Aluminum alloy multi-axial fatigue life prediction method based on non-proportional loading effect

Abstract

The embodiment of the invention relates to the field of mechanical engineering and material science, in particular to an aluminum alloy multi-axial fatigue life prediction method based on a non-proportional loading effect. A specific embodiment of the method comprises the following steps: carrying out uniaxial tensile mechanical test treatment on the aluminum alloy to generate stress-strain data; determining a candidate plane set based on the stress-strain data; based on the stress-strain data, determining a stress tensor and a strain tensor corresponding to each candidate plane in the candidate plane set, and obtaining a stress tensor set and a strain tensor set; determining a critical plane based on the stress tensor set, the strain tensor set and the candidate plane set; determining a damage parameter based on the damage model and the critical plane; and predicting the fatigue life of the multi-axial load based on the damage parameter and a Manson-Coffin equation. According to the embodiment, the fatigue life of the aluminum alloy cross beam of the vulcanizing machine can be accurately predicted.

Description

Technical Field

[0001] The embodiments of this application relate to the fields of mechanical engineering and materials science, specifically to a method for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects. Background Technology

[0002] In modern mechanical equipment and major industrial facilities, critical load-bearing components typically operate under complex alternating load environments for extended periods. Due to geometric discontinuities such as holes, chamfers, and connection interfaces, localized areas of the structure often exhibit significant multiaxial stress-strain states. Numerous engineering failure cases demonstrate that multiaxial fatigue, especially non-proportional multiaxial fatigue, is one of the main causes of premature failure in metal structures.

[0003] In existing engineering projects, multiaxial fatigue life prediction methods mainly include the equivalent stress method, the equivalent strain method, the energy method, and multiaxial fatigue models based on the critical plane method. Among them, the critical plane method, developed based on experimental observations of crack nucleation and propagation during loading, has good multiaxial fatigue life assessment capabilities and clear physical significance, and therefore has been widely used.

[0004] To improve prediction accuracy under non-proportional loading conditions, several improved models based on the critical plane method have been proposed, such as the SWT (Stable Wavelet Transform) model, the FS (Feature Selection) model, and the MSWT (Multi-Scale Wavelet Transform) model. These models, to some extent, incorporate the influence of normal stress or shear energy on fatigue damage, but still suffer from problems such as a large number of model parameters, high engineering calibration costs, or insufficient prediction stability under specific materials and load paths. Especially for typical engineering materials such as 7050 series high-strength aluminum alloys, under complex non-proportional loading conditions, the aforementioned models still struggle to simultaneously achieve both prediction accuracy and engineering applicability.

[0005] Therefore, it is necessary to develop a new multiaxial fatigue life prediction method that can reasonably characterize the additional hardening effect under non-proportional loading conditions, has a clear model form, clear physical meaning of parameters, and is easy to promote and apply in engineering. Summary of the Invention

[0006] The summary section of this application is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description section below. This summary section is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0007] Some embodiments of this application propose a method, apparatus, computer device, and computer-readable storage medium for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects, in order to solve one or more of the technical problems mentioned in the background section above.

[0008] In a first aspect, some embodiments of this application provide a method for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects. The method includes: performing uniaxial tensile mechanical tests on the aluminum alloy to generate stress-strain data; determining a set of candidate planes based on the stress-strain data; determining the stress tensor and strain tensor corresponding to each candidate plane in the set of candidate planes based on the stress-strain data, thereby obtaining a set of stress tensors and a set of strain tensors; determining a critical plane based on the set of stress tensors, the set of strain tensors, and the set of candidate planes; determining damage parameters based on a damage model and the critical plane; and predicting the fatigue life under multiaxial loads based on the damage parameters and the Manson-Coffin equation.

[0009] Secondly, some embodiments of this application provide a device for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects. The device includes: a testing unit configured to perform uniaxial tensile mechanical testing on the aluminum alloy to generate stress-strain data; a first determining unit configured to determine a set of candidate planes based on the stress-strain data; a second determining unit configured to determine the stress tensor and strain tensor corresponding to each candidate plane in the set of candidate planes based on the stress-strain data, thereby obtaining a set of stress tensors and a set of strain tensors; a third determining unit configured to determine a critical plane based on the set of stress tensors, the set of strain tensors, and the set of candidate planes; a fourth determining unit configured to determine damage parameters based on a damage model and the critical plane; and a prediction unit configured to predict the fatigue life of multiaxial loads based on the damage parameters and the Manson-Coffin equation.

