent strain-elongation relationship is specifically as follows:

[0033] Based on the tensile specimens in the target regions of each equivalent strain value, mechanical properties were tested to obtain the yield strength and elongation data of each tensile specimen.

[0034] Based on the yield strength of each tensile specimen, the contribution of dislocation strengthening to the yield strength is calculated using Taylor's formula, and a relationship between dislocation density and dislocation strength contribution is constructed.

[0035] Establish criteria for identifying T1 tangential over-enhancement and bypass enhancement mechanisms:

[0036]

[0037] in, To identify the criteria; The diameter of phase T1; The thickness of phase T1; For the statistical average diameter of phase T1, when When >10, the dislocation bypass mechanism is used; when When the value is ≤10, the dislocations are sheared.

[0038] Based on the identification criteria for T1 phase over-strengthening and bypass strengthening mechanisms, the strength contributions of T1 phase diameter and T1 phase thickness to over-strengthening and bypass strengthening are constructed:

[0039]

[0040]

[0041] in, For equivalent effect The contribution of T1 phase diameter and T1 phase thickness to the strength of shear strengthening; Shear modulus; It is the Bergman vector; For equivalent effect The diameter of phase T1 at that time; For equivalent effect The thickness of the T1 phase at that time; For equivalent effect The contribution of the T1 phase diameter and T1 phase thickness to the strength of bypass reinforcement; For interface energy; For dislocation line tension;

[0042] Combining the equivalent strain-dislocation density relationship with the dislocation density-dislocation intensity contribution relationship, we obtain the relationship between equivalent strain and dislocation intensity contribution:

[0043]

[0044] in, For equivalent effect The contribution of dislocation strength at time; For equivalent change; The average value of the Taylor factor M; These are material constants; For equivalent effect Dislocation density at time;

[0045] By combining the equivalent strain-T1 phase diameter relationship, the equivalent strain-T1 phase thickness relationship, the strength contribution of T1 phase diameter and T1 phase thickness to shear strengthening, and the strength contribution of T1 phase diameter and T1 phase thickness to bypass strengthening, we obtain the equivalent strain-shear strengthening relationship and the equivalent strain-bypass strengthening relationship.

[0046] By superimposing the basic strength of aluminum-lithium alloy, the relationship between equivalent strain and dislocation strength contribution, the equivalent strain-through strengthening relationship, and the equivalent strain-bypass strengthening relationship, the equivalent strain-yield strength relationship is obtained.

[0047] Based on the elongation data of each tensile specimen and the mean equivalent strain of each equivalent strain target region, the equivalent strain-elongation relationship is constructed as follows:

[0048]

[0049] in, Elongation; , and All are equivalent strain-elongation fitting coefficients.

[0050] The beneficial effects of the above-mentioned further scheme are as follows: This step involves testing the mechanical properties of tensile specimens in each equivalent strain target region, using the yield strength of the specimen after solution treatment as the basic strength, constructing a dislocation density-dislocation strength contribution relationship based on Taylor's formula, combining the K-value identification criterion for the T1 phase tangential and bypass strengthening mechanism and the corresponding strength contribution model, simultaneously establishing the equivalent strain-dislocation density and T1 phase size relationship, superimposing the basic strength, dislocation strengthening and T1 phase strengthening contributions to calculate the yield strength, and establishing the equivalent strain-elongation relationship through polynomial fitting. This achieves a quantitative correlation from microscopic strengthening mechanism to macroscopic mechanical properties, providing a technical solution with a clear theoretical basis and strong engineering operability for predicting the mechanical properties and optimizing the process of cold-pressed pre-deformation of aluminum-lithium alloy forgings.

[0051] Furthermore, the basic strength of the aluminum-lithium alloy is the yield strength of the aluminum-lithium alloy after solution treatment.

[0052] The beneficial effects of the above-mentioned further scheme are: determining the basic strength, which prepares for solving the equivalent strain-yield strength relationship.

[0053] Furthermore, the secondary development of the finite element simulation software, compiling a finite element solver, specifically involves:

[0054] Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, the code was written in FORTRAN programming language, referring to the secondary development subroutine writing format of finite element simulation software.

[0055] Use the finite element software secondary development compiler to copy the written code to the finite element software secondary development subroutine node compilation file and update and save it.

[0056] The program is compiled based on the updated and saved files to produce a finite element solver.

[0057] The beneficial effects of the above-mentioned further scheme are as follows: This step is based on the quantitative relationship between equivalent strain and yield strength, elongation and T1 phase size. The code is written in FORTRAN language with reference to the secondary development subroutine format of finite element software. The code is imported into the compilation file of the secondary development subroutine node of finite element software through a standardized process to obtain a finite element operation solver. This realizes the embedding of the material microstructure evolution and macroscopic mechanical property model in finite element software. The solver has high calculation stability and fast convergence speed. It can directly couple the equivalent strain field and mechanical property prediction model in the cold pressing deformation process, providing an efficient digital tool for the process optimization of aluminum-lithium alloy forgings. It also has good model scalability and iterative mechanism.

