WO2022196209A1 - 物性マップ画像生成装置、制御方法、及び非一時的なコンピュータ可読媒体 - Google Patents

物性マップ画像生成装置、制御方法、及び非一時的なコンピュータ可読媒体 Download PDF

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WO2022196209A1
WO2022196209A1 PCT/JP2022/005626 JP2022005626W WO2022196209A1 WO 2022196209 A1 WO2022196209 A1 WO 2022196209A1 JP 2022005626 W JP2022005626 W JP 2022005626W WO 2022196209 A1 WO2022196209 A1 WO 2022196209A1
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Prior art keywords
physical property
node
map image
assigned
map
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Ceased
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PCT/JP2022/005626
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English (en)
French (fr)
Japanese (ja)
Inventor
直樹 鍬守
昭裕 撫佐
陽平 瀧川
悠加 風間
佳彦 佐藤
広明 小林
豪太 菊川
朋永 岡部
一彦 小松
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tohoku University NUC
NEC Corp
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Tohoku University NUC
NEC Corp
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Application filed by Tohoku University NUC, NEC Corp filed Critical Tohoku University NUC
Priority to EP22770968.0A priority Critical patent/EP4310715A4/en
Priority to US18/282,381 priority patent/US20240161354A1/en
Priority to CN202280022362.3A priority patent/CN117043780A/zh
Priority to JP2023506876A priority patent/JP7598108B2/ja
Publication of WO2022196209A1 publication Critical patent/WO2022196209A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—Two-dimensional [2D] image generation
    • G06T11/10—Texturing; Colouring; Generation of textures or colours
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/10—Numerical modelling
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/26—Composites

Definitions

  • Patent Literature 1 discloses a system that uses a self-organizing map to support understanding of causal relationships between design values and physical property values of tires.
  • the non-transitory computer-readable medium of the present disclosure stores a program that causes a computer to execute the control method of the present disclosure.
  • FIG. 1 is a diagram illustrating an overview of the operation of the physical property map image generation device 2000 of Embodiment 1.
  • FIG. 1 is a diagram for facilitating understanding of the outline of the physical property map image generation device 2000, and the operation of the physical property map image generation device 2000 is not limited to that shown in FIG.
  • the physical property map image generation device 2000 generates the physical property map image 40 for the deliverable 70 that can be generated in a specific process of product development (hereinafter referred to as the target process).
  • the physical property map image 40 is an image expressing the physical property distribution of the product 70 with a color distribution, focusing on two or three specific physical properties.
  • the material identification information 10 is used, for example, to include an indication of the material identification information 10 in the physical property map image 40 .
  • the physical property map image 40 may not include this display. Therefore, if the material identification information 10 is not used, the physical property map image generation device 2000 does not need to acquire the material identification information 10 .
  • the physical property map image generation device 2000 uses the physical property information 20 to generate a self-organizing map 30 representing the physical property distribution of the product 70 .
  • the self-organizing map 30 has a plurality of nodes arranged on an m-dimensional map space.
  • m is set to 2 or 3 so that the physical property map image 40 can be generated from the self-organizing map 30 .
  • a node can be expressed as a square of squares, a grid on a grid, or the like.
  • the physical property information 20 indicates physical property amounts for n or more types of physical properties.
  • the physical property map image generation device 2000 learns the self-organizing map 30 using the physical property amounts of the n types of physical properties indicated by the physical property information 20, thereby determining the physical property vector to be assigned to each node. to generate a self-organizing map 30 .
  • the physical property map image generation device 2000 assigns a color to each node of the self-organizing map 30, and generates the physical property map image 40 as an image in which each node is represented by the assigned color.
  • the physical property map image generation device 2000 assigns colors to nodes by focusing on two or three types of physical properties. More specifically, the physical property map image generation device 2000 determines the color to be assigned to each node according to the values corresponding to specific two or three physical properties among the values indicated by the physical property vector of the node.
  • a color assigned to a node is hereinafter referred to as a node assigned color.
