Environment condition prediction system and program, as well as environment condition prediction method

Abstract

To provide a system, program and method that predict an environment condition in which a water absorbing mold stands at a preliminarily determined water absorption rate.SOLUTION: An environment condition prediction system 100 comprises: a learning unit 110 that learns a diffusion coefficient prediction model, an equilibrium water absorption rate prediction model and / or a material characteristic prediction model; a computation unit 120 that executes a prediction computation, using the equilibrium water absorption rate prediction model and diffusion coefficient prediction model; an identification unit 130 that identifies an environment condition in which a water absorbing mold stands at a preliminarily determined water absorption rate; a material characteristic prediction unit 140 that predicts a material characteristic of the water absorbing mold, using the material characteristic prediction model; a proposition unit 150 that proposes the environment condition the identification unit 130 identifies to a user; and an output unit 160 that outputs the proposition of the proposition unit 150. The identification unit 130 is configured to identify the environment condition on the basis of shape information on a shape of the water absorbing mold, a diffusion coefficient of water in the water absorbing mold, and an equilibrium water absorption rate of the water absorbing mold.SELECTED DRAWING: Figure 1A

Description

[Technical field]

[0001] The present invention relates to an environmental condition prediction system, a program, and an environmental condition prediction method. [Background technology]

[0002] Patent Document 1 describes that the method includes "a method for analyzing organic material characteristics, comprising: reading characteristic data for each temperature from a material characteristic database storing characteristic data of an organic material to be analyzed, the characteristic data including a linear expansion coefficient for each temperature during a temperature rise process and a linear expansion coefficient for each temperature during a temperature drop process; and numerically analyzing the expansion / contraction characteristics of the organic material during the temperature rise process and the temperature drop process based on the given material characteristic data and the linear expansion coefficient for each temperature" (Claim 1). Patent Document 2 describes that the optical characteristic analysis system for an optical device includes at least: "a diffusion constant acquisition means for reading out stable arrangement data from a stable arrangement storage means for storing stable arrangements in which the potential energy between atoms constituting the molecules of a component material and water molecules arranged in an arbitrary rectangular parallelepiped region of an optical system with an unknown diffusion constant is substantially constant, and a diffusion constant is calculated from the displacement of the water molecules obtained by analyzing the movement of the water molecules from the stable arrangement for a predetermined time by a molecular dynamics method, and storing the diffusion constant in a diffusion constant storage means; an optical system model generation means for dividing the optical system into meshes, generating a numerical analysis model required for numerical analysis by a finite element method, and storing the model in a numerical analysis model storage means; and an optical characteristic calculation means for calculating optical characteristics from a refractive index distribution obtained by calculating a water absorption distribution of the optical system under a predetermined humidity environment using the diffusion constant and the numerical analysis model, and a post-deformation optical surface shape obtained by calculating a displacement of the optical system caused by the water absorption distribution" (Claim 1). [Prior art document] [Patent documents] [Patent Document 1] JP 2005-156494 A [Patent Document 2] JP 2006-153810 A Summary of the Invention

[0003] In a first aspect of the present invention, there is provided an environmental condition prediction system including a specifying unit for specifying an environmental condition under which a water-absorbent molding has a predetermined water absorption rate. The specifying unit may specify the water absorption rate based on shape information on the shape of the water-absorbent molding having water absorption, a diffusion coefficient of water in the water-absorbent molding, and an equilibrium water absorption rate of the water-absorbent molding.

[0004] In the above, the environmental conditions may be one or a combination of the substances surrounding the water-absorbent molding, the temperature at which the water-absorbent molding is placed, humidity, and time.

[0005] In the above, the information relating to the shape of the water-absorbent molding may include information relating to the shape and / or size of the water-absorbent molding.

[0006] In the above, the predetermined water absorption rate may be an equilibrium water absorption rate under specified environmental conditions, which are environmental conditions that are specified in advance for the water-absorbent molding, or may be a water absorption rate that is directly input by the user.

[0007] In the above, the environmental condition prediction system may further include a proposing unit. The proposing unit may propose an environmental condition, among the environmental conditions identified by the identifying unit, that reaches an equilibrium water absorption rate under a designated environmental condition more quickly than under the designated environmental condition.

[0008] In the above, the proposing unit may propose an environmental condition that most quickly reaches the equilibrium water absorption rate under the designated environmental condition, from among the plurality of environmental conditions identified by the identifying unit.

[0009] In the above, the specifying unit may output a result of a simulation of the water absorption state of the water-absorbent molding under the environmental conditions proposed by the proposing unit.

[0010] In the above, the identifying unit may identify, from among a plurality of environmental conditions prepared in advance, a closest environmental condition that can provide an equilibrium water absorption rate closest to the equilibrium water absorption rate under a designated environmental condition that is a pre-designated environmental condition.

[0011] In the above, the specifying unit may specify a first environmental condition having an equilibrium water absorption rate higher than the equilibrium water absorption rate in a designated environmental condition, which is a pre-specified environmental condition, from among a plurality of environmental conditions prepared in advance. The specifying unit may simulate the water absorption state of the water-absorbent molding under the first environmental condition until the water absorption state of the water-absorbent molding under the first environmental condition becomes a pre-specified first state. The specifying unit may specify a second environmental condition having an equilibrium water absorption rate closest to the equilibrium water absorption rate under the designated environmental condition. The specifying unit may simulate the water absorption state of the water-absorbent molding under the second environmental condition, starting from the first state.

[0012] In the above, the environmental condition prediction system may further include a learning unit. The learning unit may learn a diffusion coefficient prediction model for predicting the diffusion coefficient of water in the water-absorbent molding under predetermined environmental conditions from at least material information and shape information of the water-absorbent molding.

[0013] In the above, the learning unit may learn an equilibrium water absorption prediction model for predicting the equilibrium water absorption of the water-absorbent molding under predetermined environmental conditions from the material information and shape information of the water-absorbent molding.

[0014] In the above, the learning section may learn a material property prediction model that predicts the physical material properties of the water-absorbent molding from the material information, shape information, water absorption state of the water-absorbent molding, and specified environmental conditions of the water-absorbent molding.

[0015] In the above, the environmental condition prediction system may further include a material property prediction section, which may predict the material property of the water-absorbent molding by using a material property prediction model.

[0016] In the above, the physical properties may include at least one of the mechanical properties and the dimensional change of the water-absorbent formed body.

[0017] In a second aspect of the present invention, there is provided a program which, when executed by a computer, causes the computer to function as the environmental condition prediction system of the first aspect.

[0018] In a third aspect of the present invention, there is provided an environmental condition prediction method executed by the environmental condition prediction system of the first aspect. The environmental condition prediction method includes a specifying step. In the specifying step, an environmental condition under which the water-absorbent molding has a predetermined water absorption rate may be specified. The specifying step may be performed based on shape information on the shape of the water-absorbent molding, the diffusion coefficient of water in the water-absorbent molding, and the equilibrium water absorption rate of the water-absorbent molding.

[0019] The above summary of the invention does not list all of the features of the present invention. In addition, subcombinations of these features may also be inventions. [Brief description of the drawings]

[0020] [Figure 1A] 1 shows a configuration of an environmental condition prediction system 100 according to the present embodiment. [Figure 1B] 1 shows a configuration of an environmental condition prediction system 100 in a modified example of the present embodiment. [Diagram 2] 4 shows an example of information input and output in the environmental condition prediction system according to the present embodiment. [Diagram 3] 3 shows a flow of prediction by the environmental condition prediction system 100 according to the present embodiment. [Figure 4A] 13 shows an example of an input screen related to S400 of the present embodiment. [Figure 4B] An example of an input screen when "target water absorption rate" is selected with selection button 418 is shown. [Diagram 5] 11 shows an example of a sub-flow of S700 according to the present embodiment. [Figure 6] An example of a simulation of the water absorption state is shown. [Figure 7] Another example of a simulation of a water absorption state is shown. [Figure 8] An example of material properties predicted by the material property prediction unit 140 is shown below. [Figure 9] 11 shows another example of the sub-flow of S700 according to the present embodiment. [Figure 10] 1 shows an example of a plurality of environmental conditions. [Figure 11] 11 shows another example of the sub-flow of S700 according to the present embodiment. [Figure 12] 22 illustrates an example computer 2200 in which aspects of the present invention may be embodied, in whole or in part. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0022] 1A shows the configuration of an environmental condition prediction system 100 according to this embodiment. The environmental condition prediction system according to this embodiment specifies the environmental conditions under which a water-absorbent molding has a predetermined water absorption rate.

