Constitutive curve construction method, device, equipment and computer-readable storage medium

Abstract

A constitutive curve construction method, device, equipment, and computer-readable storage medium. The method includes: obtaining a first test data set obtained from a preset test conducted on a sample; extracting a first sub-test data set from the first test data set; determining a first curve based on the first sub-test data set, the first curve being used to characterize the relationship between true stress and plastic strain; extracting a second sub-test data set from the first test data set; determining a second curve based on the second sub-test data set, the second curve being used to characterize the relationship between true stress and plastic strain; splicing the first curve and the second curve to obtain a spliced ​​curve; deleting the curve segment corresponding to the failure stage of the sample from the spliced ​​curve, and using the remaining curve segment as the constitutive curve of the sample under the preset test. Through the present application, a constitutive curve is constructed based on the test data, so that the constructed constitutive curve can more accurately characterize the mechanical characteristics of the material.

Description

Technical Field

[0001] The present application relates to the technical field of material performance testing, and in particular to a constitutive curve construction method, device, equipment and computer-readable storage medium. Background Art

[0002] In existing technologies, constitutive curves for plastic materials are determined by fitting the software's built-in functional constitutive models with a few numerical parameters. Because the software's built-in functional constitutive models are limited in number and cannot be automatically modified, and because some modified thermoplastic materials have varying properties that are difficult to characterize using a unified functional model, constitutive curves constructed using existing methods cannot accurately represent the properties of modified thermoplastic materials. Summary of the Invention

[0003] The present application provides a constitutive curve construction method, device, equipment and computer-readable storage medium, which can solve the technical problem in the prior art that constitutive curves cannot accurately characterize the performance of modified thermoplastic materials.

[0004] In a first aspect, an embodiment of the present application provides a constitutive curve construction method, the constitutive curve construction method comprising:

[0005] Acquire a first test data set obtained from a preset test performed on the sample, wherein the first test data set includes a true stress and a true strain corresponding to each sampling moment during the preset test process;

[0006] Determine the first sampling moment corresponding to the yield point;

[0007] Determine the second sampling moment corresponding to the necking point;

[0008] Extracting a first sub-test data set corresponding to a first sampling period from the first test data set, where the start time of the first sampling period is a first sampling time and the end time is a second sampling time;

[0009] determining a first curve based on the first sub-test data set, where the first curve is used to represent the relationship between true stress and plastic strain;

[0010] Extracting a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment;

[0011] determining a second curve based on the second sub-test data set, where the second curve is used to represent the relationship between the true stress and the plastic strain;

[0012] splicing the first curve and the second curve to obtain a spliced ​​curve;

[0013] The curve segments corresponding to the failure stage of the sample are deleted from the splicing curve, and the remaining curve segments are used as the constitutive curves of the sample under the preset test.

[0014] In conjunction with the first aspect, in one embodiment, before the step of determining the first sampling time corresponding to the yield point, the method further includes:

[0015] determining a third curve based on the first test data set, where the third curve is used to represent the relationship between true stress and true strain;

[0016] Determine a curve segment corresponding to a preset true strain interval on the third curve;

[0017] The slope of the regression line corresponding to the curve segment is determined based on the linear least squares method and used as the Young's modulus;

[0018] Draw a straight line having a slope of Young's modulus and passing through a preset coordinate point, wherein the preset coordinate point corresponds to a preset true strain and a preset true stress;

[0019] The intersection of the third curve and the straight line is taken as the yield point.

[0020] In combination with the first aspect, in one embodiment, before the step of determining the second sampling time corresponding to the necking point, the method further includes:

[0021] Convert the true strain corresponding to each sampling moment in the first test data set into the plastic strain to obtain the second test data set;

[0022] The third test data set is obtained by multiplying the true stress corresponding to each sampling moment in the second test data set by the corresponding proportional coefficient, wherein the proportional coefficient corresponding to the true stress corresponding to a sampling moment is determined based on the plastic Poisson's ratio corresponding to the plastic strain corresponding to the sampling moment;

[0023] determining a fourth curve based on the second test data set, where the fourth curve is used to represent the relationship between true stress and plastic strain;

[0024] determining a derivative curve corresponding to the fourth curve;

[0025] determining a fifth curve based on the third experimental data set;

[0026] The intersection of the derivative curve and the fifth curve is taken as the necking point.

[0027] In conjunction with the first aspect, in one embodiment, the step of determining the first curve based on the first sub-test data set includes:

[0028] Convert the true strain corresponding to each sampling moment in the first sub-test data set into plastic strain to obtain a new first sub-test data set;

[0029] A first curve is obtained based on the new first sub-experimental data set.

[0030] In combination with the first aspect, in one embodiment, the step of determining the second curve based on the second sub-test data set includes:

[0031] Based on the true stress corresponding to the earlier sampling moment in the second sub-test data set, the true stress corresponding to the later sampling moment is updated, and the true strain corresponding to each sampling moment in the second sub-test data set is converted into plastic strain to obtain a new second sub-test data set;

[0032] For the new second sub-test data set, the true stress corresponding to each sampling moment in the new second sub-test data set and the true stress corresponding to the necking point are weightedly summed to obtain the third sub-test data set;

[0033] A second curve is obtained based on the third sub-experimental data set.