  • first physical property and the second physical property For example, let's focus on two types of physical properties in order to determine the assigned colors.
  • these two physical properties are called the first physical property and the second physical property, respectively.
  • the reference colors associated with the first physical property and the second physical property are called the first reference color and the second reference color, respectively.
  • the physical property map image generation device 2000 determines the magnitude of the component of the first reference color in the assigned color of the node based on the value indicated by the physical property vector of the node for the first physical property.
  • the physical property map image generation device 2000 also determines the magnitude of the second reference color component in the assigned color of the node based on the value of the second physical property indicated by the physical property vector of the node.
  • the physical property map image generation device 2000 determines the magnitude of the third reference color component in the assigned color of the node based on the value of the third physical property indicated by the physical property vector of the node.
  • the first physical property is flame retardancy and the second physical property is heat resistance. It is also assumed that red is used as the first reference color and green is used as the second reference color.
  • the physical property map image generation device 2000 determines the magnitude of the red component in the assigned color of the node based on the flame resistance value indicated by the physical property vector of the node. Also, the physical property map image generation device 2000 determines the magnitude of the green component in the assigned color of the node based on the value of heat resistance indicated by the physical property vector of the node. In this example, a fixed value (for example, 0) is used for the magnitude of the blue component in the allocated color.
  • the third physical property When generating the physical property map image 40 focusing on three physical properties, one more physical property is used. This physical property is called the third physical property.
  • a reference color corresponding to the third physical property is called a third reference color.
  • the magnitude of the component of the third reference color in the assigned color of the node is determined based on the value of the third physical property indicated by the physical property vector. For example, the three primary colors of light, red, green, and blue, are used for the first to third reference colors, respectively.
  • the physical property map image 40 provided by the physical property map image generation device 2000 visually expresses the physical property distribution of the product 70, and is useful for the above-described inverse analysis. Specifically, in the physical property map image 40 , the color of each node is determined by focusing on two or three physical properties among the plurality of physical properties of the product 70 . Therefore, from the color distribution in the physical property information 20, it is possible to intuitively grasp the physical property distribution of the product 70 focusing on these two or three physical properties.
  • the physical property map image 40 there is a node with a color that satisfies the condition that "any reference color component is sufficiently large". For example, if the reference colors are red, green, and blue, it can be said that a color close to white satisfies this condition. It can be said that such a node represents a product 70 that exhibits good physical property quantities for any of the two or three physical properties focused on for determining the color assigned to the node. Therefore, by using the physical property map image 40, it can be easily understood that the product 70 having desired physical properties can be generated.
  • one possible method of selecting physical properties to focus on in order to determine the color to be assigned to a node is to select two or three physical properties that have a trade-off relationship. By making such a selection, it can be understood that it is possible to generate a product 70 having good properties with respect to any of the two or three physical properties that should be in a trade-off relationship. .
  • the physical property map image generation device 2000 of this embodiment will be described in more detail below.
  • each reference color component in the node's assigned color is determined based on the value that the node's physical property vector indicates for the first physical property. Also, the magnitude of the second reference color component in the assigned color of the node is determined based on the value of the second physical property indicated by the physical property vector of the node.
  • the processor 504 is various processors such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), or FPGA (Field-Programmable Gate Array).
  • the memory 506 is a main memory implemented using a RAM (Random Access Memory) or the like.
  • the storage device 508 is an auxiliary storage device implemented using a hard disk, SSD (Solid State Drive), memory card, ROM (Read Only Memory), or the like.
  • the input/output interface 510 is an interface for connecting the computer 500 and input/output devices.
  • the input/output interface 510 is connected to an input device such as a keyboard and an output device such as a display device.
  • a network interface 512 is an interface for connecting the computer 500 to a network.
  • This network may be a LAN (Local Area Network) or a WAN (Wide Area Network).
  • the storage device 508 stores a program for realizing each functional component of the physical property map image generation device 2000 (a program for realizing the application described above).