[0023] The water-absorbent molding may be an object that has water-absorbency and can be molded by any method (e.g., injection molding, extrusion molding, lamination molding such as 3D printer, molding, cutting, etc.). For example, the water-absorbent molding may be plastic.

[0024] Water-absorbent moldings are usually dry immediately after production, but may absorb water from water that adheres to the body or moisture in the air during use. For this reason, when designing a part using a water-absorbent molding, it is necessary to take into consideration the possibility of dimensional changes and changes in physical properties occurring between the state immediately after production and the state where the equilibrium water absorption rate is reached. For this reason, it was necessary to leave the water-absorbent molding in a natural environment for a long period of time to reproduce the state where the water absorption reaches equilibrium, and to identify the dimensional changes and changes in properties.

[0025] There are methods for speeding up water absorption, such as spraying water directly onto the water-absorbent molding or immersing it in water, but the method of applying liquid water may cause the water-absorbent molding to have a state of water absorption that deviates from the equilibrium water-absorption state during actual use. In this way, it takes a long time to control the water-absorbent molding to a predetermined water absorption rate, or there is room for improvement in the reproducibility of the equilibrium water absorption state. Here, the environmental condition prediction system 100 provides information on environmental conditions that cause the water-absorbent molding to have a predetermined water absorption rate, and that reach the predetermined water absorption rate in a shorter time than in the natural environment.

[0026] The environmental condition prediction system 100 includes a learning unit 110, a calculation unit 120, a specification unit 130, a material property prediction unit 140, a proposal unit 150, and an output unit 160.

[0027] The learning unit 110 learns a prediction model used in the environmental condition prediction system 100. For example, the learning unit 110 may learn a diffusion coefficient prediction model, an equilibrium water absorption prediction model, and / or a material property prediction model.

[0028] The diffusion coefficient prediction model predicts the diffusion coefficient of water in a water-absorbent molding. For example, the diffusion coefficient prediction model predicts the diffusion coefficient of water in the water-absorbent molding under predetermined environmental conditions from at least material information of the water-absorbent molding. The diffusion coefficient prediction model may be a model that inputs the material information and the environmental conditions and outputs the diffusion coefficient of water in the water-absorbent molding.

[0029] The equilibrium water absorption prediction model predicts the equilibrium water absorption of a water-absorbent molding. For example, the equilibrium water absorption prediction model predicts the equilibrium water absorption of a water-absorbent molding under predetermined environmental conditions from material information of the water-absorbent molding. The equilibrium water absorption is the water absorption in a state where the water absorption of the water-absorbent molding does not change any more. The equilibrium water absorption prediction model may be a model that inputs material information and environmental conditions and outputs the equilibrium water absorption.

[0030] The material property prediction model predicts material properties such as physical properties and / or chemical properties of a water-absorbent molding. For example, the material properties of the water-absorbent molding are predicted from the material information of the water-absorbent molding, the water absorption state of the water-absorbent molding, and specified environmental conditions. The material property prediction model may be a model that inputs the material information, the water absorption state, and the environmental conditions, and outputs the material properties.

[0031] The water absorption state indicates the state of water absorption of the water-absorbent molding. For example, the water absorption state may be the average water absorption rate of the entire water-absorbent molding, the distribution of the water absorption rate, and / or the water absorption rate of a part (for example, the center of gravity, center, or end of the water-absorbent molding). For example, the distribution of the water absorption rate may indicate the water absorption rate at a position of the water-absorbent molding (for example, a position in three-dimensional coordinates, a position on two-dimensional coordinates, or a position in one dimension (for example, the thickness direction)).

[0032] The material properties may be physical properties and / or chemical properties of the water-absorbent molding, and may include at least one of mechanical properties and dimensional change. For example, the physical properties may be volume, volume change, dimensions, dimensional change, weight, weight change, expansion rate, tensile modulus, tensile stress, compressive stress, shear stress, tensile elongation, flexural modulus, flexural strength, taper abrasion resistance, hardness such as Rockwell hardness, and / or other physical strengths. For example, the chemical properties may be pH, molecular weight, hydrophilicity, lipophilicity, and / or surface tension.

[0033] The calculation unit 120 executes a prediction calculation using the equilibrium water absorption prediction model and the diffusion coefficient prediction model. For example, the calculation unit 120 may execute a prediction using the equilibrium water absorption prediction model and the diffusion coefficient prediction model learned by the learning unit 110. The calculation unit 120 may input material information and environmental conditions to the prediction model to obtain the predicted diffusion coefficient and equilibrium water absorption.

[0034] The calculation unit 120 may further perform calculations based on a diffusion equation to perform a simulation of the change over time of the water absorption state of the water-absorbent molding, etc. For example, the calculation unit 120 may perform a simulation of the water absorption state based on the acquired diffusion coefficient and equilibrium water absorption rate, and shape information related to the shape of the water-absorbent molding.

[0035] The specifying unit 130 specifies the environmental conditions under which the water-absorbent molding has a predetermined water absorption rate. For example, the specifying unit 130 may specify the environmental conditions using the calculation results of the water absorption state of the water-absorbent molding under each environmental condition performed by the calculation unit 120. In this way, the specifying unit 130 may specify the environmental conditions based on the shape information, the diffusion coefficient of water in the water-absorbent molding, and the equilibrium water absorption rate of the water-absorbent molding.

[0036] Here, the predetermined water absorption rate may be the equilibrium water absorption rate of the water-absorbent molding under environmental conditions (hereinafter also referred to as "designated environmental conditions") designated in advance. The designated environmental conditions may be an environment in which the water-absorbent molding is normally used, for example, in air with a temperature of 23°C and a humidity of 50%. The designated environmental conditions may be an environment different from an environment in which the water-absorbent molding may be used, for example, in air with a temperature of 23°C and a humidity of 50%, a temperature of 35°C and a humidity of 80%, a temperature of 80°C and a humidity of 50%, a temperature of 23°C and a humidity of 90%, or a temperature of 0°C and a humidity of 30%.

[0037] Alternatively, the predetermined water absorption rate may be a water absorption rate input by a user to the environmental condition prediction system 100. The function of the calculation unit 120 may be executed by the determination unit 130. Details of a specific determination method by the determination unit 130 will be described later.

[0038] The material property prediction unit 140 predicts the material property of the water-absorbent molding using a material property prediction model. For example, the material property prediction unit 140 predicts the change in dimensions of the water-absorbent molding placed in a specified environment.

[0039] The suggestion unit 150 suggests to the user at least some of the environmental conditions identified by the identification unit 130. The suggestion unit 150 may suggest one or more environmental conditions. The suggestion unit 150 may suggest an environmental condition, among the multiple environmental conditions identified by the identification unit 130, that reaches the equilibrium water absorption rate in the designated environmental condition more quickly than the designated environmental condition.

[0040] The output unit 160 outputs the proposal of the proposal unit 150. The output unit 160 outputs a simulation result of the water absorption state of the water-absorbent molding under the environmental conditions proposed by the proposal unit 150. The output unit 160 may obtain and output the simulation result obtained from the calculation unit 120. The output unit 160 may output the prediction result of the material property prediction unit 140.

[0041] The environmental condition prediction system 100 may be a computer such as a PC (personal computer), a tablet computer, a smartphone, a workstation, a server computer, or a general-purpose computer, or may be a computer system in which a plurality of computers are connected.

[0042] Alternatively, the environmental condition prediction system 100 may be a dedicated computer designed for each application, or may be dedicated hardware realized by a dedicated circuit. The environmental condition prediction system 100 may be implemented by one device (computer), or may be realized by multiple devices with different roles. For example, the environmental condition prediction system 100 may be a server-client system that provides a cloud service to users who use the environmental condition prediction method.