[0058] Furthermore, the prediction of the verification alloy using the finite element method solver specifically involves: establishing a three-dimensional model of the verification alloy forging and a three-dimensional model of the cold pressing die; and using the finite element method solver to predict the spatial distribution of the verification alloy's yield strength, elongation, T1 phase diameter, and T1 phase thickness.

[0059] The beneficial effect of the above-mentioned further solutions is that they set up a verification process to ensure the prediction accuracy of the finite element calculation solver.

[0060] Furthermore, the fitting termination condition is as follows: the yield strength error and elongation error of the verification alloy are both less than the corresponding error thresholds; the yield strength error is the difference between the spatial distribution result of the actual yield strength of the verification alloy and the spatial distribution prediction result of the yield strength of the verification alloy; the elongation error is the difference between the spatial distribution result of the actual elongation of the verification alloy and the spatial distribution prediction result of the elongation of the verification alloy.

[0061] The beneficial effects of the above-mentioned further solutions are: providing an exit point for the fitting method while ensuring the prediction accuracy of the finite element calculation solver. Attached Figure Description

[0062] Figure 1 This is a flowchart of the method of the present invention.

[0063] Figure 2 True stress-strain curve for 7% compression.

[0064] Figure 3 Flowchart for taking the average equivalent strain of a stretched sample.

[0065] Figure 4 A schematic diagram of the XRD / EBSD sampling location and detection surface.

[0066] Figure 5 The drawing shows the dimensions and actual image of the tensile specimen.

[0067] Figure 6 The figures show the full width at half maximum (FWHM) fitting plots for different diffraction peaks and the fitting plots of equivalent strain and dislocation density.

[0068] Figure 7 Taylor factor distribution of Al-Cu-Li alloy under different equivalent variables.

[0069] Figure 8 A schematic diagram showing the T1 phase morphology and high-resolution T1 phase thickness displayed in HAADF images of samples with different equivalent strains.

[0070] Figure 9 The figure shows the fitting relationship between the diameter D and thickness t of samples with different equivalent strains and the equivalent strain.

[0071] Figure 10 Tensile curves of tensile specimens with different equivalent strain mean values.

[0072] Figure 11 This is a schematic diagram showing the matching relationship between specimens with different equivalent strain values ​​and tensile properties.

[0073] Figure 12 This diagram illustrates the contribution of the main strengthening mechanism to the sample yield strength and compares the experimental strength with the predicted strength.

[0074] Figure 13 This is a schematic diagram of the fitted curve of equivalent strain-elongation.

[0075] Figure 14 This is a schematic diagram of the spatial distribution of yield strength of a grid-patterned forging after cold pressing, created by finite element simulation.

[0076] Figure 15 This is a schematic diagram of the spatial distribution of elongation of a grid-patterned forging after cold pressing, created by finite element simulation.

[0077] Figure 16 This diagram illustrates the sampling location and verification results of the test specimens for the cold pressing deformation process of the grid-patterned forging. Detailed Implementation

[0078] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0079] like Figure 1 As shown, in one embodiment of the present invention, a method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings includes:

[0080] Experimental and numerical simulation analysis of cold pressing pre-deformation process of aluminum-lithium alloy were carried out to obtain the mean equivalent strain of target regions with different equivalent strain values, XRD microstructure specimens, EBSD microstructure specimens, TEM microstructure specimens and tensile specimens.

[0081] Based on the mean equivalent strain of each equivalent strain target region, XRD microstructure characterization sample, EBSD microstructure characterization sample and TEM microstructure characterization sample, the equivalent strain-dislocation density relationship, the average value of Taylor factor M, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship are obtained.

[0082] Based on the average value of Taylor factor M in each equivalent strain target region, tensile specimen, equivalent strain-dislocation density relationship, equivalent strain-T1 phase diameter relationship and equivalent strain-T1 phase thickness relationship, construct equivalent strain-yield strength relationship and equivalent strain-elongation relationship.

[0083] Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, secondary development of finite element simulation software was carried out, and a finite element calculation solver was compiled.

[0084] The spatial distribution prediction results of the verification alloy yield strength, elongation, T1 phase diameter and T1 phase thickness were obtained by using a finite element method solver.

[0085] Based on the spatial distribution prediction results of the verification alloy, determine whether the finite element method solver meets the fitting termination condition. If it does, then the spatial distribution prediction of the mechanical properties of the verification alloy is realized; otherwise, return to retrain the finite element method solver for fitting.