[0034] In conjunction with the first aspect, in one embodiment, after the step of deleting the curve segments corresponding to the failure stage of the sample from the splicing curve and using the remaining curve segments as the constitutive curve of the sample under the preset test, the method further includes:

[0035] Acquire a simulation data set obtained by simulating the sample, wherein the simulation data set includes the displacement at the force-bearing point of the sample corresponding to each simulation moment during the simulation process and the external load at the force-bearing point of the sample, wherein the simulation and the preset test correspond to the same test conditions;

[0036] The displacement at the stress point of the sample corresponding to the target simulation time corresponding to the failure stage of the sample in the simulation data set and the external load at the stress point of the sample are deleted to obtain a new simulation data set;

[0037] Determine the true stress and plastic strain corresponding to each simulation moment in the new simulation data set based on the constitutive curve as labels;

[0038] Training an extreme learning machine based on the new simulation data set and the labels to obtain a trained extreme learning machine;

[0039] Obtaining a second test data set obtained from a preset test performed on the sample, the second test data set including the displacement at the force-bearing point of the sample and the applied load at the force-bearing point of the sample corresponding to each sampling moment during the preset test;

[0040] The displacement at the stress point of the sample corresponding to the target sampling time corresponding to the failure stage of the sample and the external load at the stress point of the sample are deleted in the second test data set to obtain a new second test data set;

[0041] Input the new second test data set into the trained extreme learning machine;

[0042] The modified constitutive curve is constructed based on the output of the trained extreme learning machine.

[0043] In combination with the first aspect, in one embodiment, the constitutive curve construction method further includes:

[0044] Receiving an expiration start time based on user operation input;

[0045] Determine the failure stage of the sample based on the failure initiation time.

[0046] In a second aspect, an embodiment of the present application provides a constitutive curve construction device, the constitutive curve construction device comprising:

[0047] an acquisition module, configured to acquire a first test data set obtained from a preset test performed on a sample, wherein the first test data set includes a true stress and a true strain corresponding to each sampling moment during the preset test process;

[0048] A first determining module, configured to determine a first sampling moment corresponding to a yield point;

[0049] The first determining module is further used to determine a second sampling time corresponding to the necking point;

[0050] an extraction module, configured to extract a first sub-test data set corresponding to a first sampling period from the first test data set, wherein the start time of the first sampling period is the first sampling time and the end time is the second sampling time;

[0051] a second determining module, configured to determine a first curve based on the first sub-test data set, wherein the first curve is used to represent a relationship between true stress and plastic strain;

[0052] The extraction module is further configured to extract a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment;

[0053] The second determination module is further used to determine a second curve based on the second sub-test data set, where the second curve is used to represent the relationship between the true stress and the plastic strain;

[0054] A splicing processing module, configured to splice the first curve and the second curve to obtain a spliced ​​curve;

[0055] The deletion module is used to delete the curve segments corresponding to the failure stage of the sample from the splicing curve, and use the remaining curve segments as the constitutive curve of the sample under the preset test.

[0056] In a third aspect, an embodiment of the present application provides a constitutive curve construction device, which includes a processor, a memory, and a constitutive curve construction program stored in the memory and executable by the processor, wherein when the constitutive curve construction program is executed by the processor, the steps of the constitutive curve construction method described in the first aspect are implemented.

[0057] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a constitutive curve construction program is stored, wherein when the constitutive curve construction program is executed by a processor, the steps of the constitutive curve construction method described in the first aspect are implemented.

[0058] The beneficial effects of the technical solutions provided in the embodiments of the present application include:

[0059] In an embodiment of the present application, a first test data set obtained from a preset test on a sample is obtained, the first test data set including the true stress and true strain corresponding to each sampling moment during the preset test process; a first sampling moment corresponding to a yield point is determined; a second sampling moment corresponding to a necking point is determined; a first sub-test data set corresponding to a first sampling period is extracted from the first test data set, the start moment of the first sampling period is the first sampling moment, and the end moment is the second sampling moment; a first curve is determined based on the first sub-test data set, the first curve is used to characterize the relationship between true stress and plastic strain; a second sub-test data set corresponding to a second sampling period is extracted from the first test data set, the second sampling period is the test period after the second sampling moment; a second curve is determined based on the second sub-test data set, the second curve is used to characterize the relationship between true stress and plastic strain; the first curve and the second curve are spliced ​​to obtain a spliced ​​curve; the curve segment corresponding to the failure stage of the sample is deleted from the spliced ​​curve, and the remaining curve segment is used as the constitutive curve of the sample under the preset test. Through the embodiment of the present application, a constitutive curve is constructed based on the test data, so that the constructed constitutive curve can more accurately characterize the mechanical characteristics of the material. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a flow chart of an embodiment of the constitutive curve construction method of the present application;

[0061] Figure 2 Schematic diagram of the scenario for determining the yield point;

[0062] Figure 3 Schematic diagram of the scenario for determining the necking point;

[0063] Figure 4 Schematic diagram of the ductile behavior characterization curve and the softening behavior characterization curve;

[0064] Figure 5This is a schematic diagram of the functional modules of an embodiment of the constitutive curve construction device of the present application;

[0065] Figure 6 Schematic diagram of the hardware structure of the constitutive curve construction device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0066] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0067] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0068] In a first aspect, an embodiment of the present application provides a constitutive curve construction method.