[0043] Although not specifically described below, the environmental condition prediction system 100 is equipped with a memory / hard disk, etc., in which information necessary for processing is appropriately stored, and the environmental condition prediction system 100 transmits information between each processing module, such as the learning unit 110, the calculation unit 120, the identification unit 130, the material property prediction unit 140, the proposal unit 150, and the output unit 160, as necessary.

[0044] In this way, the environmental condition prediction system 100 of the present embodiment can specify the environmental conditions under which the water-absorbent molding has a predetermined water absorption rate by using each prediction model, diffusion equation, etc. This makes it possible to reproduce the state in which the water absorption reaches equilibrium without leaving the water-absorbent molding in the natural environment for a long period of time.

[0045] 1B shows a configuration of an environmental condition prediction system 100 in a modified example of the present embodiment. In this modified example, the learning unit 110 is provided outside the environmental condition prediction system 100. For example, the learning unit 110 may be provided in a computer separate from the environmental condition prediction system 100. In this modified example, the environmental condition prediction system 100 acquires a diffusion coefficient prediction model, an equilibrium water absorption prediction model, and / or a material property prediction model from the external learning unit 110.

[0046] 2 shows an example of input and output of information in the environmental condition prediction system according to the present embodiment. In one embodiment, a diffusion coefficient prediction model 210 may input material information 204 and environmental conditions 208 to predict a diffusion coefficient 206. An equilibrium water absorption prediction model 212 may input material information 204 and environmental conditions 208 to predict an equilibrium water absorption 214.

[0047] The diffusion equation 220 is used to calculate the water absorption rate 222 and its change over time based on the shape information 202, the diffusion coefficient 206, and the equilibrium water absorption rate 214. The material property prediction model 230 inputs the material information 204, the environmental conditions 208, and the water absorption rate 222 to predict the material property 232.

[0048] Each model and diffusion equation 220 may not input all of the information described in FIG. 2, or may input additional information.

[0049] 3 shows a flow of prediction by the environmental condition prediction system 100 according to this embodiment. The environmental condition prediction system 100 executes, for example, each process of S100 to S800, to identify and output the environmental conditions under which the water-absorbent molding has a predetermined water absorption rate. Some of S100 to S800 may be omitted. Other operations may be executed in addition to S100 to S800.

[0050] In S100, the learning unit 110 learns a diffusion coefficient prediction model for predicting the diffusion coefficient of water in a water-absorbent molding. The diffusion coefficient prediction model may receive at least one of material information and environmental conditions as input data, and output the diffusion coefficient of water in the water-absorbent molding. The diffusion coefficient prediction model may further receive shape information, which will be described later.

[0051] The material information may be information about the material of the water-absorbent molding. For example, the material information may include information about the type and / or amount of a material such as a resin, the type and / or shape of a filler, the blend amount and / or blend ratio of the resin and the filler, the name of the raw material, the sales name of the raw material, the manufacturer of the raw material, the time of manufacture, the storage period, and / or the storage environment.

[0052] The material information may include factors that affect the water absorbency of the water-absorbent formed body due to the material. For example, when information on the type of material such as resin is used as the material information, the information may include the ratio of amorphous parts in the resin, the type and size of crystal lattice, and / or the ratio of polar groups (e.g., carboxyl groups and amide groups) in the resin, and the degree of molecular orientation. The material information may also include information on the shape of the filler, such as the aspect ratio, diameter, and / or length.

[0053] The environmental conditions may be information about the environment in which the water-absorbent molding is placed. For example, the environmental conditions may include information about the substance surrounding the water-absorbent molding (e.g., the name of the surrounding substance, or a designation of whether the water-absorbent molding is placed in air or water, etc.), temperature, humidity, time, and / or air pressure, etc. As an example, the environmental conditions may be a combination of the substance surrounding the water-absorbent molding, the temperature at which the water-absorbent molding is placed, and humidity. The environmental conditions may further include the time at which the water-absorbent molding is placed. When the water-absorbent molding is placed in a plurality of different environments (e.g., when the environment is different on each side of a board material), the environmental conditions may include information about a plurality of environments (e.g., temperature and humidity on a plurality of sides, etc.).

[0054] The learning unit 110 may learn the diffusion coefficient prediction model based on the teacher data. For example, the teacher data includes a plurality of pairs of explanatory variable data (e.g., material information and environmental conditions) and objective variable data (e.g., diffusion coefficients). The learning unit 110 may learn the diffusion coefficient prediction model by an existing method such as regression analysis.

[0055] The numerical range of the aspect ratio of the filler input as material information in the training data may be 1 to 100, the numerical range of the diameter of the filler may be 0.1 to 1000 μm, the numerical range of the length of the filler may be 0.1 to 2000 μm, and the numerical range of the filler proportion may be 0 to 99 wt%. The numerical range of the storage period input as material information in the training data may be 0 days to 1000 days. The numerical range of the temperature input as environmental conditions in the training data may be -50°C to 150°C. The numerical range of the humidity input as environmental conditions in the training data may be 0 to 100%.

[0056] When information on the type of material, such as resin, is used as material information in the training data, the numerical range of the ratio of the amorphous portion in the resin may be 0 to 100 wt%, the numerical range of the size of the crystal structure may be 0.1 nm to 100 μm, and the numerical range of the concentration of polar groups (e.g., carboxyl groups and amide groups) in the resin may be 0 to 0.1 mol / g. The numerical range of the diffusion coefficient in the training data is 0.001 to 10.0 mm. 2 It can be / day.

[0057] In S200, the learning unit 110 learns an equilibrium water absorption prediction model for predicting the equilibrium water absorption rate of water in the water-absorbent molding. The equilibrium water absorption prediction model may receive at least one of material information and environmental conditions as input data, and output the equilibrium water absorption rate of water in the water-absorbent molding. The equilibrium water absorption prediction model may further receive shape information, which will be described later.

[0058] The learning unit 110 may learn the equilibrium water absorption prediction model based on the teacher data. For example, the teacher data includes a plurality of pairs of explanatory variable data (e.g., material information and environmental conditions) and objective variable data (e.g., equilibrium water absorption). The learning unit 110 may learn the equilibrium water absorption prediction model by an existing method such as regression analysis. Compared with the case of experimentally obtaining the equilibrium water absorption, this embodiment not only significantly shortens the time required to obtain the equilibrium water absorption using the equilibrium water absorption prediction model, but also enables the manufacture of water-absorbent moldings with high accuracy in dimensions and material properties under specified environmental conditions.

[0059] The numerical range of the training data may be the same as that described in S100. The numerical range of the equilibrium water absorption in the training data may be 0 to 10%.

[0060] The diffusion coefficient prediction model and the equilibrium water absorption prediction model (hereinafter, simply referred to as "prediction model") may be a model for predicting the diffusion coefficient and equilibrium water absorption for each layer by dividing the water-absorbent molding into any number of layers in the thickness direction. For such prediction, the learning unit 110 may learn the diffusion coefficient prediction model and the equilibrium water absorption prediction model for each layer.

[0061] For example, it is assumed that the water-absorbent molding is divided into two layers, the layer that is in direct contact with the external environment being the skin layer, and the layer that is not in direct contact with the external environment being the core layer. The learning unit 110 may learn a diffusion coefficient prediction model and an equilibrium water absorption prediction model for each of the skin layer and the core layer. The ratio of the skin layer to the core layer may be used as a weight, and the two layers of the skin layer and the core layer may be integrated by weighting the values ​​predicted from the prediction models of each layer, and this value may be calculated as the numerical value of the entire water-absorbent molding.

[0062] When preparing a prediction model for each of a plurality of layers, the orientation of the filler may be included as part of the material information. The numerical range of the orientation of the filler may be 0.0 to 1.0. When the water-absorbent molding is an injection-molded molding, the orientation of the filler may be a numerical range of three axes, that is, the flow direction, the direction perpendicular to the flow, and the thickness direction during injection molding, and the numerical range of each axis may be 0.0 to 1.0.

[0063] In addition, when preparing a prediction model for each of a plurality of layers, a prediction model may be generated only for some layers, and for layers for which a prediction model is not generated, the diffusion coefficient and / or equilibrium water absorption may be predicted using the results of the prediction models for the other layers. For example, a diffusion coefficient prediction model and an equilibrium water absorption prediction model are created for some layers, and a regression equation or the like is generated based on experimental data including the diffusion coefficient and equilibrium water absorption for each layer. Then, the values ​​of the diffusion coefficient and / or equilibrium water absorption of the remaining layers for which no prediction model is used may be obtained by applying the predicted values ​​for some layers with the prediction model to the regression equation or the like.