  • the processor 504 implements each functional component of the physical property map image generation device 2000 by reading this program into the memory 506 and executing it.
  • the physical property map image generation device 2000 may be realized by one computer 500 or may be realized by a plurality of computers 500. In the latter case, the configuration of each computer 500 need not be the same, and can be different.
  • FIG. 4 is a flowchart illustrating the flow of processing executed by the physical property map image generation device 2000 of the first embodiment.
  • the acquisition unit 2020 acquires the material identification information 10 and the physical property information 20 for each of the plurality of materials 60 that can be used in the target process (S102).
  • the self-organizing map generator 2040 uses the physical property information 20 to generate the self-organizing map 30 (S104).
  • the self-organizing map generator 2040 generates the physical property map image 40 from the self-organizing map 30 (S106).
  • the acquisition unit 2020 acquires the material identification information 10 of each of the plurality of patterns of materials 60 that can be used in the target process, and the physical property information 20 of the deliverables 70 that can be generated using the materials 60 ( S102).
  • one pattern of material 60 is specified by material specifications. Therefore, the material identification information 10 can be said to be identification information assigned to specific material specifications.
  • FIG. 5 is a diagram illustrating correspondence between material identification information and specifications in a table format.
  • the table 100 of FIG. 5 has columns of material identification information 102 and material specifications 104 .
  • Material identification information 102 indicates identification information assigned to material 60 (ie, material identification information 10).
  • a material specification 104 indicates the specification of the material 60 .
  • the acquisition unit 2020 acquires multiple pairs of material identification information 10 and physical property information 20 .
  • a pair of material identification information 10 and physical property information 20 is stored in advance in an arbitrary storage device accessible from the physical property map image generation device 2000 .
  • the acquisition unit 2020 acquires a pair of the material identification information 10 and the physical property information 20 by accessing this storage device.
  • the acquisition unit 2020 may acquire a pair of the material identification information 10 and the physical property information 20 by accepting user input for inputting the pair of the material identification information 10 and the physical property information 20 .
  • the acquisition unit 2020 may acquire a pair of material identification information 10 and physical property information 20 by receiving a pair of material identification information 10 and physical property information 20 transmitted from another device.
  • the pair of material identification information 10 and physical property information 20 is generated by simulating the generation of the product 70 . Specifically, by giving specific material specifications as input and executing a simulation, the physical property information 20 indicating the predicted value of the physical quantity of each physical property is generated for the product 70 . Then, correspondence between the generated physical property information 20 and the material identification information 10 assigned to the material specifications given as input is obtained.
  • a technology that realizes a simulation that acquires material specifications as input and outputs predictive data on the physical properties of deliverables that are produced in specific processes using the materials specified by the material specifications. can use existing technology.
  • the pair of material identification information 10 and physical property information 20 may be generated by actually generating the deliverable 70.
  • the product 70 is experimentally generated by using the material 60 represented by specific material specifications in the target process.
  • the physical property information 20 is generated by measuring the physical quantity of each physical property of the generated product 70 . As a result, correspondence between the generated physical property information 20 and the material identification information 10 assigned to the material 60 used is obtained.
  • the physical property information 20 acquired by the acquisition unit 2020 may include information with different data representation methods. For example, different labels may be used for essentially identical physical properties. In addition, it is conceivable that the physical quantity of the same physical property is expressed in units different from each other. In such a case, the acquisition unit 2020 preferably unifies the data expression method by unifying labels, converting units, and the like. Such a situation in which the physical property information 20 has different data representation methods is, for example, the physical property information 20 generated using a simulation and the physical property information 20 generated by actually generating the product 70. It is considered possible when both are acquired.
  • the self-organizing map generator 2040 uses the material identification information 10 and the physical property information 20 to generate the self-organizing map 30 (S104).
  • Each node of the self-organizing map 30 is assigned an n-dimensional physical property vector.
