JP2022134806A - Display program, display method, and information processing device - Google Patents

Abstract

To make it possible to easily select a surface in an analysis model expressed by a point group.SOLUTION: A display program causes a computer to execute processing of: displaying a model 101 including a point group; specifying a first plurality of points among the point group in accordance with a first input 102; generating a plurality of surfaces 104 to 106 corresponding to a surface of the model 101 based on the first plurality of points; and causing a second plurality of points 108 to be a selected state that are in a distance of a threshold value or less from the first surface 104 included in the plurality of surfaces 104 to 106 among the first plurality of points in accordance with a second input.SELECTED DRAWING: Figure 1

Description

The present invention relates to a display program, a display method, and an information processing apparatus.

In numerical simulations of physical phenomena, software called analysis pre-post displays an analysis model to be analyzed on a computer screen, sets calculation conditions, and visualizes calculation results.

Physical simulation based on an analytical model using a particle method is known as one of numerical simulation techniques. The particle method is a method of representing an object as a point group, for example, discretely arranged point information (particles).

In physics simulation, software running on a server applies weights or Calculation is performed by giving calculation conditions such as temperature.

JP 2011-123835 A JP 2017-151601 A

In a technique such as the finite volume method or the finite element method, in which an object is expressed by dividing it into geometric elements such as hexahedrons or tetrahedrons, the surface of the object is expressed by planes. For example, in a simulation using the finite volume method or the finite element method, the user selects (picks) the surface to be analyzed on the software with a mouse, and the surface of the analysis model represented by polygons is displayed. Conditions can be easily given.

On the other hand, in simulations using the particle method, an analytical model of an object is represented by a collection (point group) of particles (points). For this reason, it may be difficult for the user to select only particles in a specific region corresponding to the surface to be analyzed among the particles representing the analysis model using a mouse or the like.

For example, when selecting the surface of a particle corresponding to the surface to be analyzed on software with a mouse, not only the surface of the particle but also the particles inside the object included in the selected rectangular area may be selected.

In addition, for example, in order to prevent the particles inside the object from being selected, the user can select a plurality of particles at positions corresponding to the surface to be analyzed by visually discriminating the boundaries by clicking a mouse or the like. is also conceivable. However, if the user selects particles on the surface one by one, as the number of particles representing the object increases, the effort increases and the possibility of selection errors increases.

As described above, in an analysis model represented by a point group, it may be difficult to select a plane that provides calculation conditions.

One of the objects of the present invention is to make it possible to easily select a plane in an analysis model represented by a point group.

In one aspect, the display program may cause the computer to perform the following processes. The processing may include displaying a model including the point cloud. The processing may also include identifying a first plurality of points of the point cloud in response to a first input. Further, the processing may include generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points. In addition, the processing may include, in response to a second input, determining a second plurality of points, among the first plurality of points, that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes. It may include a process to put it in a selected state.

In one aspect, the present invention can easily select faces in an analytical model represented by a point cloud.

FIG. 4 is a diagram for briefly explaining an example of processing by a server according to an embodiment; FIG. It is a block diagram showing an example of functional composition of a system concerning one embodiment. FIG. 5 is a diagram showing a display example of an analysis model displayed on a screen; It is a figure which shows an example of particle information. FIG. 10 is a diagram for explaining an example of range selection processing for the display area of the analysis model; It is a figure which shows an example of the production|generation process of selected particle information. FIG. 10 is a diagram for explaining an example of surface generation processing; It is a figure which shows an example of vertex information. It is a figure which shows an example of surface information. It is a figure which shows an example of a unit surface. FIG. 10 is a diagram for explaining an example of surface generation processing by the marching cubes method; FIG. 10 is a diagram illustrating an example of surface data model generation processing; It is a figure for demonstrating an example of grouping processing. It is a figure for demonstrating an example of a group determination process. It is a figure for demonstrating an example of a group determination process. FIG. 10 is a diagram illustrating an example of processing for generating group plane information; It is a figure for demonstrating an example of a particle|grain search process. It is a figure which shows an example of the calculation process of the distance d. It is a figure which shows an example of the production|generation process of surface particle information. FIG. 10 is a diagram showing an example of original data and an analysis model (particle model) according to an application example; 21 is a diagram showing an example of a rectangular area for selecting part of the analytical model shown in FIG. 20; FIG. FIG. 10 is a diagram showing an example of a surface generated based on particles within a rectangular area according to an application example; FIG. 10 is a diagram showing an example of a group surface according to an application example; FIG. 24 is a diagram showing an example of surface particles extracted when the surface A shown in FIG. 23 is specified; FIG. 10 is a diagram showing an example of a selection state of surface particles according to an application example; 9 is a flowchart for explaining an operation example of selection processing by a server according to one embodiment; FIG. 2 is a block diagram showing a hardware (HW) configuration example of a computer that implements the functions of a server;

