Material plastic deformation testing methods, devices, equipment and media

Abstract

The present invention provides a material plastic deformation testing method, apparatus, equipment, and medium, relating to the field of computer-aided design technology. The method comprises: obtaining the optimal crystal plasticity parameters of a sample material; constructing a small punch test model and a crystal specimen model for finite element simulation; performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data for the small punch test; and determining the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data from the small punch test. The present invention can more accurately simulate and analyze the plastic deformation behavior of materials in small punch tests, thereby providing support for equipment reliability assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and in particular to a material plastic deformation testing method, device, equipment and medium. Background Art

[0002] Large-scale equipment such as nuclear reactor vessels, oil pipelines, and chemical production equipment that serve in extreme environments such as high temperature, high pressure, nuclear radiation, and corrosive media are prone to creep, embrittlement, and even fracture risks during long-term operation. Therefore, regular safety and remaining life assessments are crucial to ensuring the safe operation of the equipment. Although traditional standard test specimens can accurately obtain the mechanical properties of materials, they have defects such as large specimen size, difficulty in sampling (smaller structures such as thin walls), and large wear and tear on in-service parts. In comparison, the small punch test sampling has almost no impact on the structural integrity and working reliability of the in-service equipment. The experimental conditions are low and the specimen preparation is simple, providing an efficient and feasible technical path for in-situ performance evaluation of in-service equipment in extreme environments.

[0003] The load-displacement curves of small-punch experiments provide macroscopic results of the material's mechanical response during the elastic-plastic deformation phase. Finite element analysis, on the other hand, can analyze the stress distribution and failure modes during microscopic deformation. By quantifying the influence of experimental results, specimen size, friction, and other factors, it can guide experiments and inversely analyze the material's constitutive relations and mechanical properties. However, in finite element analysis of small-punch experiments, traditional finite element models are limited by homogenization assumptions and empirical parameter dependence, making it difficult to accurately capture the deformation behavior of materials at the microscale, which is dominated by slip systems and grain boundary effects. Furthermore, their phenomenological constitutive models are unable to characterize the anisotropic response that is sensitive to crystal orientation. Summary of the Invention

[0004] Embodiments of the present invention provide a material plastic deformation testing method, apparatus, device, and storage medium to more accurately simulate and analyze the plastic deformation behavior of materials in small punch experiments, thereby providing support for equipment reliability evaluation.

[0005] In a first aspect, an embodiment of the present invention provides a material plastic deformation testing method, comprising:

[0006] Obtain the optimal crystal plasticity parameters of the sample material;

[0007] Construct a small punch experimental model and crystal specimen model for finite element simulation;

[0008] Performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test;

[0009] Based on the simulation data of the small punch experiment, the strain gradient distribution characteristics of the sample material at different plastic deformation stages are determined.

[0010] As a possible implementation manner, obtaining the optimal crystal plasticity parameters of the sample material includes:

[0011] Acquiring actual data from a uniaxial tensile test of the sample material;

[0012] The crystal plastic strain gradient analysis function of finite element simulation is used to simulate and analyze the uniaxial tensile test and obtain the simulation data of the uniaxial tensile test;

[0013] By comparing the difference between the actual data and the simulated data of the uniaxial tensile test, the crystal plasticity parameters of the crystal plasticity strain gradient analysis function are adjusted, and the crystal plasticity parameters that make the difference less than a preset threshold are determined as the optimal crystal plasticity parameters.

[0014] As a possible implementation, performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test includes:

[0015] Importing the optimal crystal plasticity parameters into the crystal plasticity strain gradient analysis function of the finite element simulation to determine the constitutive relationship of the sample material;

[0016] By using the crystal plastic strain gradient analysis function, a small punch experiment simulation calculation is performed on the small punch experiment model and the crystal sample model to obtain simulation data of the small punch experiment.

[0017] As a possible implementation, determining the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment includes:

[0018] Acquire actual data of a small punch experiment on the sample material;

[0019] The geometrically required dislocation distribution of the sample material at different plastic deformation stages is determined based on the actual data and simulation data of the small punch experiment.

