Material model identification processing device, material model identification processing network system, material model identification processing method, and material model identification processing program

Abstract

This material model identification processing device comprises: a load unit that applies a load in a non-linear stress path to a test piece which is a subject of material model identification; an acquisition unit that acquires a measurement value which indicates the deformation behavior of the test piece in response to the load applied in the non-linear stress path by the load unit; and a presentation unit that presents information pertaining to the difference between the measurement value acquired by the acquisition unit and a calculation value of each of a plurality of predetermined material models.

Description

[Technical field]

[0001] This disclosure , material The present invention relates to a material model identification processing device, a material model identification processing network system, a material model identification processing method, and a material model identification processing program. [Background technology]

[0002] To achieve a highly accurate press forming simulation, it is necessary to perform a highly accurate evaluation of material properties using multi-axial stress testing. The following technologies are available for material testing machines that can be used for this evaluation of material properties.

[0003] Japanese Patent No. 5838165 discloses a material testing machine that applies an internal pressure and an axial stress to a cylindrical test piece to measure the strain of the test piece. This material testing machine is equipped with a plurality of radial displacement detection units that detect the radial displacement of the outer peripheral surface at the center of the effective length in the axial direction of the test piece, and an axial displacement detection unit that detects the axial displacement of the outer peripheral surface at the center of the effective length of the test piece. This material testing machine is also equipped with a calculation unit that calculates the circumferential and axial strains at the center of the effective length of the test piece based on the detection results of the radial displacement detection units and the axial displacement detection unit. This material testing machine is configured so that the plurality of radial displacement detection units detect displacements in different directions around the axis of the test piece. Summary of the Invention [Problem to be solved by the invention]

[0004] The property of a material to undergo permanent deformation is called plasticity, and the general technology of processing materials using plasticity is called plastic processing. Many industrial products made of metal or resin are manufactured using plastic processing.

[0005] In this plastic processing, various forming defects occur, such as breakage, wrinkles, and elastic recovery, which are obstacles to efficient parts manufacturing. Therefore, a method that uses computer-based numerical simulation of processing phenomena (hereinafter referred to as "forming simulation") to predict forming defects in advance and determine optimal die shapes and process designs without trial and error has become the global standard. In this forming simulation, a mathematical model (hereinafter referred to as "material model") is used to reproduce the plastic deformation characteristics of the target material on analysis software.

[0006] As a conventional material testing method for determining an optimal material model, the inventors of the present invention have used test pieces having two types of shapes shown in FIGS.

[0007] The example shown in FIG. 20 is a method in which a load in two orthogonal directions is applied to a cross-shaped test piece in the direction of the arrows in the figure to generate normal stress in two orthogonal directions. This method is described in detail in "Kuwabara, T., Ikeda, S. and Kuroda, T.: Measurement and Analysis of Differential Work Hardening in Cold-Rolled Steel Sheet under Biaxial Tension, J. Material Process. Technol., 80 / 81(1998), 517-523." by the present inventors, so a detailed explanation will be omitted here. Incidentally, this test method was registered as an international standard as ISO16842 in 2014, and is currently approved for continued registration until 2025.

[0008] On the other hand, the example shown in Fig. 21 is a method in which an internal pressure P and an axial force T are applied to a cylindrical test piece to generate normal stresses in two perpendicular directions at the center of the cylindrical test piece. This method is also described in detail in "Kuwabara Toshihiko, Narihara Koji, Yoshida Kengo, Takahashi Susumu: Measurement and Analysis of Plastic Deformation Properties of 5000 Series Aluminum Alloy Tubes Subjected to Axial Force and Internal Pressure, Plasticity and Processing, 44-506 (2003), 281-286" by the present inventors, so a description thereof will be omitted here.

[0009] In both of these material testing methods, a dedicated servo-controlled testing machine is used to measure the stress-strain curves in two orthogonal directions, and a material model is determined based on the data. In both material testing methods, at least nine test pieces must be prepared (usually 18 test pieces are used to increase the reliability of the test), and a linear stress path must be applied to each of them with a different stress ratio, as shown in Figure 22 as an example, which poses the problem that it takes a lot of effort to identify a material model suitable for the test piece.

[0010] Incidentally, the technology disclosed in Japanese Patent No. 5838165 does not take this problem into consideration either, and is therefore ineffective in addressing the problem.

[0011] The present disclosure has been made in consideration of the above problems, and is directed to a method for identifying a material model suitable for a test piece more easily than when a linear stress path is used. Materials The object of the present invention is to provide a material model identification processing device, a material model identification processing network system, a material model identification processing method, and a material model identification processing program. [Means for solving the problem]

[0012] A first aspect of the present disclosure is a stress testing apparatus comprising a loading section that applies a non-linear stress path to a test piece for which a material model is to be identified, an acquisition section that acquires measurement values ​​indicating the deformation behavior of the test piece in response to the loading of the non-linear stress path by the loading section, and a material testing apparatus in which the test piece is mounted and is the subject of loading of the stress path by the loading section and from which the measurement values ​​are acquired by the acquisition section.

[0013] A second aspect of the present disclosure is the stress testing apparatus of the first aspect, wherein the non-linear stress path is at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path.

[0014] A third aspect of the present disclosure is the stress testing apparatus according to the first or second aspect, wherein the test piece is a tubular test piece or a cross-shaped test piece.

[0015] A fourth aspect of the present disclosure is the stress testing apparatus of the third aspect, wherein the test piece is a tubular test piece.

[0016] A fifth aspect of the present disclosure is a stress testing apparatus according to the fourth aspect, wherein the loading section loads the test piece with the non-linear stress path using a biaxial bulge testing apparatus, and the acquisition section acquires the measurement value from the biaxial bulge testing apparatus.