[0064] When the water-absorbent molding is divided into a plurality of layers, the simulation calculation based on the diffusion equation (e.g., S740 described later) may be performed for each layer separately using the predicted values ​​of the equilibrium water absorption and diffusion coefficient obtained above for each layer. Alternatively, the simulation calculation based on the diffusion equation for the entire water-absorbent molding may be performed using a weighted average value obtained by multiplying the predicted values ​​of the equilibrium water absorption and diffusion coefficient obtained above for each layer by weights based on the ratio of each layer and adding them up.

[0065] In S300, the learning unit 110 learns a material property prediction model for predicting the material property of the water-absorbent molding. The material property prediction model may receive at least one of material information, environmental conditions, and water absorption rate as input data, and output the material property of the water-absorbent molding. The material property prediction model may further receive shape information, which will be described later.

[0066] The water absorption rate input to the material property prediction model may be distribution data of the water absorption rate at the position of the water-absorbent molding (for example, a position in three-dimensional coordinates, a position on two-dimensional coordinates, or a position in one dimension (for example, the thickness direction)). The water absorption rate input to the material property prediction model may be the average water absorption rate of the entire water-absorbent molding. The water absorption rate input to the material property prediction model may be output from a diffusion equation described below.

[0067] The learning unit 110 may learn the material property prediction model based on the training data. For example, the training data includes a plurality of pairs of explanatory variable data (e.g., material information, environmental conditions, and water absorption rate) and objective variable data (e.g., physical properties). The learning unit 110 may learn the material property prediction model by an existing method such as regression analysis.

[0068] The numerical ranges of the explanatory variables in the training data may be the same as those explained in S100, but the numerical range of the water absorption rate may be 0 to 100%.

[0069] The physical properties, which are the data of the objective variables, may include any one or more of the following data: dimensional change rate in the mold direction (MD) of the resin, dimensional change rate in the transverse direction (TD) to the resin flow direction, tensile modulus, flexural modulus, stress, and strain. The numerical range of the dimensional change rate in the MD and TD directions in the teacher data may be 0 to 10%, the numerical range of the tensile modulus and flexural modulus may be 1 MPa to 1000 GPa, the numerical range of the stress may be 0 to 10000 MPa, and the numerical range of the strain may be 0 to 100%.

[0070] S100 to S300 do not have to be performed in the order described. For example, they may be performed in the order of S300, S200, and S100. Furthermore, at least some of S100 to S300 may be performed in parallel. S100 to S300 may all be performed in parallel.

[0071] In S400, the environmental condition prediction system 100 receives inputs of information on the water-absorbent molding to be the target of environmental condition identification and information on designated environmental conditions, which are environmental conditions designated in advance for the water-absorbent molding, from the user. The information on the water-absorbent molding may be the above-mentioned material information and shape information.

[0072] The shape information may include information on the shape of the water-absorbent molding (e.g., plate, cube, rectangular parallelepiped, sphere, oval sphere, cone, triangular pyramid, polygon, etc.) and / or size (e.g., length of each side, etc.). The shape information may be three-dimensional data of the water-absorbent molding. The shape information may also be thickness data of the water-absorbent molding.

[0073] Fig. 4A shows an example of an input screen related to S400 of this embodiment. The environmental condition prediction system 100 may acquire the designated environmental conditions, material information of the water-absorbent molding, and shape information from the information input by the user to the input screen shown in Fig. 4A.

[0074] In the embodiment of Fig. 4A, it is assumed that the water-absorbent molding is a plate having a first surface and a second surface, and the environmental conditions on the first surface side are different from the environment on the second surface side. For example, when the water-absorbent molding is used in a vehicle such as an automobile, the environment may be different between the outer surface in contact with the outside air / water and the inner surface in contact with the internal combustion engine, battery, etc. In such a case, one environmental condition includes information on the environment for each of the multiple surfaces.

[0075] For example, as shown in the figure, whether the environment of each surface (first surface and second surface) is in the air or in water that is in direct contact with water may be input via selection button 402 and selection button 403. The temperature and humidity of each surface (first surface and second surface) may be input via input field 404, input field 405, input field 406, and input field 407 on the input screen.

[0076] As shown in the figure, information on "material type (resin A)" is entered as material information in a selection field 410. Furthermore, as shape information, "shape (plate-like)" is entered in a selection field 412, and "thickness (4 mm)" is entered in an input field 414. When the shape is plate-like, it is possible to simulate the water absorption state by inputting only the thickness, so in this example, only "thickness" is entered, but when the shape is other than plate-like, more detailed dimensions such as height, width and / or length may be entered.

[0077] An initial state of water absorption when performing a simulation of the water absorption state later may be further input in the input field 416. For example, "initial water absorption (0.2%)" is input in Fig. 4A. Alternatively, one-dimensional, two-dimensional or three-dimensional distribution data of water absorption may be input as the initial water absorption.

[0078] Either "equilibrium water absorption" or "target water absorption" may be selected by using the selection button 418 on the input screen. When the equilibrium water absorption is selected, the environment of the first surface and the environment of the second surface are input as described above, and the equilibrium water absorption in the environment is calculated in S500 described later. For example, the "equilibrium water absorption" may be selected when dealing with a water-absorbent molding whose equilibrium water absorption is unknown.

[0079] When "target water absorption rate" is selected with the selection button 418 on the input screen of FIG. 4A in S400, the input screen is switched to that of FIG. 4B.

[0080] Fig. 4B shows an example of an input screen when "target water absorption" is selected with the selection button 418. In the input screen of Fig. 4B, a numerical value of the water absorption that will be a search target in the later S700 may be input in a target water absorption field 420. When "target water absorption" is selected, it is not necessary to calculate the equilibrium water absorption. Therefore, input of information regarding the environment on the first and second surface sides may be omitted, and only material information, shape information, and information on the initial state may be input.

[0081] When "target water absorption rate" is selected in S400, the process of S500 described below may be omitted.

[0082] Next, in S500, the calculation unit 120 predicts the equilibrium water absorption using the equilibrium water absorption prediction model. For example, the calculation unit 120 inputs the information of the water-absorbent molding input in S400 and the designated environmental conditions to the equilibrium water absorption prediction model, and predicts the equilibrium water absorption of the water-absorbent molding under the designated environmental conditions.

[0083] Next, in S700, the identifying unit 130 searches for an environmental condition under which the water-absorbent molding has a predetermined water absorption rate, and outputs the result. The identifying unit 130 may identify an environmental condition under which the water-absorbent molding reaches a predetermined water absorption rate in a shorter time. For example, the identifying unit 130 may identify an environmental condition under which the equilibrium water absorption rate under the specified environmental condition predicted in S500 is reached more quickly than when the water-absorbent molding is left in the specified environmental condition. Instead of the equilibrium water absorption rate under the specified environmental condition, a target water absorption rate input by the user may be used.

[0084] Fig. 5 shows an example of a subflow of S700 according to this embodiment. The environmental condition prediction system 100 may search for environmental conditions by executing the flow from S720 to S780 in Fig. 5. The environmental condition prediction system 100 searches for environmental conditions by performing loop processing from S720 to S760.

[0085] In S720, the identification unit 130 sets new environmental conditions. In the first S720, the identification unit 130 may set specified environmental conditions (for example, a temperature of 23° C. and a humidity of 50%). In the second or subsequent S720, the identification unit 130 sets new environmental conditions that were not set in the previous S720.

[0086] For example, in the second or subsequent S720, the determination unit 130 may randomly set the environmental conditions. For example, in the second or subsequent S720, the determination unit 130 may preferentially set the environmental conditions (e.g., higher humidity and / or higher temperature than the designated environmental conditions) that are expected to reach the equilibrium water absorption state earlier than the designated environmental conditions.

[0087] As an example, the determination unit 130 may set environmental conditions with a temperature and / or humidity higher than the designated environmental conditions by a predetermined numerical range and / or magnification, and may reduce the numerical range and / or magnification each time the number of times S720 is performed increases. This allows the environmental condition prediction system 100 to save computational resources and / or storage resources.