[0069] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of an embodiment of the constitutive curve construction method of this application. Figure 1 As shown in Figure 2, the constitutive curve construction method includes:

[0070] Step S10, obtaining a first test data set obtained from a preset test performed on the sample, wherein the first test data set includes the true stress and true strain corresponding to each sampling moment in the preset test process;

[0071] In this embodiment, the preset test performed on the sample can be any of the following:

[0072] The sample was subjected to static stretching at 0.01 / s;

[0073] Dynamic stretching at different loading rates of 1 / s, 10 / s, 100 / s, and 400 / s;

[0074] 0.01 / s static shear;

[0075] 0.01 / s static compression test.

[0076] Among them, static tension, dynamic tension, static shear, and static compression adopt corresponding test standards. The selection of test standards is conventional technology and will not be elaborated here.

[0077] During the preset test of the sample, a DIC visual camera is used to capture the strain ε along the length of the sample. eng，X, strain ε along the width direction of the sample eng，Y and the strain ε along the thickness direction of the specimen eng，Z The image capture rate is 30 frames per second. A CMT5205 electronic universal testing machine is used to record the displacement and applied load at each sampling point on the specimen. The data collected by the DIC vision camera and the CMT5205 electronic universal testing machine are used to construct a test dataset corresponding to a pre-determined test.

[0078] Furthermore, in order to reduce the error, each preset test is performed three times, and the two groups of test data sets with smaller deviations are averaged to obtain the initial test data set corresponding to the preset test.

[0079] Based on the initial test data set, the engineering stress σ corresponding to each sampling moment is first calculated eng and engineering strain ε eng :

[0080]

[0081] Where Δx represents the displacement of the specimen at the force-bearing point at each sampling moment, x represents the gauge length of the specimen, A0 represents the cross-sectional area of ​​the specimen within the gauge length in the initial state, and F represents the applied load at the force-bearing point of the specimen at each sampling moment.

[0082] Furthermore, the engineering stress σ corresponding to each sampling moment is eng and engineering strain ε eng Convert to true stress σ ture and true strain ε ture :

[0083]

[0084] ε ture =ln(1+ε eng )

[0085] At this point, a first test data set including the true stress and true strain corresponding to each sampling moment in the preset test process can be obtained.

[0086] Step S20, determining a first sampling moment corresponding to the yield point;

[0087] In this embodiment, a true stress-true strain relationship curve is first determined based on the first test data set, and then the coordinates of the yield point are determined on the relationship curve. The sampling time corresponding to the true stress and true strain closest to the coordinates of the yield point in the first test data set is used as the first sampling time corresponding to the yield point.

[0088] Furthermore, in one embodiment, before step S20, the method further includes:

[0089] A third curve is determined based on the first experimental data set, and the third curve is used to characterize the relationship between true stress and true strain; a curve segment corresponding to a preset true strain interval on the third curve is determined; a slope of a regression line corresponding to the curve segment is determined based on the linear least squares method and used as the Young's modulus; a straight line with a slope equal to the Young's modulus and passing through a preset coordinate point is drawn, and the preset coordinate point corresponds to a preset true strain and a preset true stress; and the intersection of the third curve and the straight line is used as the yield point.

[0090] In this embodiment, refer to Figure 2 , Figure 2 Schematic diagram of the scenario for determining the yield point. Figure 2 As shown in the figure, since the first test data set contains the true stress and true strain corresponding to each sampling moment, it is reflected in Figure 2 In the coordinate system shown, the true stress and true strain corresponding to each sampling moment are represented by a coordinate point. Fitting the coordinate points corresponding to all sampling moments yields the third curve. For example, the preset true strain interval is [0.05%, 0.25%]. This means determining the curve segment with the horizontal coordinates [0.05%, 0.25%]. The linear least squares method is then used to determine the slope of the regression line for this curve segment, which serves as the Young's modulus E.

[0091] Then, a straight line is drawn with a slope equal to the Young's modulus E and passing through a preset coordinate point, wherein the preset coordinate point corresponds to a preset true strain of 0.2% and a preset true stress of 0.

[0092] like Figure 2 As shown in Figure 2, the intersection of the third curve and the straight line is taken as the yield point. At this point, the true strain and true stress corresponding to the yield point can be clearly determined.

[0093] It should be noted that the above-mentioned values ​​of the preset true strain range and the preset coordinate points are only for illustrative purposes and do not constitute a limitation on the embodiments of the present application.

[0094] Step S30, determining a second sampling time corresponding to the necking point;

[0095] In this embodiment, the coordinate point of the necking point is determined in the corresponding coordinate system, and then the sampling moment closest to the coordinate point is determined to serve as the second sampling moment corresponding to the necking point.

[0096] Furthermore, in one embodiment, before step S30, the method further includes:

[0097] The true strain corresponding to each sampling moment in the first test data set is converted into plastic strain to obtain a second test data set; the true stress corresponding to each sampling moment in the second test data set is multiplied by the corresponding proportional coefficient to obtain a third test data set, wherein the proportional coefficient corresponding to the true stress corresponding to a sampling moment is determined based on the plastic Poisson's ratio corresponding to the plastic strain corresponding to the sampling moment; a fourth curve is determined based on the second test data set, and the fourth curve is used to characterize the relationship between the true stress and the plastic strain; a derivative curve corresponding to the fourth curve is determined; a fifth curve is determined based on the third test data set; and the intersection of the derivative curve and the fifth curve is used as the necking point.

