Computational device, prediction method, and program for predicting the hysteresis properties of composite materials

Abstract

To improve the prediction technology for hysteresis properties related to composite materials. [Solution] A computing device comprising a control unit for predicting the hysteresis properties of a composite material containing a polymer and a filler, wherein the control unit acquires the mechanical properties of the filler aggregates and the correspondence between the mechanical properties of the filler aggregates and the hysteresis properties of the filler aggregates, acquires the mechanical properties of the composite material using the acquired mechanical properties of the filler aggregates, and predicts the hysteresis properties of the composite material based on the correspondence and the mechanical properties of the composite material.

Description

Technical Field

[0001] The present disclosure relates to a computing device, a prediction method, and a program for predicting the history characteristics of composite materials such as rubber.

Background Art

[0002] When calculating history-dependent physical properties such as hysteresis and viscoelasticity (hereinafter also referred to as history characteristics), it is necessary to obtain the corresponding agglomerate physical properties and apply them to the entire system for calculation (for example, Non-Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even in the full-system model, it is necessary to perform a long-time simulation according to the history due to the history effect, and the calculation load is large. In Non-Patent Document 1, it is an example of simulating the Mullins effect dealing with a large-scale filler dispersion structure, but the calculation cost is large and the supercomputer "K" was used. That is, there was room for improvement in the prediction technology for the history characteristics of composite materials.

[0005] In view of such circumstances, an object of the present disclosure is to improve the prediction technology for the history characteristics of composite materials.

Means for Solving the Problems

[0006] (1) The computing device according to an embodiment of the present disclosure is <00%00037>A computing device comprising a control unit for predicting the hysteresis properties of a composite material including a polymer and a filler, wherein the control unit is The relationship between the mechanical properties of the filler aggregates and the hysteresis properties of the filler aggregates is obtained. The mechanical properties of the composite material are obtained by utilizing the mechanical properties of the acquired filler aggregates. Based on the aforementioned correspondence and the mechanical properties of the composite material, the hysteresis properties of the composite material are predicted.

[0007] (2) A computing device according to one embodiment of the present disclosure, the computing device described in (1), The mechanical properties of the filler aggregates and their corresponding relationships are obtained based on a first simulation model that uses molecular dynamics theory.

[0008] (3) A computing device according to one embodiment of the present disclosure is the computing device described in (1) or (2), The aforementioned correspondence is the relationship between the mechanical properties input to the filler aggregate and the hysteresis properties of the filler aggregate.

[0009] (4) A computing device according to one embodiment of the present disclosure is a computing device according to any one of (1) to (3), The mechanical properties of the aforementioned composite material are obtained based on a second simulation model that is based on continuum theory.

[0010] (5) A computing device according to one embodiment of the present disclosure is a computing device according to any one of (1) to (4), The filler aggregate comprises the filler and the polymer surrounding the filler.

[0011] (6) A computing device according to one embodiment of the present disclosure, the computing device described in (2), The element that takes the mechanical properties of the filler aggregate as input properties is set based on the positional information of the filler in the composite material and the volume fraction of the filler in the filler aggregate set in the first simulation model.

[0012] (7) A computing device according to one embodiment of the present disclosure is a computing device according to any one of (1) to (6), A computing device that determines the mechanical properties of the filler aggregate as stress-strain relationship, viscoelastic properties, damage fracture properties, or thermal conductivity properties.

[0013] (8) A computing device according to one embodiment of the present disclosure is a computing device according to any one of (1) to (7), The hysteresis characteristic of the filler aggregate is the hysteresis loss value of the filler aggregate. A computing device in which the hysteresis characteristics of the composite material are the hysteresis loss value of the composite material.

[0014] (9) A computing device according to one embodiment of the present disclosure, the computing device described in (2), The mechanical properties of the filler aggregate are determined based on an approximate curve fitted within a predetermined strain range from the stress-strain relationship of the filler aggregate obtained based on the first simulation model.

[0015] (10) A computing device according to one embodiment of the present disclosure is the computing device described in (2), wherein the first simulation model is a model based on coarse-grained molecular dynamics simulation or whole-atom simulation.

[0016] (11) A computing device according to one embodiment of the present disclosure, the computing device described in (4), The second simulation model is a model based on the finite element method, particle method, or phase-field method.

[0017] (12) A computing device according to one embodiment of the present disclosure is a computing device according to any one of (1) to (11), The hysteresis characteristics of the filler aggregate are determined based on the area ratio within the positive stress range.