[0020] As a possible implementation method, constructing the crystal sample model includes:

[0021] The crystal sample model is constructed by using a Thiessen polygon algorithm, and each grain in the crystal sample model is given material crystal mechanical properties and grain orientation parameters.

[0022] As a possible implementation, the crystal plastic strain gradient analysis function is constructed based on an explicit dynamics analysis stress integration algorithm.

[0023] As a possible implementation method, the actual data and simulation data of the uniaxial tensile test are both load-displacement curves;

[0024] The crystal plasticity parameters include: elastic constant, reference shear strain rate, rate sensitivity index, slip system initial yield stress, slip system saturation stress, slip system initial yield hardening modulus.

[0025] In a second aspect, an embodiment of the present invention provides a material plastic deformation testing device, comprising:

[0026] An acquisition module, used to obtain the optimal crystal plasticity parameters of the sample material;

[0027] Construction module, used to construct small punch experimental model and crystal specimen model for finite element simulation;

[0028] A simulation module, configured to perform finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test;

[0029] The determination module is used to determine the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment.

[0030] In a third aspect, an embodiment of the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method in the first aspect or any possible implementation of the first aspect is implemented.

[0031] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method in the first aspect or any possible implementation of the first aspect.

[0032] In an embodiment of the present invention, by obtaining the optimal crystal plasticity parameters of the sample material and combining the crystal plasticity constitutive relation with the finite element method, the local stress concentration and uneven plastic deformation behavior caused by the difference in grain orientation can be captured; a crystal specimen model is constructed based on the pseudo-random grain modeling technology, and the contribution of microscopic mechanisms such as grain boundary effects to the macroscopic mechanical response can be quantified; finite element simulation is performed according to the optimal crystal plasticity parameters, the small punch test model and the crystal specimen model, and based on the simulation data of the small punch test, the strain gradient distribution characteristics of the sample material in different plastic deformation stages are calculated, so as to accurately simulate and analyze the plastic deformation behavior of the material in the small punch test, and provide support for the reliability evaluation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic diagram of a load-displacement curve provided by an embodiment of the present invention;

[0034] Figure 2 Schematic diagram of geometrically required dislocation distribution of a small punch experiment provided by an embodiment of the present invention;

[0035] Figure 3 1 is a schematic diagram of a finite element simulation of a small punch experiment provided by an embodiment of the present invention;

[0036] Figure 4 1 is a flow chart of a material plastic deformation testing method provided by one embodiment of the present invention;

[0037] Figure 5 is a schematic diagram of curve comparison provided by an embodiment of the present invention;

[0038] Figure 6 Schematic diagram of a small punch experimental model provided by an embodiment of the present invention;

[0039] Figure 7 is a schematic diagram of a crystal sample model provided by an embodiment of the present invention;

[0040] Figure 8 1 is a flow chart of a material plastic deformation testing method provided by another embodiment of the present invention;

[0041] Figure 9 Schematic diagram of the structure of a material plastic deformation testing device provided by an embodiment of the present invention;

[0042] Figure 10 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0044] First, a brief introduction to the small punch experiment is given.

[0045] The small punch test is a miniaturized testing technique used to evaluate the mechanical properties of materials, such as strength, plasticity, and toughness. Compared to traditional tensile and impact tests, its most significant advantage is that it requires only tiny circular, thin specimens (typically 2-10 mm in diameter and 0.1-2 mm thick). This makes it particularly suitable for applications where material sampling is difficult (such as nondestructive testing of in-service components and small-scale material research) or where rapid evaluation is required. The basic principle is to place a circular, thin specimen on a base with a circular hole. A punch (typically a hemispherical or cylindrical indenter) at the top applies a vertical load at a constant rate, causing the specimen to bend and deform until it fractures. A load-displacement curve is recorded, and material properties are evaluated based on its characteristics, such as peak load, fracture displacement, and energy absorption.