[0098] In this embodiment, the true strain ε ture Converted to plastic strain ε p The formula is as follows:

[0099]

[0100] The plastic strain ε corresponding to each sampling moment p The corresponding plastic Poisson's ratio v p for:

[0101]

[0102] Among them, v e is the elastic Poisson's ratio of the sample, which is a constant and can be obtained by consulting the material manual or performing standard test calculations; A1, A2, B1, B2, C1, and C2 are fitting parameters; and e is a natural constant.

[0103] Optional, the proportionality factor 2v corresponding to the true stress at a sampling moment p .

[0104] Furthermore, the horizontal coordinate of the data point of the fourth curve is kept unchanged, and the vertical coordinate is calculated by dividing the difference between the vertical coordinate of the next adjacent data point and the point by the difference between the horizontal coordinate of the next adjacent data point and the point.

[0105] It can be seen that the derivative curve and the fifth curve can be drawn in the true stress-plastic strain coordinate system. Figure 3 , Figure 3 Schematic diagram of the scene for determining the necking point. Figure 3 As shown, the abscissa of the determined necking point is a plastic strain, and the plastic strain corresponds to the true strain, that is, the sampling moment closest to the true strain can be used as the second sampling moment corresponding to the necking point.

[0106] Step S40: extracting a first sub-test data set corresponding to a first sampling period from the first test data set, where the start time of the first sampling period is the first sampling time and the end time is the second sampling time;

[0107] Step S50, determining a first curve based on the first sub-test data set, where the first curve is used to represent the relationship between true stress and plastic strain;

[0108] In this embodiment, a first sub-test data set at the sampling moment within the first sampling period is extracted from the first test data set, and then the true strain at each sampling moment in the first sub-test data set is converted into plastic strain to obtain a new first sub-test data set, thereby drawing a first curve for characterizing the relationship between true stress and plastic strain in the true stress-plastic strain coordinate system.

[0109] Furthermore, in one embodiment, step S50 includes:

[0110] Convert the true strain corresponding to each sampling moment in the first sub-test data set into plastic strain to obtain a new first sub-test data set;

[0111] A first curve is obtained based on the new first sub-experimental data set.

[0112] In this embodiment, based on the above true strain ε ture Converted to plastic strain ε p The formula converts the true strain corresponding to each sampling moment in the first sub-test data set into plastic strain.

[0113] Step S60: extracting a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment;

[0114] Step S70, determining a second curve based on the second sub-test data set, where the second curve is used to represent the relationship between true stress and plastic strain;

[0115] In this embodiment, the sample is a modified thermoplastic material, which is a ductile polymer. Ductile behavior and softening behavior will occur after the necking point. It is necessary to simulate the two behaviors based on the second sub-test data set and determine the second curve based on the simulation results.

[0116] Furthermore, in one embodiment, step S70 includes:

[0117] Step S701: updating the true stress corresponding to the later sampling moment based on the true stress corresponding to the earlier sampling moment in the second sub-test data set, and converting the true strain corresponding to each sampling moment in the second sub-test data set into plastic strain, thereby obtaining a new second sub-test data set;

[0118] In this embodiment, the true stress corresponding to the subsequent sampling time is updated as follows:

[0119]

[0120] Among them, σ ture，n+1 is the new true stress at the n+1th sampling moment, σ ture，n is the true stress corresponding to the nth sampling moment, v n+1 is the Poisson's ratio corresponding to the n+1th sampling moment, v n is the Poisson's ratio corresponding to the nth sampling moment, ε ture，n+1 is the true strain corresponding to the n+1th sampling moment, ε ture，n is the true strain corresponding to the nth sampling moment.

[0121] Among them, the Poisson's ratio v corresponding to the nth sampling moment is n The technical formula is as follows:

[0122]

[0123] ε eng，X，n is the strain of the gauge length section along the length direction of the sample corresponding to the nth sampling moment, ε eng，Y，n is the strain along the width direction of the sample corresponding to the nth sampling moment.

[0124] Based on the true strain ε ture Converted to plastic strain ε p The formula can be used to convert the true strain corresponding to each sampling moment in the second sub-test data set into plastic strain.

[0125] Assume that the true stress-true strain in the second sub-test data set arranged in the order of sampling time are:

[0126] σ ture1 -ε ture1 , σ ture2 -ε ture2 , σ ture3 -ε ture3 .

[0127] After processing according to the above instructions, the new second sub-test data set is obtained:

[0128] σ ture1 -ε p1 、New σ ture2 -ε p2 、New σ ture3 -ε p3 .

[0129] Step S702: For the new second sub-test data set, perform weighted summation of the true stress corresponding to each sampling moment and the true stress corresponding to the necking point in the new second sub-test data set to obtain a third sub-test data set;

[0130] In this example, the new second sub-experimental dataset characterizes the ductile behavior that occurs after the necking point. The softening behavior of ductile polymers can persist for a considerable period of time. To eliminate the numerical instability of the material caused by the softening behavior, it is assumed that the true stress of the material remains unchanged during the softening stage. That is, the true stress after the necking point is always the true stress corresponding to the necking point.