[0088] Also, for example, in S720 from the second time onward, the specifying unit 130 may set the environmental conditions from the second time onward by an existing search method (for example, a gradient method, etc.) so that the equilibrium water absorption rate of the set environmental conditions approaches the equilibrium water absorption rate of the specified environmental conditions. This can save the calculation resources and / or storage resources of the environmental condition prediction system 100.

[0089] Hereinafter, the environmental conditions set in S720 will also be referred to as "set environmental conditions" in the loop process including S720.

[0090] Next, in S730, the calculation unit 120 calculates the diffusion coefficient and the equilibrium water absorption. For example, the calculation unit 120 may input the material information input in S400 and the set environmental conditions set in S720 to the diffusion coefficient prediction model learned in S100 to calculate the diffusion coefficient. For example, the calculation unit 120 may input the material information input in S400 and the set environmental conditions set in S720 to the equilibrium water absorption prediction model learned in S200 to calculate the equilibrium water absorption. If the "target water absorption" is input in S400 or the equilibrium water absorption has already been calculated for the specified environmental conditions in S500, the calculation process of the equilibrium water absorption may be omitted.

[0091] Next, in S740, the calculation unit 120 executes a simulation of the water absorption state of the water-absorbent molding based on the diffusion equation. For example, the calculation unit 120 may input the shape information input in S400, the diffusion coefficient calculated in S730, and the equilibrium water absorption rate into the diffusion equation, and simulate the change over time in the water absorption rate at each position in the water-absorbent molding. A known diffusion equation may be used.

[0092] An example of the diffusion equation used by the calculation unit 120 will be described. (Diffusion equation) The calculation unit 120 uses the diffusion coefficient D obtained by the diffusion coefficient prediction model and the following diffusion equation to calculate the diffusion of water in a specific humidity environment in the water-absorbent molding by the finite element method, and calculates the water absorption distribution ρ(t, x) at a position x=(Xi, Yi, Zi) inside the water-absorbent molding after a certain time has passed. In the calculation, an equilibrium water absorption is given as a boundary condition, and an arbitrary water absorption is given as an initial condition. The arbitrary water absorption may be the water absorption of the water-absorbent molding after production, or may be the water absorption input by the user. The equilibrium water absorption used in the diffusion equation may be the equilibrium water absorption obtained by the equilibrium water absorption prediction model.

number

[0093] The calculation unit 120 may use a predetermined state or a state input by a user (e.g., the initial water absorption rate in FIG. 4A) as the initial state of the simulation. The calculation unit 120 may execute the simulation until a predetermined condition is reached (e.g., a predetermined time has elapsed, the water absorption rate has reached equilibrium, a predetermined water absorption rate (e.g., a target water absorption rate) has been reached, and / or an instruction to end the simulation has been received from a user, etc.).

[0094] Fig. 6 shows an example of a simulation of the water absorption state. The vertical axis in the figure indicates the average water absorption rate of the entire water-absorbent molding, and the horizontal axis indicates the passage of time. A solid line 610 indicates the transition of the average water absorption rate of the water-absorbent molding under the specified environmental conditions. As shown by the solid line 610, the average water absorption rate of the water-absorbent molding under the specified environmental conditions increases over time from the initial water absorption rate indicated by X, and reaches an equilibrium water absorption rate R1 around time t1, thereby entering an equilibrium state.

[0095] Here, equilibrium refers to the point where there is no change in water absorption rate, or the change in water absorption rate per hour is below a certain value (e.g., 1% difference in water absorption rate / hour) or below a certain rate (e.g., 1% change rate in water absorption rate / hour). Hereinafter, the time required to reach equilibrium is also referred to as the "equilibrium time."

[0096] An example of an equilibrium state may be when the following conditions are met: 1. Weight stability: Three consecutive weight measurements shall be within a tolerance of 0.1%, with the measurements being taken at intervals of at least one day. 2. Moisture content stability: The change in the average moisture content of the material during the test period must be within 0.01%. In addition, the following criteria are used to estimate the time to reach moisture equilibrium: If the moisture diffusion coefficient DZ is known, the time to reach moisture equilibrium is 0.02 × d 2 / DZt or 1 day, whichever is greater, where d is the thickness of the test specimen (mm) and t is the conditioning time (s).

[0097] The dashed line 620 indicates the change in the average water absorption rate of the water-absorbent molding under the set environmental condition different from the specified environmental condition. As shown by the dashed line 620, the average water absorption rate of the water-absorbent molding under the set environmental condition increases over time from the initial water absorption rate indicated by X, and reaches an equilibrium state near the equilibrium water absorption rate R1, which is the same as that under the specified environmental condition, around the equilibrium time t2.

[0098] The dotted line 630 shows the change in the average water absorption rate of the water-absorbent molding under another set environmental condition different from the specified environmental condition. As shown by the dotted line 630, the average water absorption rate of the water-absorbent molding under the other set environmental condition increases over time from the initial water absorption rate indicated by X, and reaches an equilibrium state at an equilibrium water absorption rate R2 higher than R1 around equilibrium time t5. As shown in the figure, under the set environmental condition of the dotted line 630, the water absorption rate becomes equal to R1 at time t4.

[0099] Fig. 7 shows another example of the simulation of the water absorption state. The horizontal axis in the figure indicates the position in the water-absorbent molding (for example, the position in the thickness direction of a plate-like member), and the vertical axis indicates the water absorption rate of the water-absorbent molding at that position. When the water-absorbent molding is a plate-like member, it may be sufficient to deal with the distribution of water absorption rate only in the thickness direction as shown in Fig. 7. In this case, the distribution of water absorption rate in the surface direction is not dealt with.

[0100] For example, solid line 710 shows the distribution of water absorption rate in the thickness direction of the water absorbent molding at point A on solid line 610 in Fig. 6. That is, the average of solid line 710 corresponds to the average water absorption rate at point A on Fig. 6. Solid line 720 shows the distribution of water absorption rate in the thickness direction of the water absorbent molding at point B on solid line 610 in Fig. 6. Solid line 730 shows the distribution of water absorption rate in the thickness direction of the water absorbent molding at point C on solid line 610 in Fig. 6. Solid line 740 shows the distribution of water absorption rate in the thickness direction of the water absorbent molding at point D on solid line 610 in Fig. 6.

[0101] In the first S740, the calculation unit 120 simulates the water absorption state of the water-absorbent molding under the specified environmental conditions. In the second or subsequent S740, the calculation unit 120 simulates the water absorption state of the water-absorbent molding under the set environmental conditions being searched for.

[0102] The environmental condition prediction system 100 returns the process to S720 after the first S740 (i.e., simulating the water absorption state of the water-absorbent molding under the specified environmental conditions). After the second or subsequent S740, the environmental condition prediction system 100 advances the process to S750.

[0103] In S750, the identifying unit 130 identifies an environmental condition under which the water-absorbent molding has a predetermined water absorption rate (for example, an equilibrium water absorption rate under the specified environmental condition, or a target water absorption rate). For example, when the result of performing the simulation in S740 for the set environmental condition shows that the equilibrium water absorption rate (for example, R1) is reached that is the same as the equilibrium water absorption rate under the specified environmental condition, and the equilibrium time is shorter than the equilibrium time (for example, t1) under the specified environmental condition (for example, in the case of the environmental condition of the broken line 620 with the equilibrium time t2), the identifying unit 130 may identify the set environmental condition as being satisfied by the set environmental condition. Such an environmental condition is also referred to as a "specified environmental condition" below.

[0104] The determination unit 130 may determine, as the specific environmental condition, a set environmental condition (e.g., the environmental condition of the dotted line 630 that exceeds R1 at time t4) in which the water absorption rate is equal to the equilibrium water absorption rate in the specified environmental condition before equilibrium, and is shorter than the equilibrium time in the specified environmental condition (e.g., t1). In this case, the determination unit 130 determines the specific environmental condition together with the time (e.g., t4) in which the water absorption rate is equal to the equilibrium water absorption rate in the specified environmental condition (e.g., R1).