[0046] For example, the load-displacement curve of the small punch test can be found in Figure 1 As shown, the deformation process can be divided into six stages: elastic deformation stage I, plastic bending stage II, uniform plastic deformation stage III, plastic deformation instability stage IV, local necking instability stage V, and fracture failure stage VI. Analyzing the mechanical behavior of these six stages can replace traditional uniaxial tensile testing to evaluate mechanical properties such as elastic-plastic behavior, greatly improving the inspection efficiency of in-service special equipment.

[0047] The embodiment of the present invention uses a small punch specimen that is circular, 8mm in diameter, and 0.5mm thick. Since the small punch with a thickness of 0.5mm has deformation non-uniformity in both the thickness and radius directions, it is of great significance to analyze the influence of strain gradient. The load-displacement curve of the small punch experiment can only obtain the macroscopic results of the mechanical response of the material in the elastic-plastic deformation stage, while the finite element analysis based on crystal plasticity theory can realize the analysis of the stress distribution and failure mode of the microscopic deformation process, quantify the influence of experimental results, sample size, friction, etc. to standardize and guide the experiment, and inverse the constitutive relationship and mechanical properties of the material.

[0048] Figure 2 Schematic diagram of the geometrically required dislocation distribution during the small punch experiment. Figure 3 This is the finite element simulation model of the small punch experimental process. Figure 3 The load concentration area Z can be used to illustrate the load condition of the small punch specimen. That is, during the deformation process of the small punch specimen, the upper surface is subjected to the load from the punch. That is, the upper surface is initially compressed, and the lower surface is tensile deformed. That is, the specimen has contraction strain along the upper surface of the cross section, and extension strain on the lower surface. That is, there is a strain difference between the upper and lower surfaces. The strain difference divided by the distance between the upper and lower surfaces is defined as the strain gradient. The strain gradient can be used to describe the degree of strain change in the thickness direction of the sheet. At the microscopic scale, the plastic deformation mechanism of metals is mainly the slip of dislocations along different slip systems. Assuming that the thickness direction of the specimen is as follows Figure 2 The three-layer grain shown in βGeometrically required dislocations, generated to maintain the bending deformation state, are the primary cause of strain gradients. These dislocations, generated to maintain shape, also increase the specimen's dislocation density, leading to lattice distortion and strengthening the material. The influence of strain gradients increases with thickness, particularly during uneven plastic deformation processes such as microbending, microtorsion, and microindentation. At these microscales, ranging from a few microns to several hundred microns, the influence of geometrically required dislocation density on plastic deformation is non-negligible. Therefore, finite element analysis based on crystal plasticity theory can be used to evaluate the strain gradient distribution associated with geometrically required dislocation density during uneven plastic deformation.

[0049] See also Figure 4 , which shows a flow chart for implementing the material plastic deformation testing method provided by an embodiment of the present invention, and is described in detail as follows:

[0050] Step S401: Obtaining the optimal crystal plasticity parameters of the sample material.

[0051] In the finite element analysis of small punch experiments, traditional finite element models, due to their homogenization assumptions and dependence on empirical parameters, struggle to accurately capture deformation behavior dominated by microscopic slip systems and grain boundary effects. Furthermore, their phenomenological constitutive models are unable to characterize the anisotropic response that is sensitive to crystal orientation. Therefore, it is necessary to develop reasonable constitutive relations that account for microscopic grain characteristics and apply them to the finite element analysis of small punch experiments, promoting integrated macro-micro model analysis.

[0052] This embodiment is based on the crystal plasticity theory of strain gradient strengthening and combines the simulated crystal plasticity strain gradient analysis function (i.e., the VUMAT subroutine) to perform multi-scale simulations of small punch experiments to obtain the optimal crystal plasticity parameters of the sample material, thereby establishing a constitutive relationship that takes into account the dynamic evolution of geometrically required dislocations. By developing a VUMAT subroutine based on an explicit dynamic analysis stress integration algorithm, cross-scale correlation analysis of the material's microscopic plastic deformation and macroscopic mechanical response is achieved.