[0086] The acquisition of the mean equivalent strain value, XRD microstructure characterization specimen, EBSD microstructure characterization specimen, TEM microstructure characterization specimen, and tensile specimen of different equivalent strain target regions specifically includes:

[0087] Cold compression tests were conducted on solution-quenched aluminum-lithium alloys using pressure equipment, and stress-strain curve data were collected simultaneously.

[0088] Based on the stress-strain curve data, Young's modulus and stress-strain curves are obtained. A flow stress model is constructed based on Young's modulus and stress-strain curves, and the flow stress model is imported into finite element software to construct a material model for simulation.

[0089] The geometric models of aluminum-lithium alloy forgings and pressure fixtures under the same cold compression test conditions were drawn using 3D modeling software. They were then imported into finite element simulation software to establish a cold compression simulation model based on the material model used for simulation, and the simulation results of the cold compression specimens were output.

[0090] Extract the equivalent strain spatial distribution data of the cold-compressed specimen from the simulation results, determine multiple equivalent strain target regions along the thickness direction of the cold-compressed specimen, and based on the equivalent strain spatial distribution data, randomly select several points in each equivalent strain target region to obtain the equivalent strain mean value of the corresponding equivalent strain target region.

[0091] XRD and EBSD microstructure characteristics of cold-compressed specimens were performed on the target regions of each equivalent variable value using wire cutting.

[0092] The cold-compression specimens were aged, and then TEM microstructure was performed on the target regions of each equivalent strain value using the wire cutting method. Specimen sampling and tensile specimen sampling were also performed.

[0093] The obtained equivalent strain-dislocation density relationship, the average value of the Taylor factor M, the equivalent strain-T1 phase diameter relationship, and the equivalent strain-T1 phase thickness relationship are as follows:

[0094] The XRD-characterized samples were characterized based on the target regions of each equivalent strain value. The dislocation density value of each XRD-characterized sample was calculated. Based on the dislocation density value of each XRD-characterized sample and the mean equivalent strain value of each target region, the equivalent strain-dislocation density relationship was established:

[0095]

[0096] in, For equivalent effect Dislocation density at time; For equivalent change; , and All are equivalent strain-dislocation density fitting coefficients;

[0097] The EBSD tissue samples were characterized based on the target regions of each equivalent variable value. The distribution of the Taylor factor M was statistically analyzed, and the average value of the Taylor factor M was calculated.

[0098] The TEM microstructure of the samples was characterized based on the target regions of each equivalent strain value. The diameter and thickness of the T1 phase were statistically analyzed. Based on the T1 phase diameter, T1 phase thickness, and the mean equivalent strain of each target region of the TEM microstructure of the samples, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship were established.

[0099]

[0100]

[0101] in, For equivalent effect The diameter of phase T1 at that time; and All are equivalent strain-T1 phase diameter fitting coefficients; For equivalent effect The thickness of the T1 phase at that time; , and All are equivalent strain-T1 phase thickness fitting coefficients.

[0102] The construction of the equivalent strain-yield strength relationship and the equivalent strain-elongation relationship is specifically as follows:

[0103] Based on the tensile specimens in the target regions of each equivalent strain value, mechanical properties were tested to obtain the yield strength and elongation data of each tensile specimen.

[0104] Based on the yield strength of each tensile specimen, the contribution of dislocation strengthening to the yield strength is calculated using Taylor's formula, and a relationship between dislocation density and dislocation strength contribution is constructed.

[0105] Establish criteria for identifying T1 tangential over-enhancement and bypass enhancement mechanisms:

[0106]

[0107] in, To identify the criteria; The diameter of phase T1; The thickness of phase T1; For the statistical average diameter of phase T1, when When >10, the dislocation bypass mechanism is used; when When the diameter is ≤10, the dislocations are sheared; D and thickness t Calculate the reinforcement mechanism corresponding to each equivalent variable value;

[0108] Based on the identification criteria for T1 phase over-strengthening and bypass strengthening mechanisms, the strength contributions of T1 phase diameter and T1 phase thickness to over-strengthening and bypass strengthening are constructed:

[0109]

[0110]

[0111] in, For equivalent effect The contribution of T1 phase diameter and T1 phase thickness to the strength of shear strengthening; Shear modulus; It is the Bergman vector; For equivalent effect The diameter of phase T1 at that time; For equivalent effect The thickness of the T1 phase at that time; For equivalent effect The contribution of the T1 phase diameter and T1 phase thickness to the strength of bypass reinforcement; For interface energy; For dislocation line tension;

[0112] Combining the equivalent strain-dislocation density relationship with the dislocation density-dislocation intensity contribution relationship, we obtain the relationship between equivalent strain and dislocation intensity contribution:

[0113]

[0114] in, For equivalent effect The contribution of dislocation strength at time; For equivalent change; The average value of the Taylor factor M; These are material constants; For equivalent effect Dislocation density at time;

[0115] By combining the equivalent strain-T1 phase diameter relationship, the equivalent strain-T1 phase thickness relationship, the strength contribution of T1 phase diameter and T1 phase thickness to shear strengthening, and the strength contribution of T1 phase diameter and T1 phase thickness to bypass strengthening, we obtain the equivalent strain-shear strengthening relationship and the equivalent strain-bypass strengthening relationship.