[0018] (13) The prediction method according to an embodiment of the present disclosure is a prediction method executed by a computing device for predicting the historical characteristics of a composite material including a polymer and a filler, comprising: obtaining the mechanical properties of the filler agglomerate and the corresponding relationship related to the historical characteristics of the filler agglomerate; obtaining the mechanical properties of the composite material based on the filler arrangement by using the obtained mechanical properties of the filler agglomerate; predicting the historical characteristics of the composite material based on the corresponding relationship and the mechanical properties of the composite material; and the like.

[0019] (14 The program according to an embodiment of the present disclosure is a program for predicting the historical characteristics of a composite material including a polymer and a filler, which causes a computer to obtain the mechanical properties of the filler agglomerate and the corresponding relationship related to the historical characteristics of the filler agglomerate; obtain the mechanical properties of the composite material based on the filler arrangement by using the obtained mechanical properties of the filler agglomerate; predict the historical characteristics of the composite material based on the corresponding relationship and the mechanical properties of the composite material; and execute the above.

Advantages of the Invention

[0020] According to an embodiment of the present disclosure, the prediction technology for the historical characteristics of composite materials can be improved.

Brief Description of the Drawings

[0021] [Figure 1] It is a block diagram showing a schematic configuration of a computing device according to an embodiment of the present disclosure. [Figure 2] It is a flowchart showing the operation of a computing device according to an embodiment of the present disclosure. [Figure 3] It is a diagram showing a snapshot of the molecular behavior of a filler agglomerate. [Figure 4] It is a graph showing the stress-strain relationship. [Figure 5]This is a graph showing the hysteresis loss value. [Figure 6] This is a schematic diagram showing the location information of the filler. [Figure 7] This graph shows the results of calculating the hysteresis loss value. [Figure 8] This graph shows the stress-strain relationship related to the modified form. [Figure 9] This graph shows the hysteresis loss values ​​related to the modified form. [Figure 10] This graph shows the stress-strain relationship related to the modified form. [Figure 11] This graph shows the hysteresis loss values ​​related to the modified form. [Modes for carrying out the invention]

[0022] Hereinafter, a materials calculation device 10 according to an embodiment of this disclosure will be described with reference to the drawings. In each figure, the same or corresponding parts are denoted by the same reference numerals. In the description of this embodiment, the description of the same or corresponding parts will be omitted or simplified as appropriate.

[0023] Referring to Figure 1, the overview and configuration of the computing device 10 according to this embodiment will be described.

[0024] The computing device 10 is any computing device used by the user. For example, the computing device 10 includes industrial measuring instruments, personal computers, server computers, general-purpose electronic devices, or dedicated electronic devices.

[0025] First, an overview of this embodiment will be described, and details will be described later. The computing device 10 of this embodiment predicts the hysteresis properties of a composite material containing a polymer and fillers. First, the computing device 10 acquires the relationship between the mechanical properties of the filler aggregates and the hysteresis properties of the filler aggregates using a first simulation model based on molecular dynamics theory. The computing device 10 then uses the acquired mechanical properties of the filler aggregates to acquire the mechanical properties of the composite material using a second simulation model based on continuum theory. Finally, the computing device 10 predicts the hysteresis properties of the composite material based on the relationship and the mechanical properties of the composite material.

[0026] Thus, according to this embodiment, the prediction technology for the hysteresis properties of composite materials can be improved by reducing the computational load and predicting the hysteresis properties of the composite material by utilizing the correspondence between the mechanical properties of the filler aggregates and the hysteresis properties of the filler aggregates.

[0027] Here, filler aggregates are aggregates defined by the filler and its surrounding region (hereinafter also referred to as the filler aggregate region), which are assumed to be based on the dispersion structure of the filler obtained from measurements such as analysis using an electron microscope on the composite material. In other words, filler aggregates are composed of fillers and polymers within the filler aggregate region of the composite material.

[0028] In this embodiment, the hysteresis characteristics to be predicted include the hysteresis loss value of the composite material. In this embodiment, the hysteresis characteristics to be predicted will be described as the hysteresis loss value, but the prediction target of this disclosure is not limited to this, and any hysteresis characteristics may be the prediction target.

[0029] Next, we will describe in detail each component of the computing device 10.

[0030] (Configuration of the computing device 10) As shown in Figure 1, the computing device 10 comprises a control unit 11, a storage unit 12, an input unit 13, and an output unit 14.