[0017] A sixth aspect of the present disclosure is a material model identification processing device including a loading unit that applies a non-linear stress path to a test piece for which a material model is to be identified, an acquisition unit that acquires measurement values ​​indicating the deformation behavior of the test piece in response to the load of the non-linear stress path by the loading unit, and a presentation unit that presents information regarding the difference between the measurement values ​​acquired by the acquisition unit and calculated values ​​for each of a plurality of predetermined material models.

[0018] A seventh aspect of the present disclosure is a material model identification processing device of the sixth aspect, further comprising an identification unit that identifies a material model having the smallest difference between the measurement value acquired by the acquisition unit and the calculated value based on each of the predetermined plurality of material models as the most suitable material model for the test piece, and the presentation unit presents information indicating the material model identified by the identification unit as information regarding the difference.

[0019] An eighth aspect of the present disclosure is the material model identification processing device according to the sixth or seventh aspect, wherein the presentation unit presents the difference itself in a visually recognizable manner as information relating to the difference.

[0020] A ninth aspect of the present disclosure is a material model identification processing device of any one of the sixth to eighth aspects, wherein the non-linear stress path is at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path.

[0021] A tenth aspect of the present disclosure is the material model identification processing device according to any one of the sixth to ninth aspects, wherein the test piece is a tubular test piece or a cross-shaped test piece.

[0022] An eleventh aspect of the present disclosure is the material model identification processing device of the tenth aspect, wherein the test piece is a cylindrical test piece.

[0023] A twelfth aspect of the present disclosure is a material model identification processing device of the eleventh aspect, wherein the loading unit loads the non-linear stress path on the test piece using a biaxial bulge testing apparatus, and the acquisition unit acquires the measurement value from the biaxial bulge testing apparatus.

[0024] A thirteenth aspect of the present disclosure is the material model identification processing device of any one of the sixth to twelfth aspects, wherein the deformation behavior is a curve showing the relationship between reference plastic strain and stress angle.

[0025] A fourteenth aspect of the present disclosure is a material model identification processing network system having a material model identification processing device including a loading unit that applies a non-linear stress path to a test piece for which a material model is to be identified, an acquisition unit that acquires measurement values ​​indicating the deformation behavior of the test piece in response to the load of the non-linear stress path by the loading unit, and a presentation unit that presents information regarding the difference between the measurement values ​​acquired by the acquisition unit and calculated values ​​for each of a plurality of predetermined material models, an information storage device that stores information indicating the plurality of predetermined material models, and a material testing device in which the test piece is provided, is the subject of the load of the stress path by the loading unit, and is the subject of the acquisition of the measurement values ​​by the acquisition unit.

[0026] A fifteenth aspect of the present disclosure is a material model identification processing network system according to the fourteenth aspect, wherein the material model identification processing device further includes an identification unit that identifies, as the most suitable material model for the test piece, a material model having the smallest difference between the measurement value acquired by the acquisition unit and the calculated value based on each of the predetermined plurality of material models, and the presentation unit of the material model identification processing device presents information indicating the material model identified by the identification unit as information regarding the difference.

[0027] A sixteenth aspect of the present disclosure is directed to a material model identification processing network system according to the fourteenth or fifteenth aspect, wherein the presentation unit of the material model identification processing device presents the difference itself in a visibly recognizable manner as information relating to the difference.

[0028] A seventeenth aspect of the present disclosure is a material model identification processing method, which applies a non-linear stress path to a test piece for which a material model is to be identified, obtains measurements showing deformation behavior of the test piece in response to the load of the non-linear stress path, and presents information regarding the difference between the obtained measurements and calculated values ​​for each of a plurality of predetermined material models.

[0029] An eighteenth aspect of the present disclosure is a material model identification processing program for causing a computer to execute a process of applying a non-linear stress path to a test piece for which a material model is to be identified, obtaining measurements showing deformation behavior of the test piece in response to the load of the non-linear stress path, and presenting information regarding the difference between the obtained measurements and calculated values ​​based on each of a plurality of predetermined material models. Effect of the Invention

[0030] According to the present disclosure, it is possible to more easily identify a material model suitable for a test specimen compared to the case where a linear stress path is used. [Brief description of the drawings]