[0116] By superimposing the basic strength of aluminum-lithium alloy, the relationship between equivalent strain and dislocation strength contribution, the equivalent strain-through strengthening relationship, and the equivalent strain-bypass strengthening relationship, the equivalent strain-yield strength relationship is obtained.

[0117] Based on the elongation data of each tensile specimen and the mean equivalent strain of each equivalent strain target region, the equivalent strain-elongation relationship is constructed as follows:

[0118]

[0119] in, Elongation; , and All are equivalent strain-elongation fitting coefficients.

[0120] The basic strength of the aluminum-lithium alloy is the yield strength of the aluminum-lithium alloy after solution treatment.

[0121] In this embodiment, the yield strength of the alloy is composed of the basic strength, the contribution of dislocation strength and the contribution of T1 phase strength. The basic strength is obtained through the following process: After the alloy involved in this invention has undergone solid solution treatment, the yield strength of the sample in this state is considered to be the basic strength, with a value of 163 MPa.

[0122] The secondary development of the finite element simulation software, specifically the compilation of a finite element solver, involves:

[0123] Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, the code was written in FORTRAN programming language, referring to the secondary development subroutine writing format of finite element simulation software.

[0124] Use the finite element software secondary development compiler to copy the written code to the finite element software secondary development subroutine node compilation file and update and save it.

[0125] The program is compiled based on the updated and saved files to produce a finite element solver.

[0126] The method of using a finite element method solver to predict the verification alloy is as follows: for the verification alloy, a three-dimensional model of the forging and a three-dimensional model of the cold pressing die of the verification alloy are established. Based on the three-dimensional model of the forging and the three-dimensional model of the cold pressing die of the verification alloy, a finite element method solver is used to make predictions to obtain the spatial distribution prediction results of the verification alloy's yield strength, elongation, T1 phase diameter and T1 phase thickness.

[0127] The fitting termination condition is as follows: the yield strength error and elongation error of the verification alloy are both less than the corresponding error thresholds; the yield strength error is the difference between the spatial distribution result of the actual yield strength of the verification alloy and the spatial distribution prediction result of the yield strength of the verification alloy; the elongation error is the difference between the spatial distribution result of the actual elongation of the verification alloy and the spatial distribution prediction result of the elongation of the verification alloy.

[0128] Example 2

[0129] The material used in this embodiment is 2050 aluminum-lithium alloy.

[0130] This embodiment discloses a method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings (technical roadmap as shown in the figure). Figure 1 (As shown), including the following steps:

[0131] Step 1: Based on cold compression tests and simulated cold compression tests, determine the quantitative relationship between the pre-deformation amount of aluminum-lithium alloy under cold compression and the equivalent strain value under simulated cold compression:

[0132] (1) In this embodiment, the sample is a rectangular sample of 12mm×18mm×30mm, with a compression rate of 0.005s-1, and compression tests of 1%, 3%, 5% and 7% are carried out respectively. Figure 2 The true stress-strain curve corresponding to a 7% compression.

[0133] Pre-compression tests with different compression amounts were conducted using pressure equipment. The true stress-strain curves under 7% compression were then imported into DEFORM-3D software to construct a material rheological constitutive model, thereby enabling the corresponding simulated cold compression experiments.

[0134] (2) The size of the finite element simulation specimen was set to 12 mm × 18 mm × 30 mm, which is consistent with the actual test size. The specimen mesh was set to a tetrahedral mesh with a mesh size of 10,000. The material properties of the mesh were defined as Young's modulus and stress-strain data in step (1). In the model setting of the mold, the deformation of the mold itself was ignored, the mold was set to be rigid, the upper mold (Top Die) was defined as the main deformation mold, and a displacement load was applied along the height of the specimen. The loading rate was set to 0.015 mm / s. The mold movement termination condition was set to automatically stop the calculation when the distance between the upper and lower molds reached the preset compression amount (Δh = 0.3~2.1 mm). The simulation step size was set to the main mold process: 0.01 mm / Step. Then, the simulation DB file was generated and calculated. Independent calculation tasks were established for different pre-deformation amounts (1%, 3%, 5%, 7%).