[0105] The specifying unit 130 may specify, as the specific environmental condition, a set environmental condition in which the water absorption rate reaches or exceeds a water absorption rate close to the equilibrium water absorption rate under the specified environmental condition at equilibrium, instead of the equilibrium water absorption rate under the specified environmental condition. The water absorption rate close to the equilibrium water absorption rate may be, for example, 90 to 110% of the equilibrium water absorption rate, preferably 95 to 105% of the equilibrium water absorption rate.

[0106] Furthermore, for example, if the result of simulating S740 for set environmental conditions shows that an equilibrium of water absorption rate is reached that is the same as the target water absorption rate, and that the target water absorption rate is reached in a shorter time than the time required to reach the target water absorption rate under specified environmental conditions, the identification unit 130 may identify the environmental conditions that satisfy the set environmental conditions as specific environmental conditions.

[0107] Next, in S760, the identification unit 130 determines whether a predetermined termination condition is satisfied. The termination condition may be, for example, that a search for a predetermined number of environmental conditions has been performed, that a predetermined number of environmental conditions has been identified, that a predetermined time has elapsed, that an environmental condition with an equilibrium time shorter than the equilibrium time (e.g., t1) under the specified environmental condition has been found, and / or that an environmental condition that reaches the target water absorption rate in a shorter time than the specified environmental condition has been found, etc.

[0108] In S780, the suggestion unit 150 suggests one or more excellent environmental conditions from the specific environmental conditions identified by the identification unit 130 in S750. For example, the suggestion unit 150 may suggest one or more environmental conditions that reach the equilibrium water absorption rate in the specified environmental conditions more quickly than the specified environmental conditions, among the multiple environmental conditions identified by the identification unit 130.

[0109] Also, for example, the suggestion unit 150 may suggest an environmental condition that reaches the equilibrium water absorption rate in the specified environmental condition most quickly among the multiple environmental conditions identified by the identification unit 130 in S750. As an example, when the equilibrium time in the specified environmental condition is t1 and the equilibrium water absorption rate is R1, the suggestion unit 150 may suggest an environmental condition with the shortest equilibrium time among the specified environmental conditions with the equilibrium water absorption rate of R1 (or close to R1).

[0110] The output unit 160 may output and / or display on a display or the like the environmental conditions proposed by the proposing unit 150. The output unit 160 may also present the simulation of the water absorption state executed in S740. For example, the output unit 160 may output and / or display on a display or the like the change over time of the water absorption state under the designated environmental conditions and the specific environmental conditions and / or the distribution for each position, as shown in Figs. 6 and 7.

[0111] The output unit 160 may present the changes over time of the water absorption state under a plurality of environmental conditions side by side as shown in Fig. 6. For example, the output unit 160 may present the changes over time under a specified environmental condition and the changes over time under a specific environmental condition side by side. The output unit 160 may display the water absorption rate and its changes over time on a three-dimensional model of the water-absorbent molding.

[0112] After S700, in S800, the material property prediction unit 140 predicts the material property of the water-absorbent molding using a material property prediction model. For example, the material property prediction unit 140 predicts the physical property and / or chemical property of the water-absorbent molding under the environmental condition specified by the specification unit 130.

[0113] For example, the material property prediction unit 140 may input the material information, specific environmental conditions, and water absorption state input in S400 to the material property prediction model learned in S100, and predict properties such as physical properties and / or chemical properties of the water-absorbent molding. The material property prediction unit 140 may predict, for example, the dimensional change and physical strength of the water-absorbent molding. Here, the water absorption rate and its distribution of the water-absorbent molding obtained by the simulations executed in S740, S840, and S1080 may be used as the water absorption state. The output unit 160 may output and / or display the prediction result of the material property prediction unit 140 on a display or the like.

[0114] 8 shows an example of physical properties predicted by the material property prediction unit 140. The material property prediction unit 140 predicts a stress-strain curve (SS curve) of a water-absorbent molding as shown in the figure. The output unit 160 may output and / or display the prediction result of the material property prediction unit 140. The prediction by the material property prediction unit 140 may be performed in parallel with the simulation of the water absorption state in S740.

[0115] According to this embodiment, it is possible to specify environmental conditions that can quickly bring the water-absorbent molding closer to the equilibrium state of the specified environmental conditions. This makes it possible to reproduce the state in which water absorption has reached equilibrium without leaving the water-absorbent molding in a natural environment for a long period of time. According to this embodiment, it is possible to significantly reduce the time required to obtain the equilibrium water absorption rate by using the equilibrium water absorption rate prediction model. In addition, it is possible to predict the material properties of the water-absorbent molding in the water-absorbed state.

[0116] 9 shows another example of a subflow of S700 according to this embodiment. The environmental condition prediction system 100 may execute the search for environmental conditions related to S700 by executing the flow from S810 to S860 in FIG.

[0117] First, in S810, the determination unit 130 sets a plurality of environmental conditions. The determination unit 130 may set the environmental conditions in the same manner as in S720. For example, the determination unit 130 may set a plurality of environmental conditions, such as a humidity and / or a temperature higher than the designated environmental conditions. As an example, the determination unit 130 may set one or a plurality of temperatures lower than the previous S810, and set a plurality of environmental conditions with different humidities for each temperature (for example, 1 to 5% difference).

[0118] 10 shows an example of a plurality of environmental conditions. For example, in S810, the identification unit 130 sets environmental conditions A to E as shown in the figure. Environmental condition A corresponds to the specified environmental condition, and environmental conditions B to E are newly set environmental conditions.

[0119] Next, in S815, the calculation unit 120 calculates the equilibrium water absorption rate for the designated environmental condition and each of the multiple environmental conditions set in S810. The equilibrium water absorption rate may be calculated in the same manner as in S730. In the example of Fig. 10, the equilibrium water absorption rates for environmental conditions A to E are calculated.

[0120] Next, in S820, the identifying unit 130 identifies, among the multiple environmental conditions set in S810, the one that provides the equilibrium water absorption rate that minimizes the error from the equilibrium water absorption rate under the specified environmental condition. Hereinafter, in this embodiment, the environmental condition identified in S820 is referred to as the "specific environmental condition." Note that, in S815, the equilibrium water absorption rate is calculated from the environmental condition on the high temperature and / or high humidity side, and when the error becomes equal to or smaller than a threshold, the environmental condition may be identified as the specific environmental condition, and the calculation of the equilibrium water absorption rate under the subsequent environmental conditions may be stopped.

[0121] 10, among the environmental conditions B to E, the environmental condition C has the smallest error from the equilibrium water absorption rate of the environmental condition A. Therefore, the identifying unit 130 identifies the environmental condition C as the identified environmental condition.

[0122] Next, in S825, the determination unit 130 determines whether the error (i.e., the difference between the equilibrium water absorption rate under the specified environmental conditions and the equilibrium water absorption rate under the specific environmental conditions) is within a predetermined numerical range. If it is determined that it is within the range, the determination unit 130 advances the process to S830. If it is determined that it is not within the range, the determination unit 130 returns the process to S810 and sets multiple environmental conditions again. Here, the determination unit 130 may set environmental conditions different from those set in S810 before the previous time.

[0123] Next, in S830, the calculation unit 120 calculates the diffusion coefficient under the specific environmental conditions. The calculation of the diffusion coefficient may be performed in the same manner as in S730.

[0124] In the example of Fig. 10, the calculation unit 120 calculates the diffusion coefficient of environmental condition A, which is a specified environmental condition, and the diffusion coefficient of environmental condition C, which is a specific environmental condition. Although diffusion coefficients other than those of environmental condition A and environmental condition C are omitted in Fig. 10, these calculations may also be performed.

[0125] Next, in S840, the calculation unit 120 executes a simulation of the water absorption state of the water-absorbent molding under the designated environmental conditions and the specific environmental conditions based on the diffusion equation. For example, the calculation unit 120 may input the shape information input in S400, the diffusion coefficients under the designated environmental conditions and the specific environmental conditions calculated in S830, and the equilibrium water absorption rates under the designated environmental conditions and the specific environmental conditions calculated in S815 into the diffusion equation, and simulate the change over time in the water absorption rate at each position in the water-absorbent molding under the designated environmental conditions and the specific environmental conditions.

[0126] The calculation unit 120 may start the simulation under the designated environmental conditions and the specific environmental conditions from the initial water absorption rate. The simulation of the water absorption state may be performed in the same manner as in S740.