[0031] [Figure 1]1 is a block diagram showing an example of a hardware configuration of a material model identification processing apparatus according to an embodiment. [Diagram 2] 1 is a block diagram showing an example of a functional configuration of a material model identification processing device according to first and third embodiments. [Diagram 3] 1 is a front view showing an example of a configuration of a material testing device according to an embodiment; [Figure 4] FIG. 2 is a perspective view showing an example of a state in which a test piece according to an embodiment is deformed by a material testing device. [Diagram 5] FIG. 4 is a schematic diagram illustrating an example of a configuration of a stress path database according to the embodiment. [Figure 6] FIG. 2 is a schematic diagram showing an example of a configuration of a material model database according to the embodiment. [Figure 7] 11 is a graph showing an example of command values ​​and measured values ​​of a stress path according to the embodiment. [Figure 8] 8 is a graph showing an example of a comparison result between measured values ​​of deformation behavior of a test piece for the stress path shown in FIG. 7 and calculated values ​​using various material models. [Figure 9A] 1 is a graph showing an example of a comparison result between measurement points of an isoplastic work surface measured by a conventional biaxial bulge test method according to an embodiment and yield curves calculated by various material models. [Figure 9B] FIG. 13 is a schematic diagram showing calculated values ​​and experimental values ​​of a yield curve using a material model in a σx-σy stress space according to an embodiment. [Figure 9C] 13 is a graph showing the change in relative error between the calculated value of the yield surface and the experimental value (equal plastic work surface) using the material model Yld2000-2d with an increase in the reference plastic strain according to the embodiment. [Figure 10] 5 is a flowchart showing an example of a material model identification process according to the first and third embodiments. [Figure 11] 13 is a front view showing an example of the configuration of a stress path selection screen displayed when a material model identification process according to an embodiment is executed. FIG. [Figure 12]FIG. 11 is a front view showing an example of the configuration of an identification result display screen displayed when a material model identification process according to the first and third embodiments is executed. [Figure 13] FIG. 11 is a block diagram showing an example of the functional configuration of a material model identification processing device according to second and third embodiments. [Figure 14] 13 is a flowchart showing an example of a material model identification process according to the second and third embodiments. [Figure 15] FIG. 11 is a front view showing an example of the configuration of a material model identification support screen displayed when a material model identification process according to the second and third embodiments is executed. [Figure 16] FIG. 11 is a block diagram showing an example of a hardware configuration of a material model identification processing network system according to a third embodiment. [Figure 17] 13 is a graph showing another example of a command value of a stress path according to the embodiment. [Figure 18] 18 is a graph showing an example of a comparison result between measured values ​​of deformation behavior of a test piece for the stress path shown in FIG. 17 and calculated values ​​using various material models. [Figure 19] 13 is a graph showing another example of a command value of a stress path according to the embodiment. [Figure 20] FIG. 1 is a front view illustrating an example of a cross-shaped test piece for explaining the prior art. [Figure 21] FIG. 1 is a perspective view illustrating an example of a tubular test piece for explaining the prior art. [Figure 22] FIG. 1 is a diagram for explaining the prior art, and is a graph showing stress paths (arrows) and measurement examples of stress points for a prescribed reference plastic strain on each stress path. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0032] Hereinafter, examples of embodiments of the technology disclosed herein will be described in detail with reference to the drawings. Note that the same or equivalent components and parts in each drawing are given the same reference numerals. Also, the dimensional ratios in the drawings are exaggerated for the convenience of explanation and may differ from the actual ratios.

[0033] [First embodiment] In this embodiment, a case will be described in which the material model identification processing device of the technology disclosed herein is applied to a general-purpose personal computer. However, the application of the material model identification processing device of the technology disclosed herein is not limited to general-purpose personal computers. For example, the material model identification processing device of the technology disclosed herein can be applied to not only dedicated computers but also portable information processing devices such as smartphones, tablet terminals, and notebook personal computers.

[0034] First, the configuration of a material model identification processing device 10 according to this embodiment will be described with reference to Fig. 1 and Fig. 2. Fig. 1 is a block diagram showing an example of the hardware configuration of the material model identification processing device 10 according to this embodiment. Fig. 2 is a block diagram showing an example of the functional configuration of the material model identification processing device 10 according to this embodiment.

[0035] As shown in Fig. 1, the material model identification processing device 10 according to this embodiment includes a CPU (Central Processing Unit) 11, a memory 12 as a temporary storage area, a non-volatile storage unit 13, and an input unit 14 such as a keyboard and a mouse. The material model identification processing device 10 according to this embodiment also includes a display unit 15 such as a liquid crystal display, a medium reading and writing device (R / W) 16, and a communication interface (I / F) unit 18. The CPU 11, the memory 12, the storage unit 13, the input unit 14, the display unit 15, the medium reading and writing device 16, and the communication I / F unit 18 are connected to each other via a bus B. The medium reading and writing device 16 reads information written in a recording medium 17 and writes information to the recording medium 17.

[0036] On the other hand, the storage unit 13 is realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, etc. A material model identification processing program 13A is stored in the storage unit 13 as a storage medium. The material model identification processing program 13A is stored (installed) in the storage unit 13 by setting a recording medium 17, on which the program 13A is written, in the medium reading and writing device 16, and the medium reading and writing device 16 reading the program 13A from the recording medium 17. The CPU 11 reads the material model identification processing program 13A from the storage unit 13, expands it in the memory 12, and sequentially executes the processes of the material model identification processing program 13A.

[0037] In this way, in the material model identification processing device 10 according to this embodiment, the material model identification processing program 13A is installed in the material model identification processing device 10 via the recording medium 17, but this is not limited to this. For example, the material model identification processing program 13A may be installed in the material model identification processing device 10 by downloading it via the communication I / F unit 18.

[0038] Further, a stress path database 13B and a material model database 13C are stored in the storage unit 13. The stress path database 13B and the material model database 13C will be described in detail later.

[0039] In addition, a material testing device 20 that performs material testing on test pieces is connected to the communication I / F unit 18. The material model identification processing device 10 can control the operation of the material testing device 20 and can also acquire measurements by the material testing device 20. The material testing device 20 will also be described in detail later.

[0040] Next, the functional configuration of the material model identification processing device 10 according to this embodiment will be described with reference to Fig. 2. As shown in Fig. 2, the material model identification processing device 10 according to this embodiment includes a load unit 11A, an acquisition unit 11B, an identification unit 11C, and a presentation unit 11D. The CPU 11 of the material model identification processing device 10 executes a material model identification processing program 13A, thereby functioning as the load unit 11A, the acquisition unit 11B, the identification unit 11C, and the presentation unit 11D. Note that the material model identification processing device 10 may be in the form of a stress testing device 10A including the load unit 11A, the acquisition unit 11B, and the material testing device 20.

[0041] The load unit 11A according to the present embodiment applies a nonlinear stress path to a test piece 50 (see also Figs. 3 and 4) to be described later, which is a target for identifying a material model. The load unit 11A functions as a load path creation unit and a calculation value creation unit. The load path creation unit creates a stress path to be applied to the test piece 50. The calculation value creation unit creates calculation values ​​(for example, the direction of an isoplastic work surface or a plastic strain rate) according to various material models for this stress path. In this embodiment, a cylindrical test piece is applied as the test piece 50, but this is not limited thereto. For example, a cross-shaped test piece shown in Fig. 20 may be applied as an example. In this embodiment, the nonlinear stress path is selectively applied to any one of three types of stress paths, namely, a step-shaped stress path, a curved stress path, and a triangular wave-shaped stress path, but this is not limited thereto. For example, a stress path in which two or three of the above three types of stress paths are combined may be applied. That is, as the stress path, all non-linear stress paths, in other words, stress paths made up of a plurality of line segments, curved stress paths, and stress paths that are a combination of these can be applied.