[0053] For example, in one possible implementation, the process of obtaining the optimal crystal plasticity parameters of the sample material is as follows:

[0054] Obtain actual data from uniaxial tensile tests of sample materials;

[0055] The crystal plastic strain gradient analysis function of finite element simulation is used to simulate and analyze the uniaxial tensile test and obtain the simulation data of the uniaxial tensile test;

[0056] By comparing the differences between the actual data and simulated data of the uniaxial tensile test, the crystal plasticity parameters of the crystal plasticity strain gradient analysis function are adjusted, and the crystal plasticity parameters that make the difference less than the preset threshold are determined as the optimal crystal plasticity parameters.

[0057] The embodiment of the present invention first obtains the macroscopic constitutive properties of the material through a uniaxial tensile test. This process obtains the load-displacement curve of the material, which can lay the foundation for the subsequent numerical simulation. Furthermore, the uniaxial tensile test is simulated by finite element simulation using the VUMAT subroutine. In this process, by continuously fitting the crystal plasticity parameters to ensure that a set of optimal parameters that are highly consistent with the simulation data and the actual data are obtained, the constitutive relationship obtained by simulation has the highest similarity with the actual experimental results, such as Figure 5 As shown in Figure 2, the accuracy and reliability of the parameters are ensured through repeated iterations. Once the optimal crystal plasticity parameters are obtained, they can be applied to more complex deformation problems—simulating small punch experiments.

[0058] Step S402 , constructing a small punch experimental model and a crystal sample model for finite element simulation.

[0059] The small punch experiment is a typical complex plastic deformation process. Finite element simulation can be used to deeply explore the internal strain gradient distribution characteristics. This step can not only verify the effectiveness of the optimal crystal plasticity parameters, but also expand the research scope from simple uniaxial tension to more complex three-dimensional deformation. Figure 6 , crystal specimen model see Figure 7 (Through numerical simulation, it was found that the plastic deformation process of the square specimen can be used to equivalently represent the different stages that the circular specimen goes through during the plastic deformation process).

[0060] The crystal specimen model here can be a single crystal specimen model or a polycrystalline specimen model. For example, in one possible implementation, a polycrystalline specimen model can be constructed using a Thiessen polygon algorithm (i.e., a Voronoi diagram). Each grain in the crystal specimen model is then assigned the material's crystal mechanical properties and grain orientation parameters. Finite element analysis software can then be used to numerically simulate the different plastic deformation stages during the experiment to obtain the plastic deformation characteristics of each stage. Furthermore, by combining strain gradient analysis and verifying the model's accuracy through experimental comparison, it is possible to promote the integration of research on the mechanism of plastic inhomogeneous deformation of thin plates at the microscale and numerical simulation studies.

[0061] Step S403 , performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test.

[0062] In this embodiment, the optimal crystal plasticity parameters are imported into the VUMAT subroutine of the finite element simulation to determine the constitutive relationship of the sample material. The VUMAT subroutine simulates the small punch test to obtain simulation data of the small punch test.

[0063] Step S404 : determining the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment.

[0064] For example, actual data from small-punch experiments can be compared and analyzed with data from finite element simulations. By carefully studying the strain gradient distribution characteristics at different stages of plastic deformation, the microscopic deformation mechanism of the material under complex loading conditions can be revealed. For example, the distribution of geometrically required dislocations associated with the strain gradient can be obtained, where the actual failure zone (i.e., the fracture zone) of the sample material has the highest density of geometrically required dislocations and is the most densely distributed.

[0065] In an embodiment of the present invention, by obtaining the optimal crystal plasticity parameters of the sample material and combining the crystal plasticity constitutive relation with the finite element method, the local stress concentration and uneven plastic deformation behavior caused by the difference in grain orientation can be captured; a crystal specimen model is constructed based on the pseudo-random grain modeling technology, and the contribution of microscopic mechanisms such as grain boundary effects to the macroscopic mechanical response can be quantified; finite element simulation is performed according to the optimal crystal plasticity parameters, the small punch test model and the crystal specimen model, and based on the simulation data of the small punch test, the strain gradient distribution characteristics of the sample material in different plastic deformation stages are calculated, so as to accurately simulate and analyze the plastic deformation behavior of the material in the small punch test, and provide support for the reliability evaluation of the equipment.