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the embodiments described below are merely examples, and are not intended to exclude various modifications or application of techniques not explicitly described below. For example, this embodiment can be modified in various ways without departing from the spirit of the embodiment. In the drawings used in the following description, parts with the same reference numerals represent the same or similar parts unless otherwise specified.

[1] One Embodiment [1-1] About One Embodiment FIG. 1 is a diagram for simply explaining an example of processing by a server according to one embodiment. As illustrated in FIG. 1, a server according to one embodiment may perform the following processes (a) to (d).

(a) The server displays the model containing the point cloud.
For example, the server displays the model 101 on the screen of a display device such as a monitor, as indicated by arrow (a). In the example of FIG. 1, the model 101 may be a three-dimensional model represented by a point group using the particle method, and as an example, may be an analytical model used for numerical simulation. A point group may mean, for example, a combination of a plurality of particles (particle group).

(b) the server identifies a first plurality of points of the point cloud in response to the first input;
For example, as indicated by an arrow (b), the server selects a rectangular region 102 input from an input device such as a mouse (rectangular selection) to select a point cloud representing the model 101 on the screen. A plurality of points included in (surrounded by) the rectangular area 102 may be identified. The specification of the rectangular area 102 is an example of a first input, and the plurality of points included in the rectangular area 102 is an example of the first plurality of points.

(c) The server may generate a plurality of surfaces corresponding to the surface of the model based on the first plurality of points.
For example, as indicated by an arrow (c), the server provides a plurality of points corresponding to the surface of the partial model 103, which is part of the model 101 and which is represented by a plurality of points included in the rectangular area 102. Surfaces 104, 105, 106 may be generated. In the example of FIG. 1, surfaces 104, 105, and 106 are denoted as surfaces A, B, and C, respectively. In addition, although the surfaces 104 to 106 are shown separated from the partial model 103 in arrow (c) for convenience, each of the surfaces 104 to 106 is formed by a group of particles existing on the surface of the partial model 103. Therefore, it may be superimposed on the partial model 103 and displayed.

(d) the server selects, in response to a second input, a second plurality of points that are at a distance equal to or less than a threshold from the first plane included in the plurality of planes, among the first plurality of points; can be
For example, the server may accept designation A (surface selection) of surface A input from an input device such as a mouse, as indicated by an arrow (d-1). The surface A that is the target of designation A is an example of a first surface.

Arrow (d-2) is a view of a part of surface A, which is the target of designation A, viewed from the plane direction of surface A, in other words, a surface that intersects surface A and is perpendicular or substantially perpendicular to surface A. 3 is a diagram showing (the cross section of the partial model 103). FIG. The server may select a plurality of points 108 of the particles 107 representing the partial model 103 that are less than or equal to a threshold distance from the surface A, as indicated by arrows (d-2). Plurality of points 108 is an example of a second plurality of points.