[0042] The acquiring unit 11B according to the present embodiment acquires a measurement value indicating the deformation behavior of the test piece 50 in response to the load of the load unit 11A on the non-linear stress path. In the present embodiment, as an example of information indicating the deformation behavior, a reference plastic strain ε0 pA curve showing the relationship between the reference plastic strain ε0 and the stress angle φ is applied, but this is not limited to this. p Alternatively, a change in the relative error between the calculated value of the yield surface by the material model and the experimental value (equal plastic work surface) accompanying an increase in strain may be applied as information indicating the deformation behavior.

[0043] The presenting unit 11D according to the present embodiment presents information on the difference between the measured value acquired by the acquiring unit 11B and the calculated value by each of a plurality of predetermined material models. In the present embodiment, the difference is expressed as the reference plastic strain ε0 p However, the present invention is not limited to this. For example, the similarity may be derived by performing pattern matching between a curve indicated by the measured value and a curve indicated by the calculated value, and the reciprocal of the similarity may be used as the difference.

[0044] Here, the identification unit 11C according to the present embodiment identifies the material model with the smallest difference as the material model most suitable for the test piece 50. When deriving the above-mentioned similarity as a value related to the difference, the material model with the largest similarity may be identified as the material model most suitable for the test piece 50.

[0045] The presenting unit 11D according to this embodiment presents information indicating the material model identified by the identifying unit 11C as information regarding the difference. Note that, in this embodiment, a model ID, which is previously assigned to the material model and will be described later, is used as the information indicating the material model, but this is not limiting. It goes without saying that any information that can identify the material model can be used as the information indicating the material model.

[0046] Next, the configuration of the material testing device 20 according to this embodiment will be described with reference to Fig. 3. Fig. 3 is a front view showing an example of the configuration of the material testing device 20 according to this embodiment.

[0047] 3, the material testing apparatus 20 according to this embodiment is configured as a biaxial bulge test apparatus that applies an axial force T and a radial internal pressure P independently to a cylindrical test piece 50. The material testing apparatus 20 according to this embodiment has a main body 22, a pair of drive units 30 and 32, a pressure adjustment unit 34, a pair of cameras 38 and 40, and a controller 24 that controls them.

[0048] The pair of drive units 30 and 32 each have a gripping portion 26 and a gripping portion 28 that grip the axial end portion of the test piece 50. With the gripping portion 26 and the gripping portion 28 gripping the axial end portion of the test piece 50, the pair of drive units 30 and 32 move axially to apply an axial force T as a tension or compression force to the test piece 50.

[0049] The pressure adjustment unit 34 is connected to the hollow portion 52 of the test piece 50 via a flow path 36 provided in the drive unit 32. A fluid such as oil is contained in the pressure adjustment unit 34. With the pressure adjustment unit 34 connected to the hollow portion 52 of the test piece 50 via the flow path 36, the fluid is pressurized, thereby applying a radial internal pressure P to the inner wall of the hollow portion 52.

[0050] The pair of cameras 38 and 40 capture images of a predetermined area on the surface of the test piece 50 from different directions. In this case, a pattern is formed in the area of ​​the test piece 50 by spraying black ink on a white background. By capturing an image of this pattern with the cameras 38 and 40 and observing the change in the position of each black dot in the pattern, it is possible to detect how much the area of ​​the test piece 50 is deformed in the axial and circumferential directions. In this case, since the pair of cameras 38 and 40 capture images from different directions, the deformation can be detected three-dimensionally by the principle of stereoscopic vision.

[0051] FIG. 4 is a perspective view showing an example of a state in which the test piece 50 according to the present embodiment is deformed by the material testing device 20. Hereinafter, the axial stress generated in the test piece 50 is referred to as σ x , strain is ε x , the circumferential stress is σy , strain is ε y and are written as follows, respectively.

[0052] The axial force T and the internal pressure P can be controlled independently. However, the test piece 50 deforms from moment to moment in the axial and circumferential directions. Therefore, the stress σ x , σ y , strain ε x , ε y The controller 24 calculates the stress σ x , σ y , strain ε x , ε y is calculated, and the axial force T and internal pressure P are fed back to perform servo control.

[0053] The controller 24 loads the test piece 50 with a stress path according to the command value received from the material model identification processing device 10, while detecting a plurality of predetermined reference plastic strains ε0 p The stress σ x , σ y The stress angle φ obtained from the above is taken as the reference plastic strain ε0 p and output to the material model identification processing device 10.

[0054] The material testing device 20 is also described in detail in JP 2016-15092 A by the inventors of the present invention, so further description will be omitted.

[0055] Next, the stress path database 13B according to this embodiment will be described with reference to Fig. 5. Fig. 5 is a schematic diagram showing an example of the configuration of the stress path database 13B according to this embodiment.

[0056] As shown in Fig. 5, the stress path database 13B according to the present embodiment is for storing information indicating each of the stress paths selected by the user for each predetermined type. As shown in Fig. 5, the stress path database 13B according to the present embodiment stores a stress path ID (Identification) and each piece of information on the stress path in association with each other.

[0057] The stress path ID is a unique ID that is assigned in advance to each of the stress paths in order to individually identify the corresponding stress paths. The stress path is information that indicates the corresponding stress path itself. In the example shown in FIG. 5, the stress path to which the stress path ID "S001" is assigned is a stepped stress path.

[0058] Next, the material model database 13C according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a schematic diagram showing an example of the configuration of the material model database 13C according to this embodiment.