  • the physical property vector obtained from the physical property information 20 may indicate the physical property amount of each of the n types of physical properties indicated by the physical property information 20 as it is, or each physical property amount may be converted by a predetermined method (for example, normalization, standardization, etc.). You may indicate the value obtained by
  • FIG. 7 is a flowchart illustrating the flow of processing for assigning colors to nodes.
  • S202 to S212 constitute loop processing L1.
  • Loop processing L1 is executed once for each node included in self-organizing map 30 .
  • the physical property map image generation unit 2060 determines whether or not the loop processing L1 has been executed for all nodes. If the loop process L1 has already been executed for all nodes, the process of FIG. 7 ends. On the other hand, if there are nodes that have not yet been subjected to the loop processing L1, the physical property map image generator 2060 selects one node from among them. The node selected here is denoted as node i.
  • the physical property map image generator 2060 determines the magnitude of the j-th reference color component in the assigned color of the node i based on the value of the j-th physical property indicated by the physical property vector of the node i.
  • the magnitude of the j-th reference color component in the assigned color of the node i is the numerical range of values indicated by the physical property vector of the self-organizing map 30 for the j-th physical property and the numerical range of the magnitude of each reference color component. It is calculated by a conversion formula determined based on and. This conversion formula is represented, for example, by the following formula (1).
  • c[i,j] represents the magnitude of the j-th reference color component in the assigned color of node i.
  • x[i,j] is the value that the physical property vector of node i indicates for the j-th physical property.
  • f() represents a conversion formula.
  • W[j] represents the size of the numerical range of the value indicated by the physical property vector of the self-organizing map 30 for the j-th physical property.
  • C represents the magnitude of the numerical range of each reference color component.
  • the larger the value that the physical property vector indicates for the j-th physical property the larger the j-th reference color component.
  • the magnitude of the jth reference color component is monotonically increasing with respect to the value that the physical property vector indicates for the jth physical property.
  • the magnitude of the j-th reference color component does not necessarily have to monotonically increase with respect to the value indicated by the physical property vector for the j-th physical property.
  • the more appropriate the value indicated by the physical property vector for the j-th physical property the larger the magnitude of the j-th reference color component.
  • the physical property map image generation unit 2060 assigns a larger value to the j-th reference color component as the value indicated by the physical property vector for the j-th physical property increases. set.
  • the physical property map image generation unit 2060 generates a larger value for the component of the j-th reference color as the value indicated by the physical property vector for the j-th physical property decreases. set.
  • the physical property map image generation unit 2060 assigns a larger value to the j-th reference color component as the value indicated by the physical property vector for the j-th physical property is closer to the ideal value. set.
  • S208 is the end of loop processing L2. Therefore, the processing in FIG. 7 proceeds to S204.
  • the degree of similarity between n-dimensional data is specified, for example, based on their distance.
  • the physical property map image generator 2060 calculates the distance between the physical property vector of each node and the physical property vector obtained from the physical property information 20 corresponding to the material identification information 10 . Then, the physical property map image generator 2060 assigns the material identification information 10 to the node for which the minimum distance has been calculated.
  • FIG. 8 is a diagram exemplifying the configuration of the self-organizing map 30 in which the colors and the material identification information 10 are assigned, in a table format.
  • the table 300 of FIG. 8 has four columns: location 302 , physical property vector 304 , assigned color 306 and material identification information 308 .
  • Table 300 has one record per node.
  • the position 302 indicates the coordinates of the node on the m-dimensional map space.
  • m 2 and the nodes are assigned x and y coordinates.
  • a physical property vector 304 represents an n-dimensional physical property vector assigned to a node.
  • n 4.
  • Assigned color 306 represents the assigned color of the node.
  • three reference colors, red, green, and blue, define assigned colors.
  • Material identification information 308 represents the material identification information 10 assigned to the node. Here, in the record of the node to which the material identification information 10 is not assigned, the material identification information 308 indicates "-".
  • the physical property map image generation unit 2060 generates the physical property map image 40 based on the table 300. Specifically, the physical property map image generation unit 2060 generates the physical property map image 40 by expressing each node arranged on the map space with the assigned color of the node.