[0135] (3) The Von Mises equivalent strain is used to characterize the degree of plastic deformation of the alloy. This parameter effectively quantifies the deformation level of the material under uniaxial stress by converting the complex three-dimensional strain tensor into a scalar form. Based on the post-processing module of the finite element software, the cold pressing simulation results are transferred to the corresponding geometric domain of the tensile specimen through data mapping. Nineteen feature points are selected in the main diagonal direction of the fracture section according to an equidistant grid. The arithmetic mean of the Von Mises strain values ​​of the feature point set is used as the equivalent cold deformation characterization parameter. Tensile specimens at 1 / 8 and 1 / 2 of the deformation are taken for each deformation. The implementation process and spatial distribution pattern of the feature points are detailed in [link to relevant documentation]. Figure 3 As shown in Table 1, the equivalent strain mean of the corresponding samples was obtained using the above method. Table 2 shows the sample numbers.

[0136] Table 1. Mean equivalent strain at fracture sections of tensile specimens at different locations

[0137]

[0138] Table 2. Numbers corresponding to different samples

[0139]

[0140] Before aging, take a 2mm × 2mm × 3mm cube sample from the center of the specimen for XRD and EBSD testing. The sampling location and the direction of the testing surface are as follows: Figure 4 As shown in the figure, parallel tests with the same heat treatment and cold pressing processes were conducted, and TEM tissue characterization samples were taken from the same locations.

[0141] Tensile specimens were taken at 1 / 8 and 1 / 2 of the length of the cold-compression specimens (after aging) with pre-deformation amounts of 1%, 3%, 5%, and 7%. The dimensions and actual drawings of the tensile specimens are shown below. Figure 5 As shown.

[0142] Step 2: Perform XRD characterization and dislocation density modeling:

[0143] Before XRD testing, the small cube samples from step one were polished to a glossy finish using 400#-3000# silicon carbide sandpaper to eliminate wire cutting marks. Subsequently, they were electropolished in a 30mL:70mL HNO3:CH3OH solution at -30℃. The full width at half maximum (FWHM) and peak value of the corresponding diffraction peaks were measured using XRD, and the dislocation density was calculated. The dislocation density values ​​calculated for different surfaces were matched with the mean equivalent strain to obtain a data set of dislocation density-mean equivalent strain. The calculation results and fitting relationship are shown below. Figure 6 As shown in (a) and (b), The relationship is shown in equation (1).

[0144] (1)

[0145] The samples, after XRD analysis, were characterized by EBSD under a JSMS-7800F field emission electron microscope. The Taylor factor M distribution of different equivalent strain samples was analyzed using OIM software, such as... Figure 7 As shown, the Taylor factor of all grains was averaged to obtain M = 2.98.

[0146] TEM samples were thinned using a GATAN PIPS II ion milling system and characterized using a TALOS F200X transmission electron microscope. T1 phase characteristics were imaged along the zone axis; HAADF images were used to observe the T1 phase diameter; and high-resolution images were used to observe the T1 phase thickness. The results are as follows: Figure 8 As shown.

[0147] For each sample, the diameters of at least 200 T1 phases were statistically analyzed and averaged. Similarly, the thicknesses of at least 15 T1 phases in the high-resolution image were statistically analyzed and averaged. The fitting relationship between the statistical results and the equivalent strain is shown in the figure below. Figure 9 As shown. T1 phase diameter D and thickness t Fitting relationship with equivalent strain ( - D )and( - t As shown in equations (2) and (3) respectively.

[0148] (2)

[0149] (3)

[0150] Step 3: Establish the correspondence between dislocation density, T1 phase diameter and thickness, yield strength, equivalent strain and elongation:

[0151] Tensile specimens were prepared at the corresponding positions in step one using wire cutting. After wire cutting, the surface was successively polished using silicon carbide sandpaper ranging from 400# to 3000#. Tensile tests were conducted on a Kamurath Weiss DDS4 in-situ tensile testing machine at a tensile rate of 5 μm / s. The results are as follows: Figure 10 As shown.

[0152] By matching specimens with different equivalent strain values ​​to their corresponding tensile properties, the trends of equivalent strain value in relation to yield strength, tensile strength, and elongation can be obtained, as follows: Figure 11 As shown.

[0153] The dislocation density and T1 phase strengthening contribution in step two are calculated according to the following formula:

[0154] (4)

[0155] In the formula For yield strength, Based on strength, Contributes to dislocation strengthening. It contributes to the enhancement of the T1 phase.

[0156] Based on experience, the value is taken as 113 MPa. The dislocation strengthening contribution is calculated according to Taylor's formula, and the coupled equivalent strain expression is shown in Equation (4). The strengthening of the T1 phase originates from the interaction between the precipitate and the dislocation, depending on whether the precipitate is bypassed or sheared by the dislocation. The coupled equivalent strain and the strengthening contribution based on the bypass and shearing mechanism are expressed in Equations (5) and (6):

[0157] (5)

[0158] In the formula, M The Taylor factor is taken as the average value of the EBSD Taylor factor distribution, which is 2.98. α Let be a constant, taken as 0.475. G The shear modulus is taken as 28 GPa; b The is the Burgers vector, taken as 0.286 nm.