The server may display a plurality of selected points 108 as a selected state 109 in the model 101 displayed on the screen of a display device such as a monitor, as indicated by an arrow (d-3). A plurality of points 108 in the selection state 109 may be treated as elements of a surface to which calculation conditions are given in a simulation using the particle method, for example.

Thus, according to the server according to one embodiment, it is possible to easily select a surface for giving conditions such as calculation conditions in the model 101 represented by a point group.

Further, according to the server, the surfaces A, B, and C are generated by restricting the plurality of particles included in the rectangular-selected partial model 103, and the surfaces A, B, and C selected by the surface selection correspond to the surfaces A, B, and C. A plurality of points 108 can be in a selected state 109 . As a result, since the number of particles to be processed can be limited, the processing load on the server can be reduced, and the surface (plurality of points 108) can be selected by the processes (a) to (d) above at high speed. .

[1-2] Functional Configuration Example FIG. 2 is a block diagram showing a functional configuration example of the system 1 according to one embodiment. A system 1 is an example of an information processing system that performs a simulation based on an analysis model, and may include a server 2 and a terminal device 3, as shown in FIG. A configuration in which the system 1 does not include the terminal device 3 may be allowed.

The server 2 is an example of a computer or an information processing device, and may be, for example, a server that executes analysis software (analysis pre-post) for performing simulations such as numerical simulations.

As shown in FIG. 2, the server 2 includes, for example, a memory unit 21, an input control unit 22, a display control unit 23, a selected particle acquisition unit 24, a surface generation unit 25, a grouping processing unit 26, and a particle search unit. A portion 27 may be provided.

The memory unit 21 is an example of a storage area, and stores various data used by the server 2 . As shown in FIG. 2, the memory unit 21 can store, for example, particle information 21a, selected particle information 21b, vertex information 21c, plane information 21d, group plane information 21e, and surface particle information 21f. you can Hereinafter, for the sake of convenience, each of these pieces of information 21a to 21f is represented in a table format, but is not limited to this. It may be stored in the memory unit 21 in various formats.

The input control unit 22 controls input of various information to the server 2 . As an example, the input control unit 22 may receive model information of the analysis model and various operation information (for example, selection information) regarding selection of a surface to be analyzed for the analysis model. “Accepting” the model information and the operation information may include, for example, outputting the acquired model information and operation information to at least one of the other blocks 21, 23-27. For example, the input control unit 22 may acquire particle information 21 a as an example of model information and store it in the memory unit 21 .

The model information and operation information may be input via various devices such as an input device, a communication device, or a reading device provided in the server 2, for example. Note that the terminal device 3 may transmit operation information input by a user by operating an input device provided in the terminal device 3 to the server 2 via a network (not shown). In this case, the communication device provided in the server 2 may receive the operation information from the terminal device 3 via the network.

The display control unit 23 controls various screen displays in the server 2 . As an example, the display control unit 23 may perform display control of the analysis model based on information or instructions input from at least one of the blocks 21, 22, 24 to 27, such as operation information or control information. .

For example, the display control unit 23 may generate display information (screen information) of the analysis model based on input information or instructions, and output the display information to a display device provided in the server 2, or via a network. may be output (transmitted) to the terminal device 3. The terminal device 3 may output the display information received from the display control unit 23 to a display device provided in the terminal device 3 .

FIG. 3 is a diagram showing a display example of the analysis model 11 displayed on the screen. The example in FIG. 3 shows an analysis model 11 that expresses a rectangular parallelepiped shape with particles. Upon acquiring the model information, the display control unit 23 may generate display information for visualizing all particles of the analytical model 11 on the display device based on the model information.

The analysis model 11 according to one embodiment shall be expressed using the particle method. For example, the display control unit 23 may generate the display information of the analytical model 11 based on the particle information 21 a acquired by the input control unit 22 and stored in the memory unit 21 . The particle information 21a is an example of model information.