[0010] Thirdly, this application also provides a computer device, which includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, it implements the method described in any implementation of the first aspect above.

[0011] Fourthly, this application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the method described in any implementation of the first aspect above.

[0012] The above embodiments of this application have the following beneficial effects: Firstly, the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects, as described in some embodiments of this application, offers high prediction accuracy: In experimental verification of 7050 aluminum alloy, all data points of the new model fall within the 1.5x error band, outperforming traditional models. Secondly, it has strong path applicability: Non-proportional additional hardening is directly quantified through the normal stress correction term, making it suitable for proportional, 45°, and 90° non-proportional loading paths. Thirdly, it is engineering-friendly: Only conventional material parameters are required, no complex calibration is needed, and it can be integrated into finite element software such as Abaqus (a finite element software for engineering simulation). Fourthly, it closely matches the microscopic mechanism: The model is based on the critical plane method, consistent with the physical mechanism of fatigue crack initiation at the maximum shear strain surface, improving theoretical reliability. Finally, it has wide applicability: Verified in a vulcanizing machine aluminum beam case study, the predicted life error compared to the measured value is approximately 20%, making it suitable for the durability design of aluminum alloy structures in aerospace, rail transportation, and other fields. Attached Figure Description

[0013] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0014] Figure 1 This is a flowchart of some embodiments of the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effect according to this application; Figure 2 This is a flowchart illustrating some embodiments of the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effect according to this application. Figure 3 This is a schematic diagram of the critical surface under multiaxial stress. Figure 4 It is a schematic diagram of the geometry of a smooth, thin-walled circular ring sample; Figure 5 This is a schematic diagram of the strain path; Figure 6 This is a schematic diagram of the structure of some embodiments of the aluminum alloy multiaxial fatigue life prediction device based on non-proportional loading effect according to this application. Figure 7 This is a schematic diagram of the structure of a computer device suitable for implementing some embodiments of this application; Figure 8 This is a comparison chart of the relationship between the predicted values ​​and experimental values ​​from the PN model; Figure 9 These are box plots of errors for each model; Figure 10 This is a diagram of the vulcanizing machine experimental setup and strain test arrangement; Figure 11 This is a schematic diagram of the strain test data on the inside and outside of the aluminum beam and bolts; Figure 12 This is a comparison chart of simulation and experimental data; Figure 13 This is a comparison chart of the predicted life and experimental value of the PN model in the aluminum beam of the vulcanizing machine. Detailed Implementation

[0015] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0016] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0017] It should be noted that the concepts of "first" and "second" mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0018] It should be noted that the terms "a" and "a plurality of" used in this application are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0019] The names of the messages or information exchanged between multiple devices in the embodiments of this application are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0020] The present application will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] Figure 1 The flowchart 100 illustrates some embodiments of the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects according to this application. This multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects includes the following steps: Step 101: Perform uniaxial tensile mechanical testing on the aluminum alloy to generate stress-strain data.

[0022] In some embodiments, the implementer of the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects can perform uniaxial tensile mechanical tests on the aluminum alloy to generate stress-strain data. In practice, the implementer can perform uniaxial tensile mechanical tests on the aluminum alloy to generate stress-strain data through the following steps: First, a dumbbell-shaped specimen is prepared and its original dimensions are accurately measured. The specimen is then mounted on a universal testing machine, and an extensometer is installed to accurately measure the deformation of the gauge length. At the start of the test, a tensile load is applied at a constant rate (usually strain-controlled), and the load and strain data are recorded synchronously by the extensometer and force sensor until the specimen fractures, thereby obtaining the original load-displacement curve. Subsequently, the original load-displacement curve is converted into a stress-strain curve (stress-strain data) with engineering stress (load divided by the original cross-sectional area) and engineering strain (deformation divided by the original gauge length) as the core. Based on this, the elastic modulus (E) is obtained by calculating the slope of the initial linear elastic segment of the curve. Since aluminum alloys do not have a distinct yield plateau, their yield strength is usually expressed as the specified plastic extension strength Rp0.2 (specified non-proportional extension strength), that is, a straight line parallel to the elastic segment is drawn with a 0.2% offset on the strain axis, and the stress value at the intersection of this line and the stress-strain curve is Rp0.2. The tensile strength (Rm) directly corresponds to the stress value at the highest point of the curve, that is, the maximum load divided by the original cross-sectional area. As an example, the flowchart of this application is as follows. Figure 2 As shown. Figure 2 A flowchart illustrating some embodiments of the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects according to this application is shown.