[0159] (6)

[0160] In the formula D The diameter of phase T1, t The thickness of phase T1.

[0161] (7)

[0162] In the formula The interface energy is taken as 0.107 J × m⁻². For dislocation tension, approximately equal to Gb 2 / 2.

[0163] This invention proposes a critical criterion for dislocation bypass / shear modes based on the diameter and thickness of the T1 phase. K ( D , t Its specific formula is:

[0164] (8)

[0165] In the formula, The average diameter of phase T1, when K When >10, the dislocation bypass mechanism is used; when K When the diameter is ≤10, the dislocations operate via a shear mechanism.D and thickness t The enhancement mechanism corresponding to each equivalent variable value was calculated. When the equivalent variable value was 0.033, it was determined to be a shearing mechanism; when the equivalent variable value was 0.011, 0.066 and 0.087, it was determined to be a bypass mechanism.

[0166] Based on the above model formulas and criteria, the contributions of different strengthening methods to yield strength are as follows: Figure 12 As shown, it can be seen that as the equivalent strain increases, dislocation strengthening increases continuously, while T1 phase strengthening decreases. This is because the size of the T1 phase decreases with increasing strain.

[0167] Furthermore, by fitting a mathematical model based on the equivalent strain-elongation data points, a functional model of the equivalent strain-elongation can be obtained. As shown in equation (9), its specific fitting curve is as follows: Figure 13 As shown.

[0168] (9)

[0169] Step 4: Develop a DEFORM software solver for the equivalent strain-yield strength / elongation / T1 phase diameter / thickness model:

[0170] The data contained in the solver is the equivalent strain-yield strength / elongation / T1 diameter / thickness model obtained in step three; the model obtained in step three is written using FORTRAN language, and its main logic is: (1) extract the equivalent strain values ​​in the finite element nodes in each step of the calculation results, and represent them as TEPS in the FORTRAN program; (2) substitute the TEPS values ​​into the formulas listed in step three, and calculate the yield strength, elongation, T1 diameter and thickness values ​​at each node position respectively; (3) update and store the calculated values ​​in the node data; (4) the yield strength, elongation, T1 diameter and thickness values ​​obtained from each node data form a spatial distribution cloud map, and obtain the performance spatial distribution prediction data; (5) update the calculation step and repeat the above steps.

[0171] The above program was compiled using the ABSOFT PRO FORTRAN compiler to obtain the DEF_SIM.exe solver, which can be called during finite element calculations.

[0172] Step 5: Conduct finite element simulation prediction for complex aluminum-lithium alloy forgings:

[0173] (1) Establish a finite element model of the forging to be predicted with complex geometric features. The data contained in the finite element model is the material package in step one.

[0174] In this embodiment, to verify the model's ability to predict the yield strength and elongation of complex forgings after cold pressing, a irregularly shaped forging with a "grid" pattern was designed using CATIA 3D modeling software. Corresponding upper and lower cold pressing dies were designed, and STL files were exported and imported into DEFORM software. In DEFORM software, the forging to be predicted was meshed with a grid size of 100,000.

[0175] (2) Define the cold pressing process conditions, set the spatial positioning relationship, contact conditions and calculation step size of the above three models, and set the movement speed and stopping conditions of the main mold;

[0176] In this embodiment, the cold pressing assembly consists of three parts: the billet, and upper and lower flat die plates. The upper die is set as a rigid body with a moving speed of 0.05 mm / s in the -Z direction, while the lower die is a stationary rigid body. The stopping condition is set when the distance between the upper and lower dies is compressed to 97% of the total height of the forging.

[0177] (3) Perform simulation calculations to obtain the spatial distribution of mechanical properties and T1 phase characteristics of the forging after cold pressing;

[0178] In this embodiment, a DB file is generated according to the above-mentioned cold-pressing simulation test parameter settings, and the DEF_SIM.exe solver obtained in step four is called to perform the solution calculation. Figure 14 and Figure 15 Contour maps of mechanical properties (yield strength and elongation) and microstructure (T1 phase diameter and thickness) in different directions are presented based on the simulation results.

[0179] Step Six: Experimental Verification of Cold Pressing Process for Forgings:

[0180] (1) Take the “grid” forging and conduct a cold pressing test on a 300-ton hydraulic press. The experimental parameters are the same as those in step five.