[0031] The control unit 11 includes at least one processor, at least one dedicated circuit, or a combination thereof. The processor is a general-purpose processor such as a CPU (central processing unit) or GPU (graphics processing unit), or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA (field-programmable gate array) or an ASIC (application-specific integrated circuit). The control unit 11 controls each part of the computing device 10 and executes processes related to the operation of the computing device 10.

[0032] The storage unit 12 includes at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or at least two combinations thereof. The semiconductor memory is, for example, RAM (random access memory) or ROM (read-only memory). The RAM is, for example, SRAM (static random access memory) or DRAM (dynamic random access memory). The ROM is, for example, EEPROM (electrically erasable programmable read-only memory). The storage unit 12 functions, for example, as a main memory, auxiliary memory, or cache memory. The storage unit 12 stores data used for the operation of the computing device 10 and data obtained by the operation of the computing device 10.

[0033] The input unit 13 includes at least one input interface. The input interface may be, for example, a physical key, a capacitive key, a pointing device, or a touchscreen integrated with a display. Alternatively, the input interface may be, for example, a microphone that accepts voice input or a camera that accepts gesture input. The input unit 13 accepts operations to input data used for the operation of the computing device 10. Instead of being provided in the computing device 10, the input unit 13 may be connected to the computing device 10 as an external input device. Any connection method can be used, for example, USB (Universal Serial Bus), HDMI (registered trademark) (High-Definition Multimedia Interface), or Bluetooth (registered trademark).

[0034] The output unit 14 includes at least one output interface. The output interface is, for example, a speaker that outputs information as sound. The output unit 14 outputs data obtained by the operation of the computing device 10. Instead of being provided in the computing device 10, the output unit 14 may be connected to the computing device 10 as an external output device. Any connection method can be used, for example, USB, HDMI®, or Bluetooth®.

[0035] The functions of the computing device 10 are realized by executing the program according to this embodiment on a processor corresponding to the computing device 10. In other words, the functions of the computing device 10 are realized by software. The program causes the computer to perform the operations of the computing device 10, thereby causing the computer to function as the computing device 10. That is, the computer functions as the computing device 10 by performing the operations of the computing device 10 according to the program.

[0036] In this embodiment, the program can be recorded on a computer-readable recording medium. The computer-readable recording medium includes non-temporary computer-readable media, such as magnetic recording devices, optical discs, magneto-optical recording media, or semiconductor memory. The program can be distributed, for example, by selling, transferring, or lending portable recording media such as DVDs (digital versatile discs) or CD-ROMs (compact disc read-only memory) on which the program is recorded. Alternatively, the program may be distributed by storing it on the storage of an external server and transmitting it from the external server to other computers. The program may also be provided as a program product.

[0037] (Operation of the computing device) The operation of the computing device 10 according to this embodiment will be described with reference to Figure 2. Figure 2 is a flowchart showing an example of a method for predicting hysteresis characteristics (in this case, hysteresis loss value) performed by the computing device 10 according to this embodiment.

[0038] Step S100: The control unit 11 of the computing device 10 acquires the correspondence between the mechanical properties of the filler agglutinator and the hysteresis properties of the filler agglutinator based on the first simulation model, etc. Specifically, in this embodiment, the tensile stress curve is acquired as the mechanical properties of the filler agglutinator. The correspondence between the hysteresis properties of the filler agglutinator is the correspondence between the mechanical properties input to the filler agglutinator and the hysteresis properties of the filler agglutinator. Specifically, in this embodiment, the correspondence between the strain energy density and the hysteresis loss value of the filler agglutinator is acquired as the correspondence between the hysteresis properties of the filler agglutinator. Such a correspondence may be a relational expression, a conversion table, etc., showing the relationship between the strain energy density and the hysteresis loss value of the filler agglutinator. The mechanical properties acquired in step S100 are appropriately determined according to the hysteresis properties to be predicted. For example, the mechanical properties of the filler agglutinator may be viscoelastic properties, damage fracture properties, or thermal conductivity properties, etc.

[0039] The first simulation model is, for example, a model based on molecular dynamics theory. For example, the first simulation model is a model based on coarse-grained molecular dynamics simulation or whole-atom simulation. As mentioned above, the filler aggregate includes the filler and the polymer surrounding the filler. The first simulation model does not have to be a model based on molecular dynamics theory. For example, the first simulation model may be a smaller finite element method, particle method, or phase-field method than the second simulation model.