[0131] Reference Figure 4 , Figure 4 Schematic diagram of the ductile behavior characterization curve and the softening behavior characterization curve. Figure 4 As shown in Figure 1, the ductile behavior characterization curve is fitted based on the new second sub-test data set; assuming that the true stress of the material remains unchanged during the softening stage, the softening behavior characterization curve is a horizontal line passing through the true stress corresponding to the necking point.

[0132] like Figure 4 It can be understood that for the same horizontal coordinate (denoted as X1), there are two corresponding vertical coordinates: the vertical coordinate on the ductility behavior curve (denoted as Y1) and the vertical coordinate on the softening behavior curve (denoted as Y2). Y1 and Y2 are weighted summed to obtain Y3, which is used as the vertical coordinate corresponding to X1. Similarly, the third sub-test data set can be obtained.

[0133] Among them, the initial weights are 0.2 and 0.8 respectively, that is, Y3=0.2Y1+0.8Y2,

[0134] The weights are then adjusted appropriately based on the comparison of the simulated load-displacement curve with the experimental load-displacement curve. For example, after the necking point, if the simulated load-displacement curve is below the experimental load-displacement curve, the weight of Y1 is increased and the weight of Y2 is decreased. Conversely, if the simulated load-displacement curve is above the experimental load-displacement curve, the weight of Y1 is decreased and the weight of Y2 is increased (the sum of the two weights is always 1). This is done until the simulated load-displacement curve and the experimental load-displacement curve show similar trends.

[0135] Step S703: obtaining a second curve based on the third sub-test data set.

[0136] In this embodiment, the second curve can be obtained by fitting based on the third sub-test data set.

[0137] Step S80, splicing the first curve and the second curve to obtain a spliced ​​curve;

[0138] In this embodiment, the first curve is used to characterize the mechanical characteristics of the sample before the necking point, and the second curve is used to characterize the mechanical characteristics of the sample after the necking point. By splicing the first curve and the second curve, a spliced ​​curve used to characterize the mechanical characteristics of the sample can be obtained.

[0139] In step S90, the curve segments corresponding to the failure stage of the sample are deleted from the spliced ​​curve, and the remaining curve segments are used as the constitutive curves of the sample under the preset test.

[0140] In this embodiment, the spliced ​​curve is used to reflect the change of true stress with plastic strain. When the rate of change of true stress is large until it returns to zero, it is the failure stage of the sample. The curve segment corresponding to the failure stage of the sample is deleted from the spliced ​​curve, and the remaining curve segment is used as the constitutive curve of the sample under the preset test.

[0141] During a pre-set test, the sample can be tested for cracks, with the moment of crack appearance being used as the failure start time, and the period after the failure start time being defined as the failure stage. The failure start time can be input by a user, or it can be determined by image detection technology to identify the moment of crack appearance.

[0142] Through the embodiments of the present application, a constitutive curve is constructed based on experimental data, so that the constructed constitutive curve can more accurately characterize the mechanical characteristics of the material.

[0143] Furthermore, in one embodiment, after step S90, the method further includes:

[0144] Acquire a simulation data set obtained by simulating a sample, the simulation data set including the displacement at the sample's stress point and the external load at the sample's stress point corresponding to each simulation moment during the simulation process, wherein the simulation and the preset test correspond to the same test conditions; delete the displacement at the sample's stress point and the external load at the sample's stress point corresponding to the target simulation moment corresponding to the failure stage of the sample in the simulation data set to obtain a new simulation data set; determine the true stress and plastic strain corresponding to each simulation moment in the new simulation data set as labels based on the constitutive curve; train an extreme learning machine based on the new simulation data set and the labels to obtain a trained extreme learning machine;

[0145] In this embodiment, the new simulation data set and label are represented as vectors I m , O m (m=1:n, n is the number of sampling points), that is, I m =[ I F m I L m ] T , O m =[ O ε m O σ m ] T , will I m , O mAs a set of inputs and outputs of the extreme learning machine, the number of input layers and output layers is 2 (m=2). The total input I and output O of the extreme learning machine are:

[0146]

[0147]

[0148] Initialize the hidden layer weight α and bias matrix b: Set the number of hidden layer neurons L (0.1n≤L≤n), and use the normal distribution function to randomly generate the initial connection weight matrix α of the input layer and hidden layer and the hidden layer neuron bias matrix b, as shown below:

[0149]

[0150] Set the activation function: To speed up the convergence, use the relu activation function. Let the activation function be f(x). Then, from the extreme learning machine structure diagram, the curve coordinate points of the network output can be obtained as follows:

[0151]

[0152] Let the solution be H(I m )β, where m=1:n, α j =[α j1 α j2 α j3 ], j=1:L.

[0153] Solve the output layer weight matrix β: In order to obtain the hidden layer and output layer connection weight matrix β with good effect on the data set, it is necessary to ensure that the training error is minimized, that is, minH(I m )β-O 2 , the optimal solution of this formula is β * =H + (I m )O, where H + is the Moore-Penrose generalized inverse matrix of H.