[0023] Step 102: Determine the candidate plane set based on stress and strain data.

[0024] In some embodiments, the execution entity may determine a set of candidate planes based on the stress-strain data. In practice, the execution entity may determine a set of candidate planes based on the stress-strain data through the following steps: The first step is to represent the stress-strain state at key nodes of the material using the stress-strain tensor, and then calculate the origin. The three unit vectors of a point Determine the second reference coordinate system: , in, , , Represents a unit vector. , , express Components on the x, y, and z axes , , express Components on the x, y, and z axes , , express Components on the x, y, and z axes This represents the angle between the projection of a unit vector onto the xy-plane and the x-axis. This represents the angle between the unit vector and the z-axis. Here, the second reference coordinate system can be a local coordinate system established based on the candidate critical plane, used to project the global stress-strain tensor onto this plane, thereby extracting the normal and shear components to calculate fatigue damage. Material critical nodes can be stress / strain concentration points. Material critical nodes are locations with the maximum stress gradient and the highest amplitude, such as the notch root, weld toe, and fillet transition zone. The stress-strain history at this point directly determines the crack initiation life.

[0025] The second step is to determine the direction vector. The direction vector is shown in the following formula: , in, Represents any direction vector on the plane. , , express Components on the x, y, and z axes express and The included angle. As an example, a schematic diagram of the critical surface under multiaxial stress is shown below. Figure 3 As shown. Figure 3 The definition of the local coordinate system and the critical plane azimuth angle is shown.

[0026] The third step involves determining the plane normal stress, plane tangential stress, plane normal strain, and plane shear strain based on the direction vector and the second reference coordinate system using the following formulas: , in, Represents the normal stress in a plane. Represents the tangential stress in the plane. Represents the normal strain in a plane. Represents plane shear strain. Indicates time, Represents the stress tensor. This represents the strain tensor. In practice, in fatigue analysis, the stress tensor... and strain tensor It varies with time (or load step). This formula calculates the plane stress / strain components at a specific instant, and is used to describe the change of this physical quantity with time throughout the entire cycle.

[0027] The fourth step involves combining the shear strain calculated using the above formula with the stress-strain data, and then iterating through all possible planes (azimuth angles). ∈ (0°, 360°), Inclination ∈(0°, 180°)), to obtain the candidate plane set.

[0028] Step 103: Based on the stress and strain data, determine the stress tensor and strain tensor corresponding to each candidate plane in the candidate plane set, and obtain the stress tensor set and strain tensor set.

[0029] In some embodiments, the execution entity can determine the stress tensor and strain tensor corresponding to each candidate plane in the candidate plane set based on the stress-strain data, thus obtaining a stress tensor set and a strain tensor set. In practice, the execution entity can obtain stress-strain data of key nodes of the component (here, key nodes can be the spatial locations in the structure with the highest stress / strain amplitudes and where fatigue cracks first initiate) through finite element simulation, and establish stress tensor and strain tensor representations in a local coordinate system (second reference coordinate system). The stress tensor corresponding to each candidate plane in the candidate plane set can be: , in, Indicates time, Represents the stress tensor. , , , , , Let x, y, and z represent the normal and tangential stress components in the x, y, and z coordinate directions, respectively. Here, x, y, and z in the stress tensor correspond to n, g, and h in the second reference coordinate system.

[0030] The strain tensor corresponding to each candidate plane in the above candidate plane set can be: , in, Represents the strain tensor. , , , , , These represent the normal and tangential strain components in the x, y, and z coordinate directions, respectively.

[0031] Optionally, the aforementioned implementing entity may also perform the following steps: The first step is to select an appropriate step size (e.g., 5° per step) within the chosen interval to make the two Euler angles equal. and By varying the angles by a certain step size, the coordinate transformation matrix for different Euler angle values ​​can be calculated. Based on the coordinate transformation relationship, the stress-strain history on any plane passing through the critical point (which can be the spatial location in the structure where the stress / strain amplitude is highest and fatigue cracks first initiate) can be obtained as follows: , in, This represents the stress in the second reference coordinate system. This represents the strain in the second reference coordinate system. This represents the stress in the first reference coordinate system. This represents the strain in the first reference coordinate system. This represents the coordinate transformation matrix (i.e., the rotation matrix that transforms the global coordinate system (first reference coordinate system) to the second reference coordinate system (n, g, h)). , , , , , , , , This represents the parameters in the coordinate transformation matrix, where... .