[0127] In the example of Fig. 10, the calculation unit 120 calculates the time to equilibrium by simulating the water absorption state under environmental conditions A and C. In Fig. 10, the time to equilibrium under environmental conditions other than A and C is omitted, but these calculations may also be performed.

[0128] Next, in S860, the proposing unit 150 proposes the specific environmental condition identified in the last S820. The output unit 160 outputs the specific environmental condition proposed by the proposing unit 150. The output unit 160 may also present the simulation of the water absorption state executed in S840. In the example of FIG. 10, the proposing unit 150 proposes environmental condition C. The proposal of the environmental condition may be performed in the same manner as in S780.

[0129] In this way, according to the embodiment of Fig. 9, the identifying unit 130 can identify the closest environmental condition that can obtain the equilibrium water absorption rate closest to the equilibrium water absorption rate under the designated environmental condition, which is the environmental condition designated in advance, from among a plurality of environmental conditions prepared in advance. Also, according to the embodiment of Fig. 9, the number of simulations of the water absorption state can be reduced compared to the embodiment of Fig. 5, and the calculation resources / storage resources can be further saved.

[0130] 11 shows another example of the subflow of S700 according to this embodiment. The environmental condition prediction system 100 may perform a search for environmental conditions by executing the flow from S1010 to S1070 in FIG.

[0131] In S1010, the determination unit 130 sets a plurality of environmental conditions, thereby preparing a plurality of environmental conditions. The determination unit 130 may set the environmental conditions in a manner similar to that of S720. For example, the determination unit 130 may set a plurality of environmental conditions, such as a humidity and / or a temperature higher than the designated environmental conditions.

[0132] Next, in S1020, the calculation unit 120 calculates the equilibrium water absorption rate for the designated environmental conditions and each of the plurality of environmental conditions set in S1010. The calculation of the equilibrium water absorption rate may be performed in the same manner as in S815.

[0133] Next, in S1030, the identifying unit 130 identifies a first environmental condition having an equilibrium water absorption rate higher than the equilibrium water absorption rate in the designated environmental condition by a predetermined range from among the multiple environmental conditions set in S1010. For example, the identifying unit 130 identifies an environmental condition having an equilibrium water absorption rate that is more than 1 time and within 3 times the equilibrium water absorption rate in the designated environmental condition as the first environmental condition.

[0134] The identifying unit 130 may search for environmental conditions starting from the high temperature and / or high humidity side, and identify a first environmental condition that matches the conditions. For example, the identifying unit 130 may identify environmental condition E as the first environmental condition from among environmental conditions B to E in Fig. 10. This allows the calculation resources and / or storage resources of the environmental condition prediction system 100 to be saved.

[0135] Next, in S1040, the calculation unit 120 calculates a diffusion coefficient for each of the designated environmental condition and the first environmental condition identified in S1030. The calculation of the diffusion coefficient may be performed in the same manner as in S730.

[0136] Next, in S1050, the calculation unit 120 executes a simulation of the water absorption state of the water-absorbent molding under the specified environmental conditions based on the diffusion equation. For example, the calculation unit 120 may input the shape information input in S400, the diffusion coefficient under the specified environmental conditions calculated in S1040, and the equilibrium water absorption rate under the specified environmental conditions calculated in S1020 into the diffusion equation, and simulate the change over time in the water absorption rate at each position in the water-absorbent molding under the specified environmental conditions. The calculation unit 120 may start the simulation under the specified environmental conditions from the initial water absorption rate.

[0137] The calculation unit 120 further executes a simulation of the water absorption state of the water-absorbent molding under the first environmental condition based on the diffusion equation. For example, the calculation unit 120 may input the shape information input in S400, the diffusion coefficient under the first environmental condition calculated in S1040, and the equilibrium water absorption rate under the first environmental condition calculated in S1020 into the diffusion equation, and simulate the change over time in the water absorption rate at each position in the water-absorbent molding under the first environmental condition. The calculation unit 120 may start the simulation under the first environmental condition from the initial water absorption rate.

[0138] Here, the calculation unit 120 may execute the simulation until the water absorption state of the water absorbent molding under the first environmental condition becomes a predetermined first state. The first state may be a state in which the water absorption rate of a part (e.g., the center, the end, or the central position of the thickness) or the whole (e.g., the average or median value of a plurality of positions) of the water absorbent molding becomes a predetermined first water absorption rate. The first water absorption rate may be higher than the initial water absorption rate and lower than or equal to the equilibrium water absorption rate under the specified environmental condition. For example, the first water absorption rate may be selected from a range of 0.7 to 1.0 times the equilibrium water absorption rate under the specified environmental condition.

[0139] When it is determined that the first state has been reached, the calculation unit 120 may temporarily suspend the simulation while maintaining the final state. The simulation of the water absorption state in S1050 may be performed in the same manner as in S740.

[0140] Next, in S1060, the identifying unit 130 identifies a second environmental condition that has an equilibrium water absorption rate closest to the equilibrium water absorption rate under the specified environmental condition. For example, the identifying unit 130 identifies the second environmental condition from among the multiple environmental conditions prepared in S1010. For example, in the case of FIG. 10, the identifying unit 130 may identify the environmental condition C from among the environmental conditions B to E as the second environmental condition.

[0141] Next, in S1070, the calculation unit 120 calculates a diffusion coefficient for the second environmental condition identified in S1060. The calculation of the diffusion coefficient may be performed in the same manner as in S730.

[0142] Next, in S1080, the calculation unit 120 executes a simulation of the water absorption state of the water-absorbent molding under the second environmental condition based on the diffusion equation. For example, the calculation unit 120 may input the shape information input in S400, the diffusion coefficient under the second environmental condition calculated in S1070, and the equilibrium water absorption rate under the second environmental condition calculated in S1020 into the diffusion equation, and simulate the change over time in the water absorption rate at each position in the water-absorbent molding under the second environmental condition.

[0143] Here, the calculation unit 120 starts the simulation under the second environmental condition not from the initial state but from the water-absorbent state interrupted in S1050. That is, the calculation unit 120 performs the simulation under the premise that the water-absorbent molding is placed under the first environmental condition for a certain period of time and then placed under the second environmental condition.

[0144] Next, in S1090, the proposing unit 150 proposes the first environmental condition identified in S1030 and the second environmental condition identified in S1060. The output unit 160 outputs these proposal results.

[0145] The output unit 160 may present the simulations of the water absorption state executed in S1050 and S1080 together. For example, the output unit 160 may output both the simulation result of the water absorption state under the specified environmental conditions as shown in Fig. 6 and the simulation result of the water absorption state when the first environmental conditions and the second environmental conditions are successively executed.

[0146] In this way, according to the embodiment of Fig. 10, it is possible to search for conditions that rapidly increase the water absorption rate under conditions that are more excessive than the designated environmental conditions, and then gently approach the equilibrium state of the designated environmental conditions under conditions that are closer to the designated environmental conditions. This makes it possible to identify environmental conditions that can approach the equilibrium state of the designated environmental conditions more quickly than, for example, the embodiment of Fig. 9.

[0147] Various embodiments of the present invention may be described with reference to flow charts and block diagrams, where the blocks may represent (1) stages of a process in which operations are performed or (2) sections of an apparatus responsible for performing the operations. Particular stages and sections may be implemented by dedicated circuitry, programmable circuitry provided with computer readable instructions stored on a computer readable medium, and / or a processor provided with computer readable instructions stored on a computer readable medium. Dedicated circuitry may include digital and / or analog hardware circuitry and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuitry may include reconfigurable hardware circuitry including logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logical operations, memory elements such as flip-flops, registers, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like.

[0148] A computer-readable medium may include any tangible device capable of storing instructions that are executed by a suitable device, such that the computer-readable medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray disks, memory sticks, integrated circuit cards, and the like.