[0154] Training model: Connect the optimal hidden layer and output layer to the weight matrix β input model, using vector I m , O m The extreme learning machine is made to learn and continuously train the initial connection weight matrix α of the hidden layer and the bias matrix b of the hidden layer neurons.

[0155] Establishing a mapping deviation feedback function e: In order to evaluate the correction effect of the extreme learning machine on the constitutive curve, it is necessary to establish a mapping deviation feedback function e. Use different sampling points under the same test data set for post-processing to obtain the true stress-plastic strain curve, and then output the load-displacement curve through simulation. This data set is used as the input of the extreme learning machine. The predicted true stress-plastic strain curve data set can be obtained through network calculation, which is recorded as P X:

[0156]

[0157] The true stress-plastic strain curve data set obtained by post-processing is denoted as X O , then the prediction error vector E is:

[0158]

[0159] The prediction deviation function is represented by the Euclidean distance of the prediction deviation vector, that is, the mapping deviation feedback function e is:

[0160]

[0161] Optimize the network model: The smaller the e value, the better the prediction accuracy of the extreme learning machine algorithm and the better the model training effect. By continuously adjusting the value of the number of hidden layer neurons L and comparing the e value of the network model after training, the optimal neural network parameters can be screened out.

[0162] A second test data set is obtained from a preset test conducted on the sample, wherein the second test data set includes the displacement at the stress point of the sample corresponding to each sampling moment in the preset test process and the external load at the stress point of the sample; the displacement at the stress point of the sample corresponding to the target sampling moment corresponding to the failure stage of the sample in the second test data set and the external load at the stress point of the sample are deleted to obtain a new second test data set; the new second test data set is input into the trained extreme learning machine; and a revised constitutive curve is constructed based on the output of the trained extreme learning machine.

[0163] In this embodiment, the load-displacement curve data set obtained from the experiment (i.e., a second test data set obtained from a preset test on the sample, the second test data set including the displacement at the force point of the sample corresponding to each sampling moment during the preset test and the external load at the force point of the sample) is input into the trained extreme learning machine to obtain a corrected constitutive curve.

[0164] In a second aspect, an embodiment of the present application also provides a constitutive curve construction device.

[0165] In one embodiment, referring to Figure 5 , Figure 5This is a functional module diagram of an embodiment of the constitutive curve construction device of this application. Figure 5 As shown, the constitutive curve construction device includes:

[0166] An acquisition module 10 is configured to acquire a first test data set obtained from a preset test performed on a sample, wherein the first test data set includes a true stress and a true strain corresponding to each sampling moment during the preset test process;

[0167] A first determining module 20, configured to determine a first sampling moment corresponding to a yield point;

[0168] The first determining module 20 is further configured to determine a second sampling time corresponding to the necking point;

[0169] An extraction module 30 is configured to extract a first sub-test data set corresponding to a first sampling period from the first test data set, where the start time of the first sampling period is the first sampling time and the end time is the second sampling time;

[0170] a second determining module 40, configured to determine a first curve based on the first sub-test data set, wherein the first curve is configured to represent a relationship between true stress and plastic strain;

[0171] The extraction module 30 is further configured to extract a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment;

[0172] The second determining module 40 is further configured to determine a second curve based on the second sub-test data set, where the second curve is configured to represent the relationship between the true stress and the plastic strain;

[0173] A splicing processing module 50 is used to splice the first curve and the second curve to obtain a spliced ​​curve;

[0174] The deletion module 60 is used to delete the curve segment corresponding to the failure stage of the sample from the splicing curve, and use the remaining curve segment as the constitutive curve of the sample under the preset test.

[0175] Furthermore, in one embodiment, the first determining module 20 is further configured to:

[0176] determining a third curve based on the first test data set, where the third curve is used to represent the relationship between true stress and true strain;

[0177] Determine a curve segment corresponding to a preset true strain interval on the third curve;

[0178] The slope of the regression line corresponding to the curve segment is determined based on the linear least squares method and used as the Young's modulus;

[0179] Draw a straight line having a slope of Young's modulus and passing through a preset coordinate point, wherein the preset coordinate point corresponds to a preset true strain and a preset true stress;

[0180] The intersection of the third curve and the straight line is taken as the yield point.

[0181] Furthermore, in one embodiment, the first determining module 20 is further configured to:

[0182] Convert the true strain corresponding to each sampling moment in the first test data set into the plastic strain to obtain the second test data set;

[0183] The third test data set is obtained by multiplying the true stress corresponding to each sampling moment in the second test data set by the corresponding proportional coefficient, wherein the proportional coefficient corresponding to the true stress corresponding to a sampling moment is determined based on the plastic Poisson's ratio corresponding to the plastic strain corresponding to the sampling moment;

[0184] determining a fourth curve based on the second test data set, where the fourth curve is used to represent the relationship between true stress and plastic strain;

[0185] determining a derivative curve corresponding to the fourth curve;

[0186] determining a fifth curve based on the third experimental data set;

[0187] The intersection of the derivative curve and the fifth curve is taken as the necking point.