  • the physical property map image 40 is an image including squares in which each square is represented (for example, filled) with the assigned color of the node corresponding to the square.
  • the physical property map image generation unit 2060 includes in the physical property map image 40 a display that allows understanding of the assignment of the material identification information 10 to the nodes (in other words, a display showing the correspondence between the material identification information 10 and the nodes).
  • the colors of the nodes are expressed using diagonal lines.
  • the first reference color is represented by a diagonal line connecting the upper right and the lower left (hereinafter referred to as the first diagonal line).
  • the second reference color is represented by a diagonal line connecting the upper left and the lower right (hereinafter referred to as the second diagonal line).
  • the greater the reference color component the higher the density of the oblique lines.
  • a node with a high density of the first diagonal line but a low density of the second diagonal line (that is, a node with a large component of the first reference color but a small component of the second reference color) is preferable for the first physical property but has the second physical property. represents an undesirable artifact 70 .
  • the density of the first diagonal line is low but the density of the second diagonal line is high (that is, the node whose first reference color component is small but whose second reference color component is large) is not preferable for the first physical property, A preferred artifact 70 is represented for the second physical property.
  • a node where both the density of the first diagonal line and the density of the second diagonal line are high (that is, the node where both the first reference color component and the second reference color component are large) has both the first physical property and the second physical property.
  • a preferred deliverable 70 is represented.
  • a display 42 representing the material identification information 10 assigned to that node is shown.
  • the display 42 includes a circle for identifying the node of interest and the value indicated by the material identification information 10 assigned to the node (ie, identification information of the material 60).
  • the node of interest is the node containing the circle inside.
  • the physical property map image 40 in FIG. 9 is useful, for example, in identifying material specifications that can produce a desired product 70 with respect to both the first physical property and the second physical property.
  • nodes with large first and second reference color components represent favorable artifacts 70 for both the first and second physical properties. Therefore, for example, among the nodes to which the material identification information 10 is assigned, a node close to the node having both large first reference color component and second reference color component is specified.
  • the material specification of the material 60 specified by the material identification information 10 associated with this node is considered to be close to the material specification capable of generating the desired product 70 with respect to both the first physical property and the second physical property. .
  • a node with a high density of both the first diagonal line and the second diagonal line is to the right of the node to which the material identification information 10 indicating "A101" is assigned, and the material identification information indicating "A102". It exists under the node to which information 10 is assigned. Therefore, the developers, etc., performed simulations with various material specifications within a range close to both the material specifications identified by "A101" and the material specifications identified by "A102". It is possible to find in a short period of time material specifications that can produce desirable products 70 for both the first physical property and the second physical property.
  • the physical property map image generation unit 2060 displays a display that makes it easy to specify the material specifications that are used as the reference for the search described above (in the example of FIG. 9, a display that makes it easy to specify “A101” and “A102”), It may be included in the physical property map image 40 .
  • the physical property map image generation unit 2060 identifies a node having an assigned color in which the size of each reference color component is equal to or greater than a threshold value, and emphasizes the node by thickening the frame of the node.
  • the physical property map image generation unit 2060 identifies a node whose distance from the node identified in this way is equal to or less than a threshold and to which the material identification information 10 is assigned, and A representation 42 shown in a node may be emphasized over another representation 42 (eg, by using a non-white circle or a thicker frame).
  • node placement may be expressed using a grid.
  • a region within a predetermined range around each grid point (for example, a circle with a predetermined radius around the grid point) is represented by the assigned color of the node corresponding to the grid point. image of the grid.
  • (Appendix 1) Acquisition means for acquiring, for each of a plurality of patterns of materials that can be used in a target process, physical property information indicating physical property amounts for each of a plurality of physical properties of a product that can be produced in the process using the material; Using the physical property information, a self-organizing map is generated in which each node is assigned a position on the map space and a physical property vector indicating a value related to each physical property quantity of n kinds of physical properties of the product.