[0059] As shown in Fig. 6, the material model database 13C according to this embodiment is for storing information indicating each of the material models that are applicable for each predetermined type in the material model identification process (see also Fig. 10) described later. As shown in Fig. 6, the material model database 13C according to this embodiment stores model IDs and each piece of information on the material models in association with each other.

[0060] The model ID is a unique ID that is assigned to each material model in advance in order to individually identify the corresponding material model. The material model is information that indicates the corresponding material model itself. In the example shown in FIG. 6, the material model to which the model ID "M001" is assigned is material model 1.

[0061] Here, the principle of the method for identifying a material model in the material model identification process according to this embodiment will be described with reference to Figs. 7 to 9A. Fig. 7 is a graph showing an example of the command value and the measured value of the stress path according to this embodiment. Fig. 8 is a graph showing an example of the comparison result between the measured value of the deformation behavior of the test piece for the stress path shown in Fig. 7 and the calculated value by various material models. Fig. 9A is a graph showing an example of the comparison result between the measurement point of the isoplastic work surface measured by the conventional biaxial bulge test method according to this embodiment and the yield curve calculated by various material models.

[0062] The inventors of the present invention conducted a test using a biaxial bulge tester to load a stepped stress path onto two types of test pieces formed into a cylindrical shape from mild steel plate. Prior to this test, the inventors of the present invention prepared three types of material models, namely, von Mises, r-Hill'48, and Yld2000-2d.

[0063] As an example, as shown in Fig. 7, the results of this test confirmed that the measured values ​​for both types of test specimens (labeled "Exp.1" and "Exp.2" in Fig. 7) tracked the command value (labeled "Reference" in Fig. 7) with high precision.

[0064] In addition, the inventors determined a reference plastic strain ε0 p A curve showing the relationship between the stress angle φ and the measured value (corresponding to the above-mentioned "measured value" and hereinafter referred to as "measured value") was obtained. The graph shown in Fig. 8 shows the measured value of one of the test pieces (Exp.1) and the calculated values ​​using the above-mentioned three types of material models superimposed on each other.

[0065] As shown in Fig. 8, in this case, the calculated values ​​of Yld2000-2d were almost in agreement with the measured values ​​of the test specimen (Exp.1), and the material model suitable for the test specimen (Exp.1) was identified as Yld2000-2d.

[0066] On the other hand, as shown in Figure 9A, the yield curve of Yld2000-2d obtained by the conventional biaxial bulge test method almost coincides with the measured values ​​for the test specimen (Exp.1), confirming that Yld2000-2d is the material model suitable for the test specimen (Exp.1).

[0067] This result is consistent with the material model identification result shown with reference to FIG. 8, and thus the validity of the material model identification method developed by the inventors of the present invention was verified. The inventors of the present invention have found that the above validity is the same not only for one type of test piece but also for other types of test pieces. As will be described later, similar results have been obtained for the shape of the stress path applied to the test piece, not only for a step-like shape but also for a triangular wave-like stress path (see FIG. 17 and FIG. 18). Furthermore, it is considered that the method can be applied to not only steel materials but also other types of metals such as aluminum in the same manner as the target materials.

[0068] FIG. 9B shows the x -σ y 9B is a schematic diagram showing the calculated values ​​(solid line) and experimental values ​​(constant plastic work surface) of the yield curve by the material model in the stress space. In Fig. 9B, δ represents the distance from the origin to the experimental value (constant plastic work surface), and δ' represents the distance from the origin to the calculated value (solid line) of the yield curve.

[0069] On the other hand, Fig. 9C shows the results for the reference plastic strain ε0 p 9C is a graph showing the change in the relative error between the calculated value of the yield surface by the material model Yld2000-2d and the experimental value (isoplastic work surface) with increasing stress. Note that the solid line in FIG. 9C is a curve showing the relative error with the isoplastic work surface identified from the nonlinear stress path, and the dashed line is a curve showing the relative error with the isoplastic work surface identified from the linear stress path. As shown in FIG. 9C, the relative error with the calculated value is less than 2% for both stress paths, and it can be seen that the identification accuracy of the material models is equivalent.

[0070] In the conventional method of identifying a material model by applying a linear stress path, as described with reference to FIG. 22 as an example, it was necessary to apply a stress path with a different stress ratio to at least nine test pieces. This is because only one physical quantity for identifying a material model can be obtained by applying a linear stress path once. In contrast, in the material model identification method according to the present embodiment, a large number of physical quantities for identifying a material model can be obtained as surfaces by applying a nonlinear stress path once. Therefore, with this identification method, even if only one measurement is performed on one test piece, a material model suitable for that test piece can be accurately identified.

[0071] Next, the operation of the material model identification processing device 10 according to this embodiment will be described with reference to Figs. 10 to 12. Fig. 10 is a flow chart showing an example of the material model identification processing according to this embodiment. Fig. 11 is a front view showing an example of the configuration of a stress path selection screen displayed when the material model identification processing according to this embodiment is performed. Fig. 12 is a front view showing an example of the configuration of an identification result presentation screen displayed when the material model identification processing according to this embodiment is performed.

[0072] The CPU 11 of the material model identification processing device 10 executes the material model identification processing program 13A, thereby executing the material model identification processing shown in Fig. 10. The material model identification processing shown in Fig. 10 is executed when a user inputs an instruction to start the execution of the material model identification processing program 13A via the input unit 14. In order to avoid confusion, the following will be described in the case where the stress path database 13B and the material model database 13C have already been constructed. In addition, the following will be described in the case where the test piece 50 is provided at a predetermined measurement position of the material testing device 20 in the state shown in Fig. 3 as an example.

[0073] In step 100 of FIG. 10, the CPU 11 controls the display unit 15 to display a stress path selection screen having a predetermined configuration, and in step 102, the CPU 11 waits until predetermined information is input.