[0188] Furthermore, in one embodiment, the second determining module 40 is configured to:

[0189] Convert the true strain corresponding to each sampling moment in the first sub-test data set into plastic strain to obtain a new first sub-test data set;

[0190] A first curve is obtained based on the new first sub-experimental data set.

[0191] Furthermore, in one embodiment, the second determining module 40 is configured to:

[0192] Based on the true stress corresponding to the earlier sampling moment in the second sub-test data set, the true stress corresponding to the later sampling moment is updated, and the true strain corresponding to each sampling moment in the second sub-test data set is converted into plastic strain to obtain a new second sub-test data set;

[0193] For the new second sub-test data set, the true stress corresponding to each sampling moment in the new second sub-test data set and the true stress corresponding to the necking point are weightedly summed to obtain the third sub-test data set;

[0194] A second curve is obtained based on the third sub-experimental data set.

[0195] Furthermore, in one embodiment, the constitutive curve construction device further includes a correction module for:

[0196] Acquire a simulation data set obtained by simulating the sample, wherein the simulation data set includes the displacement at the force-bearing point of the sample corresponding to each simulation moment during the simulation process and the external load at the force-bearing point of the sample, wherein the simulation and the preset test correspond to the same test conditions;

[0197] The displacement at the stress point of the sample corresponding to the target simulation time corresponding to the failure stage of the sample in the simulation data set and the external load at the stress point of the sample are deleted to obtain a new simulation data set;

[0198] Determine the true stress and plastic strain corresponding to each simulation moment in the new simulation data set based on the constitutive curve as labels;

[0199] Training an extreme learning machine based on the new simulation data set and the labels to obtain a trained extreme learning machine;

[0200] Obtaining a second test data set obtained from a preset test performed on the sample, the second test data set including the displacement at the force-bearing point of the sample and the applied load at the force-bearing point of the sample corresponding to each sampling moment during the preset test;

[0201] The displacement at the stress point of the sample corresponding to the target sampling time corresponding to the failure stage of the sample and the external load at the stress point of the sample are deleted in the second test data set to obtain a new second test data set;

[0202] Input the new second test data set into the trained extreme learning machine;

[0203] The modified constitutive curve is constructed based on the output of the trained extreme learning machine.

[0204] Furthermore, in one embodiment, the constitutive curve construction device further includes a failure stage determination module, which is used to:

[0205] Receiving an expiration start time based on user operation input;

[0206] Determine the failure stage of the sample based on the failure initiation time.

[0207] Among them, the functional implementation of each module in the above-mentioned constitutive curve construction device corresponds to the various steps in the above-mentioned constitutive curve construction method embodiment, and their functions and implementation processes are no longer repeated here.

[0208] In a third aspect, an embodiment of the present application provides a constitutive curve construction device, which may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0209] Reference Figure 6 , Figure 6 Schematic diagram of the hardware structure of the constitutive curve construction device involved in the embodiment of the present application. In the embodiment of the present application, the constitutive curve construction device may include a processor, a memory, a communication interface and a communication bus.

[0210] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0211] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces, which are used to interconnect components within the constitutive curve construction device, as well as interfaces used to interconnect the constitutive curve construction device with other devices (such as other computing devices or user devices). Physical interfaces can be Ethernet, fiber, or ATM interfaces; user devices can be displays or keyboards.

[0212] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0213] The processor may be a general-purpose processor, which may call a constitutive curve construction program stored in a memory and execute the constitutive curve construction method provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the constitutive curve construction program is called may refer to the various embodiments of the constitutive curve construction method of the present application, and will not be repeated here.

[0214] Those skilled in the art will understand that Figure 6 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0215] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0216] The computer-readable storage medium of the present application stores a constitutive curve construction program, wherein when the constitutive curve construction program is executed by a processor, the steps of the constitutive curve construction method as described above are implemented.

[0217] Among them, the method implemented when the constitutive curve construction program is executed can refer to the various embodiments of the constitutive curve construction method of the present application, and will not be repeated here.

[0218] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0219] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0220] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0221] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0222] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0223] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0224] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of this application, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A constitutive curve construction method, characterized in that: The constitutive curve construction method includes: Acquire a first test data set obtained from a preset test performed on the sample, wherein the first test data set includes a true stress and a true strain corresponding to each sampling moment during the preset test process; Determine the first sampling moment corresponding to the yield point; Determine the second sampling moment corresponding to the necking point; Extracting a first sub-test data set corresponding to a first sampling period from the first test data set, where the start time of the first sampling period is a first sampling time and the end time is a second sampling time; determining a first curve based on the first sub-test data set, where the first curve is used to represent the relationship between true stress and plastic strain; Extracting a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment; determining a second curve based on the second sub-test data set, where the second curve is used to represent the relationship between the true stress and the plastic strain; splicing the first curve and the second curve to obtain a spliced ​​curve; The curve segments corresponding to the failure stage of the sample are deleted from the splicing curve, and the remaining curve segments are used as the constitutive curves of the sample under the preset test.

2. The constitutive curve construction method according to claim 1, wherein: Before the step of determining the first sampling moment corresponding to the yield point, the method further includes: determining a third curve based on the first test data set, where the third curve is used to represent the relationship between true stress and true strain; Determine a curve segment corresponding to a preset true strain interval on the third curve; The slope of the regression line corresponding to the curve segment is determined based on the linear least squares method and used as the Young's modulus; Draw a straight line having a slope of Young's modulus and passing through a preset coordinate point, wherein the preset coordinate point corresponds to a preset true strain and a preset true stress; The intersection of the third curve and the straight line is taken as the yield point.