[0066] The following uses a specific example to explain the implementation process of the material plastic deformation testing method proposed in the embodiment of the present invention.

[0067] See also Figure 8 As shown, the material plastic deformation test methods include:

[0068] (1) Use programming language to write code and establish the VUMAT subroutine based on the explicit dynamic analysis stress integration algorithm, so that the VUMAT subroutine can be called to perform calculations in the finite element software during operation to obtain the shear strain gradient of the inhomogeneous deformation of the grains and the geometrically required dislocation density and sequence related to it, thereby realizing cross-scale correlation analysis of the micro-plastic deformation and macro-mechanical response of the material.

[0069] (2) A uniaxial tensile test is performed on the sample material to obtain the load-displacement curve of the sample material.

[0070] (3) In the finite element software, the uniaxial tensile test process was simulated. During the simulation, the VUMAT subroutine was called to obtain the crystal plasticity parameters for the simulation of the small punch test. The set of parameters with high coincidence between the experimental simulation and the load-displacement curve was taken as the optimal parameters. The parameters included: elastic constant, reference shear strain rate, rate sensitivity index, initial yield stress of the slip system, saturation stress of the slip system, and initial yield hardening modulus of the slip system.

[0071] (4) Construct a small punch experimental model and a crystal specimen model for finite element simulation, and assign material crystal mechanical properties and grain orientation parameters to each grain in the crystal specimen model so that the effects of the two can be considered during the plastic deformation process.

[0072] (5) The optimal crystal plasticity parameters obtained in step 3 are imported into the finite element software, and the numerical analysis results of the small punch experiment are obtained through simulation analysis, including the plastic deformation characteristics of the small punch specimen at different deformation stages, such as the distribution of geometrically required dislocations related to the strain gradient.

[0073] The embodiments of the present invention have the following advantages:

[0074] By combining crystal plasticity finite element analysis with small punch experiments, and comparing numerical simulations of crystal plasticity strain gradient finite element analysis with experimental results, the authors optimized material constitutive parameters and revealed microscopic deformation mechanisms, significantly improving the accuracy of complex deformation predictions. During the finite element analysis, dynamic explicit algorithms were employed to avoid convergence difficulties caused by nonlinearities in implicit analysis. Furthermore, the nonlinear crystal specimen model was combined to characterize the evolution of microscopic properties during complex plastic deformation. By introducing a dislocation density evolution model, the strain gradient crystal plasticity numerical simulation method was extended to study the plastic deformation of micro- and nanoscale materials. Furthermore, thermal and mechanical fields can be added to the finite element simulations to simulate material degradation under extreme environments, providing research insights for efficient equipment design and lifespan assessment.

[0075] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0076] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0077] Figure 9 The following is a schematic diagram of the structure of a material plastic deformation testing device provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are detailed as follows:

[0078] like Figure 9 As shown, the material plastic deformation testing device 9 includes:

[0079] An acquisition module 91 is used to obtain the optimal crystal plasticity parameters of the sample material;

[0080] A construction module 92 is used to construct a small punch experimental model and a crystal sample model for finite element simulation;

[0081] A simulation module 93 is used to perform finite element simulation based on the optimal crystal plasticity parameters, the small punch test model and the crystal specimen model to obtain simulation data of the small punch test;

[0082] The determination module 94 is used to determine the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment.

[0083] As a possible implementation, the acquisition module 91 is configured to:

[0084] Obtain actual data from uniaxial tensile tests of sample materials;

[0085] The crystal plastic strain gradient analysis function of finite element simulation is used to simulate and analyze the uniaxial tensile test and obtain the simulation data of the uniaxial tensile test;

[0086] By comparing the differences between the actual data and simulated data of the uniaxial tensile test, the crystal plasticity parameters of the crystal plasticity strain gradient analysis function are adjusted, and the crystal plasticity parameters that make the difference less than the preset threshold are determined as the optimal crystal plasticity parameters.