[0074] As shown in Fig. 11, the stress path selection screen according to this embodiment displays a message prompting the selection of a stress path. In addition, the stress path selection screen according to this embodiment displays a designation frame 15A, which is designated when selecting a stress path to be applied in the current material model identification process from among a plurality of types of predefined stress paths, together with information indicating the type (shape) of the stress path.

[0075] 11 is displayed on the display unit 15, the user designates the designation frame 15A corresponding to the stress path to be applied using the input unit 14. When the user designates any one of the designation frames 15A, the result of step 102 is affirmative, and the process proceeds to step 104.

[0076] In step 104, the CPU 11 reads out information indicating the stress path specified by the user (hereinafter referred to as the "applied stress path") from the stress path database 13B. In step 106, the CPU 11 transmits instruction information to the material testing device 20 to start applying a load to the test piece 50 along the applied stress path together with information indicating the applied stress path (corresponding to the above-mentioned "command value"). Upon receiving this instruction information, the controller 24 of the material testing device 20 starts applying a load to the test piece 50 along the applied stress path indicated by the received information, and also starts transmitting information indicating the above-mentioned measured values ​​measured in response to this load to the material model identification processing device 10.

[0077] Therefore, in step 108, CPU 11 starts storing the measurement values ​​indicated by the information received from material testing device 20 in memory unit 13 at predetermined intervals (0.1 seconds in this embodiment). In step 110, CPU 11 waits until a period (10 minutes in this embodiment) predetermined as a measurement period by material testing device 20 has elapsed.

[0078] In step 112, the CPU 11 ends the storage of the measured values ​​in the memory unit 13, which was started by the processing of step 108. In step 114, the CPU 11 transmits instruction information to the material testing apparatus 20 to end the load on the test piece 50 of the applied stress path, which was started by the processing of step 106. Upon receiving this instruction information, the controller 24 of the material testing apparatus 20 ends the load on the test piece 50 of the applied stress path, and also ends the transmission of information indicating the measured values ​​to the material model identification processing apparatus 10.

[0079] In step 116, the CPU 11 reads out the measured value stored by the above process from the storage unit 13. In step 118, the CPU 11 derives the difference between the read out measured value and a calculated value based on any one of the multiple material models (hereinafter referred to as the "target material model") stored in the material model database 13C as described above. Then, the CPU 11 stores the derived difference in the storage unit 13 in association with the target material model.

[0080] In step 120, the CPU 11 judges whether or not the process of step 118 has been completed for all of the multiple material models stored in the material model database 13C. If the judgment is negative, the process returns to step 118, whereas if the judgment is positive, the process proceeds to step 122. When repeatedly executing the processes of steps 118 to 120, the CPU 11 applies a material model that has not been the target so far as a target material model. Through the above process, the above differences are derived for all material models prepared in advance and stored in the storage unit 13.

[0081] In step 122, the CPU 11 identifies the material model (hereinafter referred to as the “identified material model”) that has the smallest difference among the pre-prepared material models stored in the memory unit 13 as the material model most suitable for the test piece 50.

[0082] In step 124, the CPU 11 controls the display unit 15 to display an identification result presentation screen having a predetermined structure, and in step 126, the CPU 11 waits until predetermined information is input.

[0083] As shown in Fig. 12, the identification result display screen according to this embodiment displays information indicating the identified material model (in the example shown in Fig. 12, a material model ID). Therefore, the user can understand the identified material model by referring to the identification result display screen.

[0084] 12 is displayed on the display unit 15, the user checks the displayed identified material model, and then selects the end button 15E using the input unit 14. When the end button 15E is selected by the user, an affirmative determination is made in step 126, and the material model identification process is terminated.

[0085] As described above, according to this embodiment, a non-linear stress path is applied to the test piece, measurements showing the deformation behavior of the test piece in response to the non-linear stress path are obtained, and information on the difference between the obtained measurements and the calculated values ​​using each of a plurality of predetermined material models is presented. Therefore, the material model can be identified by only one measurement, and as a result, the material model suitable for the test piece can be identified more easily than when a linear stress path is used.

[0086] According to the present embodiment, the material model having the smallest difference between the acquired measured value and the calculated value from each of the plurality of predetermined material models is identified as the most suitable material model for the test piece, and information indicating the identified material model is presented as information regarding the difference. Therefore, the material model can be more easily identified compared to the case where the computer does not identify the most suitable material model for the test piece.

[0087] In addition, according to the present embodiment, the non-linear stress path is any one of a step-like stress path, a curved stress path, and a triangular wave stress path. Therefore, the material model can be appropriately identified according to the type of the applied stress path.

[0088] In addition, according to the present embodiment, a cylindrical test piece is used as the test piece, which allows material testing over a wider range of stresses to be performed compared to the case where a cross-shaped test piece is used as the test piece.

[0089] According to the present embodiment, a biaxial bulge test apparatus is used to apply a non-linear stress path to a test piece, and measurements are obtained from the biaxial bulge test apparatus, so that a material test can be performed with higher accuracy than when a material test apparatus using only a single axis is used.

[0090] Furthermore, according to this embodiment, a curve showing the relationship between the reference plastic strain and the stress angle is applied as the deformation behavior. Therefore, by comparing the relationship curve between the reference plastic strain and the stress angle measured by an experiment with the calculated curve between the reference plastic strain and the stress angle according to the assumed material model, the difference between the two is visualized, and the suitability of the assumed material model can be easily determined.

[0091] In this embodiment, the identified material model is presented by displaying it on the display unit, but the present invention is not limited to this. For example, the identified material model may be presented by voice output from a voice output unit such as a microphone, or may be presented by printing it on an image forming device such as a printer.

[0092] [Second embodiment] In the first embodiment, an example of a case where a material model with the smallest difference between the measured value and the calculated value is automatically identified as the material model most suitable for the test piece is described. In the second embodiment, an example of a case where the difference between the measured value and the calculated value itself is visually displayed is described.