[0149] The computer readable instructions may include either assembler instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0150] Computer readable instructions may be provided to a processor or programmable circuitry of a programmable data processing apparatus, such as a general purpose computer, special purpose computer, or other computer, either locally or over a local area network (LAN), a wide area network (WAN) such as the Internet, etc., to execute the computer readable instructions to create means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0151] 12 illustrates an example of a computer 2200 in which aspects of the present invention may be embodied in whole or in part. Programs installed on the computer 2200 may cause the computer 2200 to function as or perform operations associated with an apparatus or one or more sections of the apparatus according to an embodiment of the present invention and / or to perform a process or steps of a process according to an embodiment of the present invention. Such programs may be executed by the CPU 2212 to cause the computer 2200 to perform specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0152] The computer 2200 according to this embodiment includes a CPU 2212, a RAM 2214, a graphic controller 2216, and a display device 2218, which are connected to each other by a host controller 2210. The computer 2200 also includes input / output units such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes legacy input / output units such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0153] The CPU 2212 operates according to a program stored in the ROM 2230 and the RAM 2214, thereby controlling each unit. The graphic controller 2216 retrieves image data generated by the CPU 2212 into a frame buffer or the like provided in the RAM 2214 or into the graphic controller 2216 itself, and causes the image data to be displayed on the display device 2218.

[0154] The communication interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads programs or data from the DVD-ROM 2201 and provides the programs or data to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0155] The ROM 2230 stores therein a boot program or the like executed by the computer 2200 upon activation, and / or a program that depends on the hardware of the computer 2200. The input / output chip 2240 may also connect various input / output units to the input / output controller 2220 via a parallel port, a serial port, a keyboard port, a mouse port, and the like.

[0156] The programs are provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The programs are read from the computer-readable medium, installed in the hard disk drive 2224, the RAM 2214, or the ROM 2230, which are also examples of computer-readable media, and executed by the CPU 2212. Information processing described in these programs is read by the computer 2200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be constructed by realizing information manipulation or processing according to the use of the computer 2200.

[0157] For example, when communication is performed between the computer 2200 and an external device, the CPU 2212 may execute a communication program loaded in the RAM 2214 and instruct the communication interface 2222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 2212, the communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in the RAM 2214, the hard disk drive 2224, the DVD-ROM 2201, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes reception data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0158] The CPU 2212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the hard disk drive 2224, the DVD-ROM drive 2226 (DVD-ROM 2201), an IC card, etc. to be read into the RAM 2214, and perform various types of processing on the data on the RAM 2214. The CPU 2212 then writes back the processed data to the external recording medium.

[0159] Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording medium and undergo information processing. The CPU 2212 may perform various types of processing on the data read from the RAM 2214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and write back the results to the RAM 2214. The CPU 2212 may also search for information in a file, database, etc. in the recording medium. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 2212 may search for an entry that matches a condition, in which an attribute value of the first attribute is specified, from among the plurality of entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0160] The above-described programs or software modules may be stored in a computer-readable medium on the computer 2200 or in the vicinity of the computer 2200. Also, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable medium, thereby providing the programs to the computer 2200 via the network.

[0161] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the description of the claims that such modifications and improvements can also be included in the technical scope of the present invention.

[0162] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the apparatus, system, program, and method shown in the claims, specifications, and drawings is not specifically indicated as "before" or "prior to," and that the process may be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, it does not mean that the process must be performed in this order. The expression "A and / or B" may mean "A, B, or A and C." The expression "A, B, and / or C" may mean "any one of A, B, and C, or any combination of two or more of them." [Explanation of symbols]

[0163] 100 Environmental Condition Prediction System 110 Learning Department 120 Arithmetic section 130 Specific section 140 Material Property Prediction Department 150 Proposal Department 160 Output section 202 Shape information 204 Material Information 206 Diffusion Coefficient 208 Environmental conditions 210 Diffusion Coefficient Prediction Model 212 Equilibrium Water Absorption Prediction Model 214 Equilibrium water absorption rate 220 Diffusion Equation 222 Water absorption rate 230 Material property prediction model 232 Material Properties 402 Select button 403 Select button 404 Input field 405 Input field 406 Input field 407 Input field 410 Selection column 412 Selection column 414 Input field 416 Input field 418 Selection button 420 Target water absorption column 610 Solid Line 620 dashed line 630 Dotted Line 2200 Computer 2201 DVD-ROM 2210 Host Controller 2212 CPU 2214 RAM 2216 Graphics Controller 2218 Display Device 2220 Input / Output Controller 2222 Communication Interface 2224 Hard Disk Drive 2226 DVD-ROM drive 2230 ROM 2240 Input / Output Chip 2242 Keyboard

Claims

1. a determination unit that determines an environmental condition under which the water-absorbent molding has a predetermined water absorption rate based on shape information relating to the shape of the water-absorbent molding having water absorbency, a water diffusion coefficient in the water-absorbent molding, and an equilibrium water absorption rate of the water-absorbent molding; An environmental condition prediction system comprising:

2. The environmental conditions are one or more combinations of the material surrounding the water-absorbent molding, the temperature, humidity, and time at which the water-absorbent molding is placed; The environmental condition prediction system of claim 1 .

3. The shape information includes information regarding the shape and / or size of the water-absorbent molding, The environmental condition prediction system of claim 1 .

4. The predetermined water absorption rate is an equilibrium water absorption rate under specified environmental conditions, which are environmental conditions that are specified in advance for the water-absorbent molding. The environmental condition prediction system of claim 1 .

5. a suggestion unit that suggests an environmental condition among the environmental conditions specified by the specification unit, in which the equilibrium water absorption rate is reached faster than that in the designated environmental condition; and The environmental condition prediction system of claim 4 further comprising:

6. the suggestion unit suggests an environmental condition that most quickly reaches an equilibrium water absorption rate under the designated environmental condition among the plurality of environmental conditions identified by the identification unit. The environmental condition prediction system according to claim 5 .

7. an output unit that outputs a simulation result of a water absorption state of the water-absorbent molding under the environmental conditions proposed by the proposal unit; The environmental condition prediction system of claim 5 , further comprising:

8. The identifying unit identifies, from among a plurality of environmental conditions prepared in advance, a nearest environmental condition that can obtain an equilibrium water absorption rate closest to an equilibrium water absorption rate under a designated environmental condition that is a pre-designated environmental condition. The environmental condition prediction system according to claim 5 .

9. The identification unit identifies a first environmental condition having an equilibrium water absorption rate that is higher than an equilibrium water absorption rate under a designated environmental condition, which is a pre-designated environmental condition, from among a plurality of environmental conditions prepared in advance, by a predetermined range; the environmental condition prediction system includes a calculation unit that simulates a water absorption state of the water absorbent molding under the first environmental condition until the water absorption state of the water absorbent molding under the first environmental condition becomes a predetermined first state; The identifying unit identifies a second environmental condition that results in an equilibrium water absorption rate closest to the equilibrium water absorption rate under the designated environmental condition, The calculation unit simulates a water absorption state of the water absorbent molding under the second environmental condition starting from the first state. The environmental condition prediction system according to claim 5 .

10. a learning unit that learns a diffusion coefficient prediction model that predicts the diffusion coefficient of water in the water-absorbent molding under predetermined environmental conditions from at least material information of the water-absorbent molding; The environmental condition prediction system of claim 1 .

11. a learning unit that learns an equilibrium water absorption prediction model for predicting an equilibrium water absorption rate of the water-absorbent molding under predetermined environmental conditions from material information of the water-absorbent molding; The environmental condition prediction system of claim 1 .

12. a learning unit that learns a material property prediction model for predicting material properties of the water-absorbent molding from material information of the water-absorbent molding, a water absorption state of the water-absorbent molding, and the specified environmental conditions; The environmental condition prediction system according to claim 4 .

13. The water-absorbent molding further includes a material property prediction unit that predicts the material property of the water-absorbent molding using the material property prediction model. The environmental condition prediction system of claim 12.

14. The material characteristics include at least one of mechanical properties and dimensional change of the water-absorbent molding; The environmental condition prediction system of claim 12.

15. The method is executed by a computer, causing the computer to: The system functions as the environmental condition prediction system according to any one of claims 1 to 14. program.

16. The environmental condition prediction system according to any one of claims 1 to 14, A step of identifying an environmental condition under which the water-absorbent molding has a predetermined water absorption rate based on shape information relating to the shape of the water-absorbent molding, a water diffusion coefficient in the water-absorbent molding, and an equilibrium water absorption rate of the water-absorbent molding; The method for predicting environmental conditions is as follows:

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