[0087] As a possible implementation, the simulation module 93 is used to:

[0088] Import the optimal crystal plasticity parameters into the crystal plasticity strain gradient analysis function of the finite element simulation to determine the constitutive relationship of the sample material;

[0089] Through the crystal plastic strain gradient analysis function, the small punch experiment simulation calculation is performed on the small punch experiment model and the crystal specimen model to obtain the simulation data of the small punch experiment.

[0090] As a possible implementation manner, the determination module 94 is configured to:

[0091] Obtain actual data from small punch experiments on sample materials;

[0092] Based on the actual data and simulation data of the small punch experiment, the geometric required dislocation distribution of the sample material at different plastic deformation stages is determined.

[0093] As a possible implementation, the building block 92 is used to:

[0094] A crystal specimen model is constructed using the Thiessen polygon algorithm, and each grain in the crystal specimen model is assigned material crystal mechanical properties and grain orientation parameters.

[0095] As a possible implementation method, the crystal plasticity strain gradient analysis function is built based on the stress integration algorithm of explicit dynamics analysis.

[0096] As a possible implementation method, the actual data and simulation data of the uniaxial tensile test are both load-displacement curves;

[0097] Crystal plasticity parameters include: elastic constant, reference shear strain rate, rate sensitivity index, initial yield stress of slip system, saturation stress of slip system, and initial yield hardening modulus of slip system.

[0098] In an embodiment of the present invention, by obtaining the optimal crystal plasticity parameters of the sample material and combining the crystal plasticity constitutive relation with the finite element method, the local stress concentration and uneven plastic deformation behavior caused by the difference in grain orientation can be captured; a crystal specimen model is constructed based on the pseudo-random grain modeling technology, and the contribution of microscopic mechanisms such as grain boundary effects to the macroscopic mechanical response can be quantified; finite element simulation is performed according to the optimal crystal plasticity parameters, the small punch test model and the crystal specimen model, and based on the simulation data of the small punch test, the strain gradient distribution characteristics of the sample material in different plastic deformation stages are calculated, so as to accurately simulate and analyze the plastic deformation behavior of the material in the small punch test, and provide support for the reliability evaluation of the equipment.

[0099] Figure 10 FIG is a schematic diagram of an electronic device 10 provided by an embodiment of the present invention. Figure 10 As shown, the electronic device 10 of this embodiment includes: a processor 100 and a memory 101. The memory 101 stores a computer program 102. When the processor 100 executes the computer program 102, the steps of the above-mentioned method embodiments are implemented. Alternatively, when the processor 100 executes the computer program 102, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0100] For example, the computer program 102 may be divided into one or more modules / units, which are stored in the memory 101 and executed by the processor 100 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 102 in the electronic device 10.

[0101] The electronic device 10 may include, but is not limited to, a processor 100 and a memory 101. Those skilled in the art will appreciate that Figure 10This is merely an example of the electronic device 10 and does not constitute a limitation of the electronic device 10. The electronic device 10 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 10 may also include input and output devices, network access devices, buses, etc.

[0102] The processor 100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0103] The memory 101 may be an internal storage unit of the electronic device 10, such as the hard disk or memory of the electronic device 10. The memory 101 may also be an external storage device of the electronic device 10, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 10. Furthermore, the memory 101 may include both an internal storage unit of the electronic device 10 and an external storage device. The memory 101 is used to store the computer program 102 and other programs and data required by the electronic device 10. The memory 101 may also be used to temporarily store data that has been output or is about to be output.

[0104] For the sake of convenience and brevity, the division of the above functional modules / units is only used as an example. In actual applications, the above functions can be assigned to different functional modules / units as needed. The above modules / units can be implemented in the form of hardware, software, or a combination of hardware and software.

[0105] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in the above-mentioned method embodiments.

[0106] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the methods in the above-mentioned method embodiments.