[0093] Since the hardware configuration of the material model identification processing device 10 according to this embodiment is the same as that of the material model identification processing device 10 of the first embodiment, the functional configuration of the material model identification processing device 10 according to this embodiment will be described below with reference to Fig. 13. Fig. 13 is a block diagram showing an example of the functional configuration of the material model identification processing device according to this embodiment. Note that the same components in Fig. 13 as those in Fig. 2 are given the same reference symbols as those in Fig. 2, and their description will be omitted.

[0094] As shown in Figure 13, the material model identification processing device 10 of this embodiment differs from the material model identification processing device 10 of the first embodiment only in that it does not have an identification unit 11C and that the presentation unit 11D is a presentation unit 11E that performs processing different from that of the presentation unit 11D.

[0095] In other words, the presentation unit 11E of this embodiment differs from the presentation unit 11D of the material model identification processing device 10 of the first embodiment in that it presents the difference itself visibly as information relating to the difference between the measured value and the calculated value described above.

[0096] The configurations of the material testing device 20, stress path database 13B, and material model database 13C according to this embodiment are similar to those according to the first embodiment (see FIGS. 3 to 6), and therefore will not be described here.

[0097] Next, the operation of the material model identification processing device 10 according to this embodiment will be described with reference to Figs. 14 and 15. Fig. 14 is a flow chart showing an example of the material model identification processing according to this embodiment. Fig. 15 is a front view showing an example of the configuration of a material model identification support screen displayed when the material model identification processing according to this embodiment is executed. Note that the steps in Fig. 14 that execute the same processing as in Fig. 10 are given the same step numbers as in Fig. 10, and their description will be omitted.

[0098] As shown in FIG. 14, the material model identification process according to this embodiment differs from the material model identification process according to the first embodiment only in that the processes of steps 130 to 132 are executed instead of the processes of steps 118 to 126.

[0099] That is, in step 130, the CPU 11 controls the display unit 15 to display a material model identification support screen having a predetermined configuration using the measured values ​​obtained by the processing up to that point and the calculated values ​​based on the multiple material models stored in the material model database 13C. Then, in step 132, the CPU 11 waits until predetermined information is input.

[0100] As shown in Fig. 15, in the material model identification support screen according to this embodiment, the above-mentioned measured values ​​and calculated values ​​using a plurality of pre-prepared material models are superimposed in the same range and visually displayed in the same manner as the graph shown in Fig. 8. Therefore, by referring to the material model identification support screen, the user can visually compare the deformation behavior states of the test piece 50 and each material model, and can identify a material model suitable for the test piece 50 at his / her own discretion.

[0101] 15 is displayed on the display unit 15, the user grasps the state of the deformation behavior of the test piece 50 and each material model, and then selects the end button 15E using the input unit 14. When the end button 15E is selected by the user, an affirmative judgment is made in step 132, and the material model identification process ends.

[0102] As described above, according to the present embodiment, the difference itself is presented in a visually recognizable manner as information relating to the difference, and therefore a material model suitable for the test piece can be identified based on the user's judgment.

[0103] [Third embodiment] In the first and second embodiments, an example of a case where processing related to identification of a material model is performed by a single material model identification processing device 10 has been described. In the present embodiment, an example of a case where processing related to identification of a material model is performed using a plurality of devices including the material model identification processing device 10 will be described.

[0104] FIG. 16 is a block diagram showing an example of the hardware configuration of a material model identification processing network system 90 according to this embodiment.

[0105] As shown in FIG. 16, the material model identification processing network system 90 according to the present embodiment includes a material model identification processing device 10, a material testing device 20, and an information storage device 70, each of which is accessible to a network 80. Examples of the information storage device 70 include information processing devices such as a personal computer and a server computer. Examples of the network 80 include various wired and wireless networks such as the Internet, an intranet, a LAN (Local Area Network), and a telephone line network. In the present embodiment, the information storage device 70 is provided as a cloud server provided in a location different from the material model identification processing device 10 and the material testing device 20, but is not limited thereto. For example, the information storage device 70 may be provided in the same location as the material model identification processing device 10 and the material testing device 20, or the material model identification processing device 10, the material testing device 20, and the information storage device 70 may be provided in different remote locations.

[0106] The material testing apparatus 20 according to this embodiment is similar to those of the first and second embodiments. The material model identification processing device 10 according to this embodiment is also similar to those of the first and second embodiments. However, the material model identification processing network system 90 according to this embodiment is different from the above-mentioned embodiments only in that the material model database 13C is not stored in the material model identification processing device 10 but is stored in the storage unit 73 of the information storage device 70.

[0107] Therefore, in the material model identification processing (see Figures 10 and 14) executed by the material model identification processing program 13A in the material model identification processing device 10 of this embodiment, when accessing the material model database 13C, the information storage device 70 is accessed.

[0108] As described above, according to this embodiment, the material model identification processing device 10 includes a load unit 11A that loads a nonlinear stress path on a test piece to be identified as a material model, an acquisition unit 11B that acquires a measurement value indicating the deformation behavior of the test piece according to the load of the nonlinear stress path by the load unit 11A, and a presentation unit 11D (or presentation unit 11E) that presents information on the difference between the measurement value acquired by the acquisition unit 11B and the calculated value by each of a plurality of predetermined material models, an information storage device 70 that stores information indicating the above-mentioned plurality of predetermined material models, and a material testing device 20 on which a test piece is provided, which is the target of the load of the stress path and the target of the measurement value acquisition. Therefore, in this embodiment, too, a material model suitable for the test piece can be identified more easily than when a linear stress path is used.