[0032] The second step, based on the above stress-strain history, is to determine the stress and strain components on any plane passing through a point in space. The stress components on this arbitrary plane can be: , in, , , , , , These represent the stresses along the x, y, and z principal axes and the shear stresses along the xy, xz, and yz axes on the rotated element, respectively. , , , , , Let x, y, z represent the stresses along the principal axes (x, y, z) and the shear stresses along the axes (xy, xz, yz) in the first reference coordinate system (before rotation), respectively. .

[0033] The strain components on any plane passing through a point in space can be: , in, , , , , , Let x, y, z represent the strain along the principal axes and xy, xz, yz of the element after rotation.

[0034] Therefore, by using the coordinate transformation method described above, after obtaining the stress and strain state at a point, we can determine the appropriate values ​​based on different Euler angles. and This allows us to obtain the stress and strain state of any plane at that point. Therefore, various damage parameters are set as the judgment criteria, making the Euler angles... and Within the specified range, the parameters are changed in steps of a certain angle, and the values ​​of the damage parameters on each plane are calculated. The plane with the maximum value is the most dangerous plane, which is the critical plane that needs to be found.

[0035] Step 104: Determine the critical plane based on the stress tensor set, strain tensor set, and candidate plane set.

[0036] In some embodiments, the executing entity may determine a critical plane based on the stress tensor set, the strain tensor set, and the candidate plane set. The critical plane may include: a shear strain range, a shear stress range, a normal strain range, and a normal stress range. The shear strain range may be: , in, Indicates the serial number. Indicates the serial number. Indicates the serial number, and , Indicates the range of shear strain. Indicates the first The analysis steps involve the shear strain components in the xy direction. Indicates the first The analysis steps involve the shear strain components in the xy direction. Indicates the first The analysis steps involve the shear strain components in the xz direction. Indicates the first The analysis step involves analyzing the shear strain components in the xz direction. Here, the analysis step can be the number of substeps in the loading cycle. For example, the analysis steps could be 1, 2, 3, ..., 10.

[0037] The range of shear stress can be: , in, This indicates the number of substeps in each loading loop. Indicates the range of shear stress. Indicates the first The shear stress components of the analysis steps Indicates the first The shear stress components of the analysis steps.

[0038] The normal strain range can be: , in, This represents the range of maximum normal strain on the critical plane. Indicates the first The normal strain components of the analysis steps Indicates the first The normal strain components of the analysis steps.

[0039] The range of normal stress can be: , in, Indicates the range of normal stress. Indicates the first The normal stress components of the analysis steps Indicates the first The normal stress components of the analysis steps.

[0040] Therefore, the critical plane method assumes that fatigue failure occurs on a specific plane, and fatigue life prediction and damage analysis are based on this specific plane. Based on the damage model used, all possible planes are traversed, and the plane with the extreme value of the damage parameters (selecting the plane with the largest shear strain value (shear strain range) as the critical plane) is selected to determine the critical plane.

[0041] Step 105: Determine the damage parameters based on the damage model and the critical plane.

[0042] In some embodiments, the execution entity can determine the damage parameters based on the damage model and the critical plane. The damage model can be: , in, Indicates the damage parameter, Represents material constants. This represents the maximum normal stress on the critical plane. Indicates the yield strength of the material. This represents the range of maximum shear strain on the critical plane. Here, It can be the above. .

[0043] Here, the material constants in the above damage model are determined by fitting uniaxial and torsional fatigue data, as shown in the following formula: , in, Indicates the elastic modulus of shear fatigue strength. Indicates the shear fatigue strength ductility coefficient. Indicates Young's modulus. Indicates fatigue life. Indicates the shear fatigue elasticity index. Indicates the shear fatigue ductility index. Indicates the elastic Poisson's ratio, Indicates the plastic Poisson's ratio. Indicates the tensile fatigue strength coefficient. This represents Young's modulus (elastic modulus). It represents the fatigue strength index (tensile fatigue strength index). It represents the fatigue ductility coefficient (tensile fatigue plasticity coefficient). It represents the fatigue ductility index (tensile fatigue plasticity index).

[0044] in, , in, Represents the actual fracture strain. Indicates the cross-sectional shrinkage rate. Represents the actual fracture stress. Indicates ultimate strength. Indicates the original cross-sectional area of ​​the specimen. This represents the cross-sectional area after fracture.