  • a transformation map generating means for generating a physical property map image in which each of the nodes arranged on the map space is represented by the color assigned to the node; For each of two or three reference colors, the physical property map image generating means converts the reference color component in the color assigned to each node into a physical property corresponding to the reference color in the physical property vector assigned to the node.
  • a physical property map image generator that determines based on the values indicated for.
  • the acquisition means acquires identification information of the material corresponding to the physical property information
  • the physical property map image generating means identifies, from the nodes, the node to which the physical property vector most similar to the physical property vector obtained from the physical property information is assigned, and the identification information corresponding to the physical property information.
  • the physical property map image generating device according to appendix 1, wherein the physical property map image includes an indication representing a correspondence relationship between the node and the specified node.
  • the physical property map image generating means preferably determines that the size of each reference color component in the color assigned to each node is a value indicating the physical property corresponding to the reference color by the physical property vector assigned to the node.
  • the physical property map image generation device according to appendix 1 or 2, wherein the value is moderately large.
  • the physical property map image generating means identifies the node to which a color having a magnitude of each reference color component greater than or equal to a threshold value is assigned, and highlights the identified node in the physical property map image. 3.
  • the physical property map image generation device according to .
  • the self-organizing map generation means generates the self-organizing map by learning the self-organizing map using the physical property vector obtained from the physical property information as training data. 1.
  • the physical property map image generation device according to claim 1.
  • a control method implemented by a computer comprising: an acquisition step of acquiring physical property information indicating physical property amounts for each of a plurality of physical properties of a product that can be produced in the process using the material for each of a plurality of patterns of materials that can be used in a target process; Using the physical property information, a self-organizing map is generated in which each node is assigned a position on the map space and a physical property vector indicating a physical property amount of each of a plurality of types of physical properties of the product.
  • a transformation map generation step a physical property map image generating step of generating a physical property map image in which each of the nodes arranged on the map space is represented by the color assigned to the node;
  • the component of the reference color in the color assigned to each node is represented by the physical property vector assigned to the node corresponding to the reference color.
  • the control method determined based on the value indicated for .
  • (Appendix 14) In the acquiring step, acquiring identification information of the material corresponding to the physical property information; In the physical property map image generating step, the node to which the physical property vector most similar to the physical property vector obtained from the physical property information is assigned is specified from the nodes, and the identification information corresponding to the physical property information. 14. The non-transitory computer-readable medium according to appendix 13, wherein the physical property map image includes an indication representing a correspondence relationship between and the identified node. (Appendix 15) In the physical property map image generating step, it is more appropriate that the magnitude of each reference color component in the color assigned to each node is indicated by the physical property vector assigned to the node with respect to the physical property corresponding to the reference color. 15.
  • material identification information 20 physical property information 30 self-organizing map 40 physical property map image 42 display 60 material 70 deliverable 100 table 102 material identification information 104 material specification 300 table 302 position 304 physical property vector 306 assigned color 308 material identification information 500 computer 502 bus 504 processor 506 memory 508 storage device 510 input/output interface 512 network interface 2000 physical property map image generation device 2020 acquisition unit 2040 self-organizing map generation unit 2060 physical property map image generation unit

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PCT/JP2022/005626 2021-03-18 2022-02-14 物性マップ画像生成装置、制御方法、及び非一時的なコンピュータ可読媒体 Ceased WO2022196209A1 (ja)

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EP22770968.0A EP4310715A4 (en) 2021-03-18 2022-02-14 Physical property map image generation device, control method, and non-transitory computer readable medium
US18/282,381 US20240161354A1 (en) 2021-03-18 2022-02-14 Physical property map image generation apparatus, control method, and non-transitory computer readable medium
CN202280022362.3A CN117043780A (zh) 2021-03-18 2022-02-14 物理性质映射图像生成设备、控制方法和非暂时性计算机可读介质
JP2023506876A JP7598108B2 (ja) 2021-03-18 2022-02-14 物性マップ画像生成装置、制御方法、及びプログラム

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