[0040] Step S200: The control unit 11 uses the mechanical properties of the filler aggregates obtained in step S100 to obtain the mechanical properties of the composite material using a second simulation model or the like. Specifically, in this embodiment, the mechanical properties of the composite material to be obtained are the tensile stress curve of the composite material. The mechanical properties of the composite material to be obtained may also be viscoelastic properties, damage fracture properties, or thermal conductivity properties, etc.

[0041] The second simulation model is based on continuum theory. For example, the second simulation model may be based on the finite element method, particle method, or phase-field method. The second simulation model simulates a continuum composed of elements corresponding to filler aggregates and elements corresponding to regions other than the filler aggregates. The elements corresponding to the filler aggregates are set based on the positional information of the fillers in the composite material and the effective volume fraction of the fillers in the filler aggregates set in the first simulation model. Any method can be used for this setting. The mechanical properties of the composite material may be obtained using methods other than the second simulation model.

[0042] Step S300: The control unit 11 predicts the hysteresis properties of the composite material based on the correspondence obtained in step S100 and the mechanical properties of the composite material obtained in step S200. Specifically, in this embodiment, the control unit 11 calculates the strain energy density of each element based on the tensile stress curve of the composite material obtained in step S200. The control unit 11 predicts the hysteresis loss value of the composite material based on the correspondence between the strain energy density obtained in step S100 and the hysteresis loss value of the filler aggregate, and the strain energy density of each element. In other words, the control unit 11 calculates the deformation energy of each phase of the composite material based on the tensile stress curve obtained in step S200. Then, the control unit 11 predicts the hysteresis loss value of the composite material based on the correspondence between the strain energy density obtained in step S100 and the hysteresis loss value of the filler aggregate, and the deformation energy of each phase.

[0043] Step S400: The control unit 11 outputs the prediction results via the output unit 14. Any method can be used for outputting the prediction results. For example, the control unit 11 may output the prediction results via a user interface displayed by the output unit 14.

[0044] As described above, this embodiment improves the prediction technology for the hysteresis properties of composite materials by utilizing the correspondence between the mechanical properties of filler aggregates and the hysteresis properties of filler aggregates, thereby enabling high-precision prediction of the hysteresis properties of composite materials while shortening the calculation time.

[0045] In particular, in this embodiment, the filler aggregate includes the filler and the polymer surrounding the filler. Because the filler and its surroundings are treated as a single integrated element, the second simulation model in this embodiment does not faithfully reproduce the complex structure of the filler, the small gaps between the fillers, and other extremely microscopic structures. This prevents calculation failures in the second simulation that may occur due to the reproduction of such microscopic structures. Furthermore, the filler and its surroundings are treated as a single integrated element, and the mechanical properties of this element are used in the second simulation model. Since the difference in physical properties between this element and the polymer is smaller than the difference in physical properties between the filler and the polymer, calculation failures caused by large differences in physical properties between the filler and the polymer can also be suppressed. In other words, this embodiment improves the prediction technology for hysteresis properties related to composite materials by eliminating calculation constraints caused by the heterogeneous structure and differences in physical properties of composite materials.

[0046] (Examples) The following describes an example in which the hysteresis properties (in this case, hysteresis loss value) of a composite material were predicted using the method described in the above embodiment. In this example, the simulation was performed according to the following procedure. (1) A coarse-grained molecular dynamics simulation model (corresponding to the first simulation model described above) was created for filler aggregates with a predetermined effective volume fraction of filler, and the stress-strain relationship (tensile stress curve) and the correspondence between strain energy density and hysteresis loss value of the filler aggregate were obtained. (2) The tensile stress curve for the filler aggregate obtained above was fitted to a region defined with respect to the measured TEM or SEM image, etc., where the filler region containing the filler was such that the effective volume fraction of the filler was a predetermined proportion. A finite element method model (corresponding to the second simulation model described above) was created by fitting the physical properties of the crosslinked polymer without filler obtained experimentally to the remaining region. (3) Tensile tests were conducted using a finite element method model, and the stress-strain relationship (tensile stress curve) of each element was obtained. (4) Based on the correspondence between the strain energy density obtained in (1) above and the hysteresis loss value of the filler aggregate, and the stress-strain relationship of each element obtained in (3) above, the hysteresis loss value of the composite material was predicted. The following explains each step.

[0047] The procedure in (1) described above corresponds to step S100 described above. The method used in procedure (1) to obtain the mechanical properties of the filler aggregates based on the first simulation model will be explained in detail. Figure 3 shows a snapshot of the molecular behavior of the filler aggregates obtained by numerical calculation using the first simulation model.