[0045] Therefore, the stress and strain fields, as well as experimental data, can be obtained using finite element simulation. Based on the damage model established above with three parameters—maximum normal stress, normal strain amplitude, and shear strain amplitude—the damage parameters of each candidate plane are calculated by iterating through each plane.

[0046] Step 106: Based on damage parameters and the Manson-Coffin equation, predict the fatigue life under multiaxial load.

[0047] In some embodiments, the aforementioned actuator can predict the fatigue life of multiaxial loads based on the damage parameters and the Manson-Coffin equation. In practice, the aforementioned actuator can predict the fatigue life of multiaxial loads based on the damage parameters and the Manson-Coffin equation using the following formula: , in, Indicates the elastic modulus of shear fatigue strength. Indicates the shear fatigue strength ductility coefficient. Indicates Young's modulus. Indicates fatigue life. Indicates the shear fatigue elasticity index. It represents the shear fatigue ductility index.

[0048] Therefore, the established damage parameters can be combined with the Manson-Coffin equation, and the fatigue life of the component under multiaxial load can be predicted through iterative solution or data fitting. In response to the additional hardening effect caused by non-proportional loading, the model improves the prediction accuracy by introducing a maximum normal stress correction term.

[0049] In practice, this damage model is applied to the aluminum alloy beam structure of the vulcanizing machine to predict its fatigue life under complex loading conditions, which can achieve high-precision life assessment.

[0050] In practice, the MTS 809 material testing system (MTS809 tensile-torsional composite material testing system, a high-temperature testing device for testing the tensile and torsional properties of composite materials) is used to perform MLCF testing (a core reliability testing technology used in advanced semiconductor processes to detect cross-layer faults in multilayer metal interconnect structures) under strain-controlled axial torsional deformation using a servo-controlled machine. The loading waveform is a sine wave, the loading frequency is 0.8 Hz, the standard gauge distance is 12.5 mm outer diameter, 10.5 mm inner diameter, and 25 mm gauge length. (e.g.) Figure 4 As shown, Figure 4 A schematic diagram of the geometry of a smooth, thin-walled circular ring specimen is shown. , , , , , , Indicates the dimensions of the sample, for example, It can be 180mm. It can be 25mm. It can be 12.5mm. It can be 35.5mm. It can be 42mm. It can be 10.5mm. It can be 25mm. The smooth, thin-walled circular ring specimen geometry is used for multiaxial fatigue testing. The gauge length is 12.5mm outer diameter and 10.5mm inner diameter. Furthermore, finite element software simulation analysis is performed. A component model is built using Abaqus (a finite element software for engineering simulation), boundary conditions are set to simulate actual working conditions and loads, and stress-strain field data is extracted for critical plane search and damage calculation. As an example, boundary conditions may include, but are not limited to, fixed constraints and loading methods for the component in the finite element simulation. As an example, this application uses three loading paths: proportional loading, 45° non-proportional loading, and 90° non-proportional loading. Figure 5 As shown, Figure 5 A schematic diagram of the strain path is shown. Figure 5 In this paper, (a) represents proportional loading, (b) represents 45° non-proportional loading, and (c) represents 90° non-proportional loading. γ represents the engineering shear strain amplitude (γ / √3 is obtained by using von Mises' (fourth strength theory) equivalent strain theory for strain space representation). The multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effect proposed in this application is applicable to aluminum beam components in vulcanizing machines. Water bag pressurization experiments were used to simulate load conditions of 1.1 MPa, 1.4 MPa, and 1.7 MPa. Strain gauges were used to monitor the strain distribution of the aluminum beam, verifying the accuracy of the finite element model, with the error controlled within 8.3%. As an example, the criteria used in this application for comparative evaluation with traditional models include: equivalent strain criterion, maximum shear strain criterion, FS (characteristic selection) criterion, SWT (stable wavelet transform) criterion, and MSWT (multi-scale wavelet transform) criterion.