3. The constitutive curve construction method according to claim 1, wherein: Before the step of determining the second sampling moment corresponding to the necking point, the method further includes: Convert the true strain corresponding to each sampling moment in the first test data set into the plastic strain to obtain the second test data set; The third test data set is obtained by multiplying the true stress corresponding to each sampling moment in the second test data set by the corresponding proportional coefficient, wherein the proportional coefficient corresponding to the true stress corresponding to a sampling moment is determined based on the plastic Poisson's ratio corresponding to the plastic strain corresponding to the sampling moment; determining a fourth curve based on the second test data set, where the fourth curve is used to represent the relationship between true stress and plastic strain; determining a derivative curve corresponding to the fourth curve; determining a fifth curve based on the third experimental data set; The intersection of the derivative curve and the fifth curve is taken as the necking point.

4. The constitutive curve construction method according to claim 1, wherein: The step of determining the first curve based on the first sub-test data set includes: Convert the true strain corresponding to each sampling moment in the first sub-test data set into plastic strain to obtain a new first sub-test data set; A first curve is obtained based on the new first sub-experimental data set.

5. The constitutive curve construction method according to claim 4, characterized in that: The step of determining the second curve based on the second sub-test data set includes: Based on the true stress corresponding to the earlier sampling moment in the second sub-test data set, the true stress corresponding to the later sampling moment is updated, and the true strain corresponding to each sampling moment in the second sub-test data set is converted into plastic strain to obtain a new second sub-test data set; For the new second sub-test data set, the true stress corresponding to each sampling moment in the new second sub-test data set and the true stress corresponding to the necking point are weightedly summed to obtain the third sub-test data set; A second curve is obtained based on the third sub-experimental data set.

6. The constitutive curve construction method according to claim 5, characterized in that: After the step of deleting the curve segments corresponding to the failure stage of the sample from the splicing curve and using the remaining curve segments as the constitutive curve of the sample under the preset test, the method further includes: Acquire a simulation data set obtained by simulating the sample, wherein the simulation data set includes the displacement at the force-bearing point of the sample corresponding to each simulation moment during the simulation process and the external load at the force-bearing point of the sample, wherein the simulation and the preset test correspond to the same test conditions; The displacement at the stress point of the sample corresponding to the target simulation time corresponding to the failure stage of the sample in the simulation data set and the external load at the stress point of the sample are deleted to obtain a new simulation data set; Determine the true stress and plastic strain corresponding to each simulation moment in the new simulation data set based on the constitutive curve as labels; Training an extreme learning machine based on the new simulation data set and the labels to obtain a trained extreme learning machine; Obtaining a second test data set obtained from a preset test performed on the sample, the second test data set including the displacement at the force-bearing point of the sample and the applied load at the force-bearing point of the sample corresponding to each sampling moment during the preset test; The displacement at the stress point of the sample corresponding to the target sampling time corresponding to the failure stage of the sample and the external load at the stress point of the sample are deleted in the second test data set to obtain a new second test data set; Input the new second test data set into the trained extreme learning machine; The modified constitutive curve is constructed based on the output of the trained extreme learning machine.

7. The constitutive curve construction method according to any one of claims 1 to 6, characterized in that: The constitutive curve construction method further includes: Receiving an expiration start time based on user operation input; Determine the failure stage of the sample based on the failure initiation time.

8. A constitutive curve construction device, characterized in that: The constitutive curve construction device comprises: an acquisition module, configured to acquire a first test data set obtained from a preset test performed on a sample, wherein the first test data set includes a true stress and a true strain corresponding to each sampling moment during the preset test process; A first determining module, configured to determine a first sampling moment corresponding to a yield point; The first determining module is further used to determine a second sampling time corresponding to the necking point; an extraction module, configured to extract a first sub-test data set corresponding to a first sampling period from the first test data set, wherein the start time of the first sampling period is the first sampling time and the end time is the second sampling time; a second determining module, configured to determine a first curve based on the first sub-test data set, wherein the first curve is used to represent a relationship between true stress and plastic strain; The extraction module is further configured to extract a second sub-test data set corresponding to a second sampling period from the first test data set, where the second sampling period is a test period after the second sampling moment; The second determination module is further used to determine a second curve based on the second sub-test data set, where the second curve is used to represent the relationship between the true stress and the plastic strain; A splicing processing module, configured to splice the first curve and the second curve to obtain a spliced ​​curve; The deletion module is used to delete the curve segments corresponding to the failure stage of the sample from the splicing curve, and use the remaining curve segments as the constitutive curve of the sample under the preset test.

9. A constitutive curve construction device, characterized in that: The constitutive curve construction device includes a processor, a memory, and a constitutive curve construction program stored in the memory and executable by the processor, wherein when the constitutive curve construction program is executed by the processor, the steps of the constitutive curve construction method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a constitutive curve construction program, wherein when the constitutive curve construction program is executed by a processor, the steps of the constitutive curve construction method according to any one of claims 1 to 7 are implemented.

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