[0048] Snapshot 300 shows the filler aggregate in the initial state of the simulation. The filler aggregate contains filler and polymer surrounding the filler. The ratio of filler to polymer regions was set so that the effective volume fraction of the filler was a predetermined ratio. This initial filler aggregate structure can take on various configurations within the defined volume fraction range. This initial configuration may be set to match the actual data.

[0049] Snapshots 310 and 320 show the filler aggregates in their initial state, stretched in the vertical direction of the paper, as a result of performing tensile calculations on the filler aggregates.

[0050] Figure 4 is a graph showing the stress-strain relationship (tensile stress curve) obtained by the first simulation model of this embodiment. Here, calculations for elongation, return to normal, and re-elongation were performed from the same initial structure, varying the maximum strain to 50% (maximum elongation ratio 1.5), 100% (maximum elongation ratio 2.0), 200% (maximum elongation ratio 3.0), etc. The deformation rate was 10 -5The formula was set to / T. Here, if the stress value is negative, the stress value is offset to 0. In other words, the hysteresis properties of the filler agglomerate are determined based on the area ratio within the positive stress range. The stress-strain relationship of the filler agglomerate may be determined by the coefficients of the approximation curve obtained by fitting the simulation result plot. The fitting range can be appropriately set based on the range of the target to be predicted by tensile calculation. In other words, the mechanical properties of the filler agglomerate may be determined based on the approximation curve fitted within a predetermined strain range from the stress-strain relationship of the filler agglomerate obtained based on the first simulation model.

[0051] Figure 5 is a graph showing the hysteresis loss value. In this example, the hysteresis loss value was calculated based on the stress-strain relationship using the following equations (1) and (2).

[0052]

number

[0053] Next, the procedures of (2) and (3) will be described. Procedures of (2) and (3) correspond to step S200 described above. Figure 6 shows a schematic diagram showing the position information of the filler in this embodiment. In this procedure, elements to be treated as filler aggregates are set based on the position information of the filler and the effective volume fraction of the filler aggregate. Specifically, for example, a spherical region with a predetermined radius centered on the position information of the filler (hereinafter also referred to as the predetermined range region) is treated as a filler aggregate. The predetermined radius is defined by the volume fraction of the filler in the filler aggregate. Thus, in this disclosure, a predetermined range region in which the filler and polymer exist is treated as a filler aggregate, centered on the location where the filler exists. In other words, by expanding (thickening) the location where the filler exists, a predetermined range region in which the filler and polymer exist is defined, and such a predetermined range region is treated as a filler aggregate. For elements in regions not treated as filler aggregates, the mechanical properties of the polymer are used as input properties.

[0054] In this way, the mechanical properties of all elements in the second simulation model are determined. By treating a predetermined region as a filler aggregate and considering the mechanical properties of the filler aggregate as input properties for the element, the second simulation model does not need to consider heterogeneous structural differences at the interface between the filler and the polymer, or large differences in physical properties between the filler and the polymer.

[0055] The prediction results are calculated and output according to the procedure in (4) described above. Procedure (4) corresponds to steps S300 and S400 described above. Specifically, the hysteresis loss value of the composite material was calculated using the following formula (3).

[0056]

number

[0057] Figure 7 shows the results of calculating the hysteresis loss value of the composite material from the aforementioned correspondence h(E). In Figure 7, the cases where the filler-to-polymer ratio is 10 phr, 25 phr, 50 phr, and X mil are plotted. The hysteresis loss values ​​for the first and second tensile tests are also plotted for each case. As shown in Figure 7, a correlation is observed between the hysteresis loss value (hysteresis loss value) obtained from experiments and the hysteresis loss value obtained from the calculations in this embodiment, indicating that highly accurate prediction results are obtained. In particular, in this case, the result for the second test is located lower left on the graph than the result for the first test, successfully reproducing the decrease in the hysteresis loss value for the second test. In other words, when the hysteresis characteristics of the filler aggregate are determined based on the area ratio within the positive stress range, the calculation accuracy is high, and the results of the first and second tensile tests can be reproduced more faithfully.

[0058] While this disclosure has been described based on the drawings and embodiments, it should be noted that those skilled in the art will find it easy to make various modifications and alterations based on this disclosure. Therefore, it should be noted that these modifications and alterations are within the scope of this disclosure. For example, the functions, etc., included in each means or each step, etc., can be rearranged in a logically consistent manner, and multiple means or steps, etc., can be combined into one or divided.