[0181] (2) After compression, tensile samples of the same size as those in step one were taken from different locations on the forging using wire cutting. The mechanical properties and microstructure were tested using the tensile parameters and TEM characterization process described in step three. Yield strength, elongation, T1 phase diameter, and thickness were statistically analyzed. The process test results and sampling locations are as follows: Figure 16 As shown, the coefficient of determination R is used. 2 The correlation between experimental and predicted values ​​is shown, with the yield strength model at 0.94, the elongation model at 0.86, the T1 phase diameter model at 0.94, and the T1 phase thickness model at 0.93. Within the allowable error range of the technical approach, this indicates that the prediction results have high accuracy.

[0182] This invention clarifies the mapping relationship between equivalent strain and mechanical properties at different spatial locations of a sample based on finite element simulation. Based on this, a mathematical model of yield strength, elongation, T1 phase characteristics, and equivalent strain is constructed, enabling finite element simulation prediction of the spatial distribution of yield strength, elongation, and T1 phase characteristics during the cold pressing process of the alloy forging. Process experiments on complex aluminum-lithium alloy forgings were conducted, and combined with mechanical property analysis, the simulation prediction results were verified, ensuring the reliability of the prediction method of this invention.

Claims

1. A method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings, characterized in that, include: Experimental and numerical simulation analysis of cold pressing pre-deformation process of aluminum-lithium alloy were carried out to obtain the mean equivalent strain of target regions with different equivalent strain values, XRD microstructure specimens, EBSD microstructure specimens, TEM microstructure specimens and tensile specimens. Based on the mean equivalent strain value of each equivalent strain target region, XRD microstructure characterization sample, EBSD microstructure characterization sample and TEM microstructure characterization sample, the equivalent strain-dislocation density relationship, the average value of Taylor factor M, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship are obtained. Based on the average value of the Taylor factor M of each equivalent strain target region, the tensile specimen, the equivalent strain-dislocation density relationship, the equivalent strain-T1 phase diameter relationship, and the equivalent strain-T1 phase thickness relationship, the equivalent strain-yield strength relationship and the equivalent strain-elongation relationship are constructed; specifically, the construction of the equivalent strain-yield strength relationship and the equivalent strain-elongation relationship is as follows: Based on the tensile specimens in the target regions of each equivalent strain value, mechanical properties were tested to obtain the yield strength and elongation data of each tensile specimen. Based on the yield strength of each tensile specimen, the contribution of dislocation strengthening to the yield strength is calculated using Taylor's formula, and a relationship between dislocation density and dislocation strength contribution is constructed. Establish criteria for identifying T1 tangential over-enhancement and bypass enhancement mechanisms: in, To identify the criteria; The diameter of phase T1; The thickness of phase T1; For the statistical average diameter of phase T1, when When >10, the dislocation bypass mechanism is used; when When the value is ≤10, the dislocations are sheared. Based on the identification criteria for T1 phase over-strengthening and bypass strengthening mechanisms, the strength contributions of T1 phase diameter and T1 phase thickness to over-strengthening and bypass strengthening are constructed: in, For equivalent effect The contribution of T1 phase diameter and T1 phase thickness to the strength of shear strengthening; Shear modulus; It is the Bergman vector; For equivalent effect The diameter of phase T1 at that time; For equivalent effect The thickness of the T1 phase at that time; For equivalent effect The contribution of the T1 phase diameter and T1 phase thickness to the strength of bypass reinforcement; For interface energy; For dislocation line tension; Combining the equivalent strain-dislocation density relationship with the dislocation density-dislocation intensity contribution relationship, we obtain the relationship between equivalent strain and dislocation intensity contribution: in, For equivalent effect The contribution of dislocation strength at time; For equivalent change; The average value of the Taylor factor M; These are material constants; For equivalent effect Dislocation density at time; By combining the equivalent strain-T1 phase diameter relationship, the equivalent strain-T1 phase thickness relationship, the strength contribution of T1 phase diameter and T1 phase thickness to shear strengthening, and the strength contribution of T1 phase diameter and T1 phase thickness to bypass strengthening, we obtain the equivalent strain-shear strengthening relationship and the equivalent strain-bypass strengthening relationship. By superimposing the basic strength of aluminum-lithium alloy, the relationship between equivalent strain and dislocation strength contribution, the equivalent strain-through strengthening relationship, and the equivalent strain-bypass strengthening relationship, the equivalent strain-yield strength relationship is obtained. Based on the elongation data of each tensile specimen and the mean equivalent strain of each equivalent strain target region, the equivalent strain-elongation relationship is constructed as follows: in, Elongation; , and All are equivalent strain-elongation fitting coefficients; Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, secondary development of finite element simulation software was carried out, and a finite element calculation solver was compiled. The spatial distribution prediction results of the verification alloy yield strength, elongation, T1 phase diameter and T1 phase thickness were obtained by using a finite element method solver. Based on the spatial distribution prediction results of the verification alloy, determine whether the finite element operation solver meets the fitting termination condition. If so, realize the spatial distribution prediction of the mechanical properties of the verification alloy; otherwise, return to re-train the finite element operation solver fitting.

2. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The acquisition of the mean equivalent strain value, XRD microstructure characterization specimen, EBSD microstructure characterization specimen, TEM microstructure characterization specimen, and tensile specimen of different equivalent strain target regions specifically includes: Cold compression tests were conducted on solution-quenched aluminum-lithium alloys using pressure equipment, and stress-strain curve data were collected simultaneously. Based on the stress-strain curve data, Young's modulus and stress-strain curves are obtained. A flow stress model is constructed based on Young's modulus and stress-strain curves, and the flow stress model is imported into finite element software to construct a material model for simulation. The geometric models of aluminum-lithium alloy forgings and pressure fixtures under the same cold compression test conditions were drawn using 3D modeling software. They were then imported into finite element simulation software to establish a cold compression simulation model based on the material model used for simulation, and the simulation results of the cold compression specimens were output. Extract the equivalent strain spatial distribution data of the cold-compressed specimen from the simulation results, determine multiple equivalent strain target regions along the thickness direction of the cold-compressed specimen, and based on the equivalent strain spatial distribution data, randomly select several points in each equivalent strain target region to obtain the equivalent strain mean value of the corresponding equivalent strain target region. XRD and EBSD microstructure characteristics of cold-compressed specimens were performed on the target regions of each equivalent variable value using wire cutting. The cold-compression specimens were aged, and then TEM microstructure was performed on the target regions of each equivalent strain value using the wire cutting method. Specimen sampling and tensile specimen sampling were also performed.

3. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The obtained equivalent strain-dislocation density relationship, the average value of the Taylor factor M, the equivalent strain-T1 phase diameter relationship, and the equivalent strain-T1 phase thickness relationship are as follows: The XRD-characterized samples were characterized based on the target regions of each equivalent strain value. The dislocation density value of each XRD-characterized sample was calculated. Based on the dislocation density value of each XRD-characterized sample and the mean equivalent strain value of each target region, the equivalent strain-dislocation density relationship was established: in, For equivalent effect Dislocation density at time; For equivalent change; , and All are equivalent strain-dislocation density fitting coefficients; The EBSD tissue samples were characterized based on the target regions of each equivalent variable value. The distribution of the Taylor factor M was statistically analyzed, and the average value of the Taylor factor M was calculated. The TEM microstructure of the samples was characterized based on the target regions of each equivalent strain value. The diameter and thickness of the T1 phase were statistically analyzed. Based on the T1 phase diameter, T1 phase thickness, and the mean equivalent strain of each target region of the TEM microstructure of the samples, the equivalent strain-T1 phase diameter relationship and the equivalent strain-T1 phase thickness relationship were established. in, For equivalent effect The diameter of phase T1 at that time; and All are equivalent strain-T1 phase diameter fitting coefficients; For equivalent effect The thickness of the T1 phase at that time; , and All are equivalent strain-T1 phase thickness fitting coefficients.

4. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The basic strength of the aluminum-lithium alloy is the yield strength of the aluminum-lithium alloy after solution treatment.

5. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The secondary development of the finite element simulation software, specifically the compilation of a finite element calculation solver, is as follows: Based on the equivalent strain-yield strength relationship, equivalent strain-elongation relationship, equivalent strain-T1 phase diameter relationship, and equivalent strain-T1 phase thickness relationship, the code was written in FORTRAN programming language, referring to the secondary development subroutine writing format of finite element simulation software. Use the finite element software secondary development compiler to copy the written code to the finite element software secondary development subroutine node compilation file and update and save it. The program is compiled based on the updated and saved files to produce a finite element solver.

6. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The method of using a finite element method solver to predict the verification alloy is as follows: for the verification alloy, a three-dimensional model of the forging and a three-dimensional model of the cold pressing die of the verification alloy are established. Based on the three-dimensional model of the forging and the three-dimensional model of the cold pressing die of the verification alloy, a finite element method solver is used to make predictions to obtain the spatial distribution prediction results of the verification alloy's yield strength, elongation, T1 phase diameter and T1 phase thickness.

7. The method for predicting the spatial distribution of mechanical properties of aluminum-lithium alloy forgings according to claim 1, characterized in that, The fitting termination condition is as follows: the yield strength error and elongation error of the verification alloy are both less than the corresponding error thresholds; the yield strength error is the difference between the spatial distribution result of the actual yield strength of the verification alloy and the spatial distribution prediction result of the yield strength of the verification alloy; the elongation error is the difference between the spatial distribution result of the actual elongation of the verification alloy and the spatial distribution prediction result of the elongation of the verification alloy.

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