[0051] Optionally, the aforementioned implementing entity may also perform the following steps: The first step is to conduct fatigue life tests on the aforementioned aluminum alloy under proportional and non-proportional multiaxial load conditions to generate experimental life. In practice, the aforementioned entity can conduct fatigue life tests on the aforementioned aluminum alloy under proportional and non-proportional multiaxial load conditions to generate experimental life through the following steps: First, debug the electro-hydraulic servo tension-torsion composite multiaxial fatigue testing machine and customize anti-instability, high coaxiality clamping fixtures. Clamp the specimen to the testing machine and calibrate the axial and torsional coaxiality. Apply preload to release residual stress, calibrate various sensors and monitoring systems, and import the preset load program (here, the preset load program can be a pre-set program that can select different loading conditions). Perform low-amplitude pre-run to verify the linkage between load parameters and the system. Subsequently, proportional and non-proportional multiaxial fatigue tests were conducted. The proportional test was loaded according to preset parameters such as load amplitude, stress ratio, and frequency, and load, strain, and other data were collected in real time and cracks were monitored periodically. The non-proportional test further enhanced the precise control of the load path and the monitoring of the non-proportional additional hardening effect of the material, with a higher monitoring frequency. Both types of tests were terminated when the specimen underwent macroscopic fracture. Parallel tests were also completed under various working conditions (here, each working condition can be: proportional loading, 45° non-proportional loading, and 90° non-proportional loading path). Finally, the experimental life under each working condition was recorded.

[0052] The second step, based on the experimental life and fatigue life mentioned above, is to determine the prediction error using the following formula: , in, Indicates the prediction error. Indicates the experimental lifespan.

[0053] The third step is to determine the normal distribution error corresponding to fatigue life using the following formula: , in, This represents the error of the normal distribution. The standard deviation of the error is represented by the standard deviation of the error. Indicates the absolute error of the mean. , Indicates the number of samples. Indicates the first The prediction error for each sample.

[0054] Therefore, the predicted fatigue life can be evaluated using a probability distribution function.

[0055] Therefore, this application considers the problem that under multiaxial nonproportional loading conditions, the additional hardening caused by the relative changes in principal stress and principal strain axes reduces the fatigue life of engineering materials, leading to deviations from actual results in the predicted values. A PN (Proportional-Nonproportional) damage model based on the critical plane method is proposed. Its core lies in introducing the maximum shear strain range, maximum normal strain range, and maximum normal stress member damage parameters on the critical plane to address the additional hardening effect caused by multiaxial nonproportional loading. Life prediction is achieved through coupling multiaxial fatigue experiments with finite element simulation.

[0056] The above embodiments of this application have the following beneficial effects: Firstly, the multiaxial fatigue life prediction method for aluminum alloys based on non-proportional loading effects, as described in some embodiments of this application, offers high prediction accuracy: In experimental verification of 7050 aluminum alloy, all data points of the new model fall within the 1.5x error band, outperforming traditional models. Secondly, it has strong path applicability: Non-proportional additional hardening is directly quantified through the normal stress correction term, making it suitable for proportional, 45°, and 90° non-proportional loading paths. Thirdly, it is engineering-friendly: Only conventional material parameters are required, no complex calibration is needed, and it can be integrated into finite element software such as Abaqus (a finite element software for engineering simulation). Fourthly, it closely matches the microscopic mechanism: The model is based on the critical plane method, consistent with the physical mechanism of fatigue crack initiation at the maximum shear strain surface, improving theoretical reliability. Finally, it has wide applicability: Verified in a vulcanizing machine aluminum beam case study, the predicted life error compared to the measured value is approximately 20%, making it suitable for the durability design of aluminum alloy structures in aerospace, rail transportation, and other fields.

[0057] Further reference Figure 6 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an aluminum alloy multiaxial fatigue life prediction device based on non-proportional loading effect. These embodiments of the aluminum alloy multiaxial fatigue life prediction device based on non-proportional loading effect are similar to... Figure 1 Corresponding to the method embodiments shown, this aluminum alloy multiaxial fatigue life prediction device based on non-proportional loading effect can be specifically applied to various electronic devices.

[0058] like Figure 6As shown, an aluminum alloy multiaxial fatigue life prediction device 600 based on non-proportional loading effect in some embodiments includes: a test unit 601, a first determination unit 602, a second determination unit 603, a third determination unit 604, a fourth determination unit 605, and a prediction unit 606. The test unit 601 is configured to perform uniaxial tensile mechanical testing on the aluminum alloy to generate stress-strain data; the first determination unit 602 is configured to determine a set of candidate planes based on the stress-strain data; the second determination unit 603 is configured to determine the stress tensor and strain tensor corresponding to each candidate plane in the candidate plane set based on the stress-strain data, obtaining a stress tensor set and a strain tensor set; the third determination unit 604 is configured to determine a critical plane based on the stress tensor set, the strain tensor set, and the candidate plane set; the fourth determination unit 605 is configured to determine damage parameters based on a damage model and the critical plane; and the prediction unit 606 is configured to predict the fatigue life under multiaxial load based on the damage parameters and the Manson-Coffin equation.