[0059] For example, in the embodiment described above, it is also possible to have an embodiment in which the configuration and operation of the computing device 10 are distributed among multiple computers that can communicate with each other.

[0060] For example, in Figures 4 and 5 above, the stress value was offset to 0 when it was negative, but as a modification, the stress value does not need to be corrected. Figures 8 and 9 are graphs showing the stress-strain relationship and hysteresis loss value when the stress value is not corrected. The hysteresis loss value of the composite material may be calculated using the correspondence relationship h(E) obtained from such graphs. Another modification is to offset the minimum stress value to 0. Figures 10 and 11 are graphs showing the stress-strain relationship and hysteresis loss value when the minimum stress value is offset to 0. The hysteresis loss value of the composite material may be calculated using the correspondence relationship h(E) obtained from such graphs.

[0061] [Contribution to the United Nations-led Sustainable Development Goals (SDGs)] The SDGs have been proposed to realize a sustainable society. One embodiment of this invention is considered to be a technology that can contribute to "No. 12: Responsible Consumption and Production" and "No. 13: Climate Action," among others. [Explanation of Symbols]

[0062] 1 computing device 11 Control Unit 12 Storage section 13 Input section 14 Output section 300, 310, 320 snapshots

Claims

1. A computing device comprising a control unit for predicting the hysteresis properties of a composite material including a polymer and a filler, wherein the control unit is The relationship between the mechanical properties of the filler aggregates and the hysteresis properties of the filler aggregates is obtained. The mechanical properties of the composite material are obtained by utilizing the mechanical properties of the acquired filler aggregates. A computing device that predicts the hysteresis properties of a composite material based on the aforementioned correspondence and the mechanical properties of the composite material.

2. A computing device according to claim 1, A computing device for acquiring the mechanical properties of the filler aggregates and the corresponding relationships based on a first simulation model based on molecular dynamics theory.

3. A computing device according to claim 2, The aforementioned correspondence is the correspondence between the mechanical properties input to the filler aggregate and the hysteresis properties of the filler aggregate, according to the computing device.

4. A computing device according to claim 2, The mechanical properties of the composite material are obtained using a computing device based on a second simulation model derived from continuum theory.

5. A computing device according to claim 1, The aforementioned filler aggregate comprises a filler and a polymer surrounding the filler, and is a computing device.

6. A computing device according to claim 2, A computing device in which the elements that take the mechanical properties of the filler aggregate as input properties are set based on the positional information of the filler in the composite material and the volume fraction of the filler in the filler aggregate set in the first simulation model.

7. A computing device according to claim 1, A computing device that determines the mechanical properties of the filler aggregate as stress-strain relationship, viscoelastic properties, damage fracture properties, or thermal conductivity properties.

8. A computing device according to claim 1, The hysteresis characteristic of the filler aggregate is the hysteresis loss value of the filler aggregate. A computing device in which the hysteresis characteristics of the composite material are the hysteresis loss value of the composite material.

9. A computing device according to claim 2, The mechanical properties of the filler aggregate are determined by a calculation device that uses an approximate curve fitted within a predetermined strain range from the stress-strain relationship of the filler aggregate obtained based on the first simulation model.

10. A computing device according to claim 2, The first simulation model is a computing device based on coarse-grained molecular dynamics simulation or whole-atom simulation.

11. A computing device according to claim 4, The second simulation model is a computing device that is based on the finite element method, particle method, or phase-field method.

12. A computing device according to claim 2, The hysteresis characteristics of the filler aggregate are determined based on the area ratio within the positive stress range, according to the calculation device.

13. A prediction method performed by a computing device for predicting the hysteresis properties of a composite material including polymers and fillers, To obtain the correspondence between the mechanical properties of the filler aggregate and the hysteresis properties of the said filler aggregate, The mechanical properties of the composite material based on the filler arrangement are obtained by utilizing the mechanical properties of the acquired filler aggregates, Based on the aforementioned correspondence and the mechanical properties of the composite material, predict the hysteresis properties of the composite material, A prediction method that includes this.

14. A program for predicting the hysteretic properties of composite materials containing polymers and fillers, wherein a computer... To obtain the correspondence between the mechanical properties of the filler aggregate and the hysteresis properties of the said filler aggregate, The mechanical properties of the composite material based on the filler arrangement are obtained by utilizing the mechanical properties of the acquired filler aggregates, Based on the aforementioned correspondence and the mechanical properties of the composite material, predict the hysteresis properties of the composite material, A program that executes the command.

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