[0107] The term "computer program" includes computer program code, which may be in source code form, object code form, executable file, or some intermediate form. Computer-readable media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunications signals, and software distribution media.

[0108] In the above embodiments, the descriptions of each embodiment have their own focus. For parts not described or recorded in detail in one embodiment, please refer to the relevant descriptions of other embodiments. Unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other. The technical features of different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0109] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A material plastic deformation testing method, characterized in that: include: Obtain the optimal crystal plasticity parameters of the sample material; Construct a small punch experimental model and crystal specimen model for finite element simulation; Performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test; Determining the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment; The obtaining of the optimal crystal plasticity parameters of the sample material comprises: Acquiring actual data from a uniaxial tensile test of the sample material; The crystal plastic strain gradient analysis function of finite element simulation is used to simulate and analyze the uniaxial tensile test and obtain the simulation data of the uniaxial tensile test; By comparing the difference between the actual data and the simulated data of the uniaxial tensile test, adjusting the crystal plasticity parameters of the crystal plasticity strain gradient analysis function, and determining the crystal plasticity parameters that make the difference less than a preset threshold as the optimal crystal plasticity parameters; The method further comprises performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test, including: Importing the optimal crystal plasticity parameters into the crystal plasticity strain gradient analysis function of the finite element simulation to determine the constitutive relationship of the sample material; By using the crystal plastic strain gradient analysis function, a small punch experiment simulation calculation is performed on the small punch experiment model and the crystal sample model to obtain simulation data of the small punch experiment.

2. The material plastic deformation testing method according to claim 1, characterized in that: The method of determining the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment includes: Acquire actual data of a small punch experiment on the sample material; According to the actual data and simulation data of the small punch experiment, the geometric required dislocation distribution of the sample material at different plastic deformation stages is determined.

3. The material plastic deformation testing method according to any one of claims 1 to 2, characterized in that: Constructing the crystal sample model includes: The crystal sample model is constructed by using a Thiessen polygon algorithm, and each grain in the crystal sample model is given material crystal mechanical properties and grain orientation parameters.

4. The material plastic deformation testing method according to claim 1, characterized in that: The crystal plastic strain gradient analysis function is constructed based on the explicit dynamics analysis stress integration algorithm.

5. The material plastic deformation testing method according to claim 1, characterized in that: The actual data and simulation data of the uniaxial tensile test are both load-displacement curves; The crystal plasticity parameters include: elastic constant, reference shear strain rate, rate sensitivity index, slip system initial yield stress, slip system saturation stress, slip system initial yield hardening modulus.

6. A material plastic deformation testing device, characterized in that: include: An acquisition module, used to obtain the optimal crystal plasticity parameters of the sample material; Construction module, used to construct small punch experimental model and crystal specimen model for finite element simulation; A simulation module, configured to perform finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test; a determination module, configured to determine the strain gradient distribution characteristics of the sample material at different plastic deformation stages based on the simulation data of the small punch experiment; The obtaining of the optimal crystal plasticity parameters of the sample material comprises: Acquiring actual data from a uniaxial tensile test of the sample material; The crystal plastic strain gradient analysis function of finite element simulation is used to simulate and analyze the uniaxial tensile test and obtain the simulation data of the uniaxial tensile test; By comparing the difference between the actual data and the simulated data of the uniaxial tensile test, adjusting the crystal plasticity parameters of the crystal plasticity strain gradient analysis function, and determining the crystal plasticity parameters that make the difference less than a preset threshold as the optimal crystal plasticity parameters; The method further comprises performing finite element simulation based on the optimal crystal plasticity parameters, the small punch test model, and the crystal specimen model to obtain simulation data of the small punch test, including: Importing the optimal crystal plasticity parameters into the crystal plasticity strain gradient analysis function of the finite element simulation to determine the constitutive relationship of the sample material; By using the crystal plastic strain gradient analysis function, a small punch experiment simulation calculation is performed on the small punch experiment model and the crystal sample model to obtain simulation data of the small punch experiment.

7. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images