[0059] It is understandable that the elements described in the aluminum alloy multiaxial fatigue life prediction device 600 based on non-proportional loading effect are similar to the reference elements. Figure 1 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the aluminum alloy multiaxial fatigue life prediction device 600 based on non-proportional loading effects and the units contained therein, and will not be repeated here.

[0060] This application also provides a computer device 700. For example... Figure 7 As shown, the computer device 700 includes a bus 701, a processor 702, a memory 703, and a communication interface 704. The processor 702, memory 703, and communication interface 704 communicate with each other via the bus 701. The computer device 700 can be a server or a terminal device. It should be understood that this application does not limit the number of processors and memories in the computer device 700.

[0061] The 701 bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus 701 may be represented by a single line, but this does not mean that there is only one bus or one type of bus. The bus 701 may include a path for transmitting information between various components of the computer device 700 (e.g., memory 703, processor 702, communication interface 704).

[0062] Processor 702 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0063] Memory 703 may include volatile memory, such as random access memory (RAM). Memory 703 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0064] The memory 703 stores executable program code, and the processor 702 executes this executable program code to implement the functions of the aforementioned test unit, first determination unit, second determination unit, third determination unit, fourth determination unit, and prediction unit, thereby realizing the above-mentioned aluminum alloy multiaxial fatigue life prediction method based on non-proportional loading effect. That is, the memory 703 stores instructions for executing the above-mentioned aluminum alloy multiaxial fatigue life prediction method based on non-proportional loading effect.

[0065] The communication interface 704 uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between the computer device 700 and other devices or communication networks.

[0066] This application also provides a chip, which includes a processor and a data interface. The processor reads instructions stored in the memory through the data interface to execute the above-described method for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects.

[0067] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct a computing device to execute the above-described method for predicting the multi-axis fatigue life of aluminum alloys based on non-proportional loading effects.

[0068] Further reference Figures 8-13 , Figure 8 A comparison graph showing the relationship between the PN model predictions and experimental values ​​is presented, with all points located within the 1.5-fold scattering band; Figure 9 Box plots of error for each model are shown, and the advantages of the PN model are quantitatively compared. Figure 10 The experimental setup of the vulcanizing machine and the strain test layout are shown, along with the locations of the aluminum beams and bolt measuring points. Figure 11 A schematic diagram showing the strain test data of the inner and outer sides of the aluminum beam and bolts is presented; Figure 12 A comparison chart of simulation and experimental data is shown to verify the accuracy of the finite element model; Figure 13 The figure shows a comparison between the predicted life of the PN model and the experimental value in the aluminum beam of the vulcanizing machine. Figure 8 In the figure, (a) represents the effective amplitude and N. f (a) is a correlation diagram, and (b) is a comparison diagram of the predicted fatigue life and the experimental life. Figure 9 In this context, MSSM, FS, MSWT, ESM, and SWT all represent existing lifetime calculation methods. MSSM stands for Minimal Supersymmetric Standard Model, FS for Feature Selection, MSWT for Multiscale Wavelet Transform, ESM for Lifetime Calculation Method, SWT for Stable Wavelet Transform, and NEW for this application. Figure 10 In the diagram, (a) represents the overall experimental layout, (b) represents the experimental data acquisition diagram, (c) represents the strain gauge arrangement diagram of the aluminum alloy beam specimen, and (d) represents the installation diagram of the bolt measuring point strain gauge. Figure 12 MPa in this context represents megapascals. Figure 13 In this context, Predicted Fatigue Life (eyeles) represents predicted fatigue life (number of cycles), Experimental Fatigue Life (cycles) represents experimental fatigue life (number of cycles), and Predieted life N... f N represents the predicted fatigue life. f ±1.5 facter represents 1.5 times the scattering band, ±2 facter represents 2 times the scattering band, and ±3 facter represents 3 times the scattering band.

[0069] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0070] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of this application.

Claims

1. A method for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects, characterized in that, include: Aluminum alloys were subjected to uniaxial tensile mechanical tests to generate stress-strain data. Based on the stress-strain data, a set of candidate planes is determined; Based on the stress and strain data, the stress tensor and strain tensor corresponding to each candidate plane in the candidate plane set are determined, and the stress tensor set and strain tensor set are obtained. Based on the stress tensor set, the strain tensor set, and the candidate plane set, the critical plane is determined; Based on the damage model and the critical plane, the damage parameters are determined; Based on the damage parameters and the Manson-Coffin equation, the fatigue life under multiaxial loads is predicted.

2. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 1, characterized in that, The stress tensor corresponding to each candidate plane in the candidate plane set is: ， in, Indicates time, Represents the stress tensor. , , , , , These represent the normal and tangential stress components in the x, y, and z coordinate directions, respectively. The strain tensor corresponding to each candidate plane in the candidate plane set is: ， in, Represents the strain tensor. , , , , , These represent the normal and tangential strain components in the x, y, and z coordinate directions, respectively.

3. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 1, characterized in that, The critical plane includes: the shear strain range, the shear stress range, the normal strain range, and the normal stress range, wherein, The shear strain range is: ， in, Indicates the serial number. Indicates the serial number. Indicates the serial number, and , Indicates the range of shear strain. Indicates the first The analysis steps involve the shear strain components in the xy direction. Indicates the first The analysis steps involve the shear strain components in the xy direction. Indicates the first The analysis steps involve the shear strain components in the xz direction. Indicates the first The analysis steps involve the shear strain components in the xz direction. The range of shear stress is: ， in, This indicates the number of substeps in each loading loop. Indicates the range of shear stress. Indicates the first The shear stress components of the analysis steps Indicates the first The shear stress components of the analysis steps The normal strain range is: ， in, This represents the range of maximum normal strain on the critical plane. Indicates the first The normal strain components of the analysis steps Indicates the first The normal strain components of the analysis steps The range of the normal stress is: ， in, Indicates the range of normal stress. Indicates the first The normal stress components of the analysis steps Indicates the first The normal stress components of the analysis steps.

4. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 1, characterized in that, The damage model is: ， in, Indicates the damage parameter, Represents material constants. This represents the maximum normal stress on the critical plane. Indicates the yield strength of the material. This indicates the range of maximum shear strain on the critical plane.

5. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 4, characterized in that, The material constants in the damage model were determined by fitting uniaxial and torsional fatigue data, as shown in the following formula: ， in, Indicates the elastic modulus of shear fatigue strength. Indicates the shear fatigue strength ductility coefficient. Indicates Young's modulus. Indicates fatigue life. Indicates the shear fatigue elasticity index. Indicates the shear fatigue ductility index. Indicates the elastic Poisson's ratio, Indicates the plastic Poisson's ratio. Indicates the tensile fatigue strength coefficient. Indicates Young's modulus. Indicates fatigue strength index, Indicates the fatigue ductility coefficient. It represents the fatigue ductility index.

6. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 1, characterized in that, The method for predicting fatigue life under multiaxial loads based on the damage parameters and the Manson-Coffin equation includes: Based on the aforementioned damage parameters and the Manson-Coffin equation, the fatigue life under multiaxial loads is predicted using the following formula: ， in, Indicates the elastic modulus of shear fatigue strength. Indicates the shear fatigue strength ductility coefficient. Indicates Young's modulus. Indicates fatigue life. Indicates the shear fatigue elasticity index. It represents the shear fatigue ductility index.

7. The method for predicting multiaxial fatigue life of aluminum alloys based on non-proportional loading effect according to claim 1, characterized in that, The method further includes: The aluminum alloy was subjected to fatigue life tests under proportional and non-proportional multiaxial load conditions to generate experimental life. Based on the experimental life and the fatigue life, the prediction error is determined using the following formula: ， in, Indicates the prediction error. Indicates experimental lifespan; The normal distribution error corresponding to fatigue life can be determined using the following formula: ， in, This represents the error of the normal distribution. The standard deviation of the error is represented by the standard deviation of the error. Indicates the absolute error of the mean. , Indicates the number of samples. Indicates the first The prediction error for each sample.

8. A device for predicting the multiaxial fatigue life of aluminum alloys based on non-proportional loading effects, characterized in that, include: The test unit is configured to perform uniaxial tensile mechanical tests on aluminum alloys to generate stress-strain data. The first determining unit is configured to determine a set of candidate planes based on the stress-strain data; The second determining unit is configured to determine the stress tensor and strain tensor corresponding to each candidate plane in the candidate plane set based on the stress and strain data, thereby obtaining a stress tensor set and a strain tensor set. The third determining unit is configured to determine the critical plane based on the stress tensor set, the strain tensor set, and the candidate plane set; The fourth determining unit is configured to determine damage parameters based on the damage model and the critical plane; The prediction unit is configured to predict the fatigue life of multiaxial loads based on the damage parameters and the Manson-Coffin equation.

9. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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