[0109] In the above-mentioned embodiments, only the step-like stress path shown in FIG. 7 is illustrated as an example, but an example of the above-mentioned triangular stress path is shown in FIG. 17. The comparison result between the measured value of the deformation behavior of the test piece for the stress path in this case and the calculated value by various material models is shown in FIG. 18. As shown in FIG. 18, even when the triangular stress path shown in FIG. 17 is applied, the calculated value of Yld2000-2d almost coincides with the measured value of the test piece (Exp.1) as in the above-mentioned embodiments. Therefore, in this case as well, the material model suitable for the test piece (Exp.1) is identified as Yld2000-2d.

[0110] Moreover, an example of the above-mentioned curved stress path is shown in Fig. 19. As shown in Fig. 19, the curved shape here does not have to have any particular regularity, and in short, any non-linear shape can be used as the stress path.

[0111] In each of the above embodiments, for example, the hardware structure of the processing unit that executes each process of the load unit 11A, the acquisition unit 11B, the identification unit 11C, the presentation unit 11D, and the presentation unit 11E can use various processors as shown below. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacture such as an FPGA (Field-Programmable Gate Array), a dedicated electric circuit, which is a processor having a circuit configuration designed specifically for executing specific processes such as an ASIC (Application Specific Integrated Circuit), etc.

[0112] The processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA).The processing unit may also be configured with a single processor.

[0113] As an example of configuring the processing unit with one processor, first, there is a form in which one processor is configured with a combination of one or more CPUs and software, as represented by computers such as client and server, and this processor functions as the processing unit. Second, there is a form in which a processor is used that realizes the functions of the entire system including the processing unit with one IC (Integrated Circuit) chip, as represented by System On Chip (SoC), etc. In this way, the processing unit is configured using one or more of the above various processors as a hardware structure.

[0114] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements.

[0115] The disclosure of Japanese Patent Application No. 2021-028672, filed on February 25, 2021, is incorporated herein by reference in its entirety. All documents, patent applications, and technical standards described herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

[0116] The above embodiment may be implemented as a non-transitory storage medium storing the program. Examples of the non-transitory storage medium include a CD-ROM (Compact Disc Read Only Memory), a magneto-optical disk, a HDD, a DVD-ROM (Digital Versatile Disc Read Only Memory), a flash memory, and a memory card.

[0117] Regarding the above embodiment, the following supplementary notes are disclosed. (Additional note 1) A non-transitory storage medium storing a program executable by a computer to perform a material model identification process, The material model identification process includes: A nonlinear stress path is applied to a test piece for which a material model is to be identified; obtaining measurements indicative of deformation behavior of the test specimen in response to loading of the non-linear stress path; Present information regarding the difference between the acquired measured value and the calculated value using each of a plurality of predefined material models. Non-transitory storage medium.

Claims

1. a loading unit that loads a non-linear stress path selected from at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path on a cylindrical test piece that is a target for identifying a material model; an acquisition unit that acquires a measurement value that indicates a deformation behavior of the test piece in response to a load of a non-linear stress path by the loading unit; a presentation unit that presents information regarding a difference between the measurement value acquired by the acquisition unit and a calculated value using each of a plurality of predetermined material models; A material model identification processing device comprising:

2. the presentation unit presents the difference itself in a visually recognizable manner in the same range as information regarding the difference from the calculated value based on each of the plurality of predetermined material models, thereby enabling a user to identify the material model; The material model identification processing device according to claim 1 .

3. The loading section applies the non-linear stress path to the test piece using a biaxial bulge test device; The acquisition unit acquires the measurement values ​​from the biaxial bulge test apparatus. The material model identification processing device according to claim 1 or 2.

4. The deformation behavior is a curve showing the relationship between the reference plastic strain and the stress angle; The material model identification processing device according to claim 3 .

5. a material model identification processing device including: a loading unit that loads a non-linear stress path selected from at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path on a tubular test piece to be identified as a material model; an acquisition unit that acquires measured values ​​showing deformation behavior of the test piece in response to the load of the non-linear stress path by the loading unit; and a presentation unit that presents information regarding differences between the measured values ​​acquired by the acquisition unit and calculated values ​​for each of a plurality of predetermined material models; an information storage device that stores information indicating the plurality of predetermined material models; a material testing device in which the test piece is provided, the stress path is loaded by the loading unit, and the measurement value is acquired by the acquisition unit; A material model identification processing network system having the above structure.

6. The loading section applies the non-linear stress path to the test piece using a biaxial bulge test device; The acquisition unit acquires the measurement values ​​from the biaxial bulge test apparatus.

6. A material model identification processing network system according to claim 5.

7. the presentation unit of the material model identification processing device presents the difference itself in a visually recognizable manner in the same range as information regarding the difference from the calculated value based on each of the plurality of predetermined material models, thereby enabling a user to identify the material model.

7. A material model identification processing network system according to claim 5 or 6.

8. Using a biaxial bulge test apparatus, a non-linear stress path selected from at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path is applied to a test piece to be identified as a material model; obtaining measurements from the biaxial bulge test apparatus indicative of deformation behavior of the test specimen in response to loading along the non-linear stress path; As information on the difference between the acquired measured value and the calculated value based on each of a plurality of predetermined material models, the difference itself is displayed in a visually recognizable manner in the same range, thereby enabling the user to identify the material model. Material model identification processing method.

9. Using a biaxial bulge test apparatus, a non-linear stress path selected from at least one of a step-like stress path, a curved stress path, and a triangular wave-like stress path is applied to a test piece to be identified as a material model; obtaining measurements from the biaxial bulge test apparatus indicative of deformation behavior of the test specimen in response to loading along the non-linear stress path; As information on the difference between the acquired measured value and the calculated value based on each of a plurality of predetermined material models, the difference itself is displayed in a visually recognizable manner in the same range, thereby enabling the user to identify the material model. A material model identification processing program for causing a computer to execute the processing.

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