FIG. 4 is a diagram showing an example of the particle information 21a. As illustrated in FIG. 4 , the particle information 21a may include particle data 211 for each particle P expressing the analysis model 11 . In the example of FIG. 4, the particle information 21a has n particle data 211 of particles P ₁ to P _n . n is an integer representing the number of particles representing the analytical model 11 .

As illustrated in FIG. 4 , the particle data 211 may include at least the identification number “id” of the particle P and the position information “x, y, z” of the particle P. In the example of FIG. 4, the subscripts “1” to “n” of the particles P ₁ to P _n are examples of identification numbers of the particles P ₁ to P _n , respectively. The position information may be, for example, coordinate information in the three-dimensional space in which the analytical model 11 is displayed. Note that the particle data 211 may include various information belonging to the particle P in addition to the identification number and position information.

The selected particle acquisition unit 24 acquires, from the input control unit 22, operation information indicating the extraction range of the surface particles of the analysis model 11 selected by the user using the input device (for example, rectangular selection), and determines the particles P included in the extraction range. to select. The extraction range is the range of particles P near the surface that the user wants to extract from the analysis model 11, and is an example of a predetermined area range. The selected particle acquisition unit 24 may store, for example, information on the particles P included in the extraction range in the memory unit 21 as the selected particle information 21b.

As a method of selecting the extraction range by the input device, for example, selection by a rectangle, circle, ellipse, free shape, or other various shapes for the display area of the analysis model 11 by a mouse or a touch panel, selection of a coordinate range by a keyboard, etc. various methods such as input.

FIG. 5 is a diagram for explaining an example of range selection processing for the display area of the analysis model 11. As shown in FIG. For example, the selected particle acquisition unit 24 selects the rectangular area 12 on the screen from among the n particles P representing the analytical model 11 in accordance with the designation (rectangular selection) of the rectangular area 12 input from the input device. The m particles P that are included (surrounded) may be identified. m is an integer less than or equal to n that indicates the number of particles included (surrounded) in the rectangular area 12 in the analytical model 11 . As exemplified in FIG. 5 , a model obtained by cutting out the analytical model 11 in a rectangular area 12 is referred to as a partial model 13 . The partial model 13 shown in FIG. 5 shows a state in which only the extracted m particles P out of the n particles P of the analysis model 11 are displayed.

FIG. 6 is a diagram showing an example of processing for generating the selected particle information 21b. For example, the selected particle acquisition unit 24 selects particles within the range of the rectangular area 12 based on the coordinate information indicating the range of the rectangular area 12 included in the operation information and the coordinate information of each of the n particles P included in the particle information 21a. may be extracted from the particle information 21a. Then, the selected particle obtaining unit 24 may store the extracted particles P in the selected particle information 21b.

In the example of FIG. ₆ , the selected particle acquisition unit 24 _{extracts m} particles _{P 2} , P ₄ , P ₉ , . to generate the selected particle information 21b. Each particle data 211 included in the selected particle information 21b may be the same as the particle data 211 of the particle information 21a shown in FIG.

The plane generation unit 25 generates a plane by extracting the particles P on the surface of the analytical model 11 , for example, the partial model 13 , for the particles P in the rectangular region 12 .

FIG. 7 is a diagram for explaining an example of surface generation processing. As illustrated in FIG. 7, the surface generator 25 may generate a grid 131 surrounding m particles P included in the partial model 13, and generate a surface 132 at a location corresponding to the surface position of the grid 131. . For example, the surface generation unit 25 may generate vertex information 21 c and surface information 21 d as information indicating the surface 132 and store them in the memory unit 21 . Note that the surface 132 may be regarded as the surface of the partial model 13 .

FIG. 8 is a diagram showing an example of the vertex information 21c. As illustrated in FIG. 8, the vertex information 21c may include vertex data 212 of a plurality of unit faces included in the face 132 (for example, forming the face 132). In the example of FIG. 8, the vertex information 21c has t pieces of vertex data 212 of vertices V ₁ to V _t . t is an integer indicating the number of vertices included in face 132 .

As illustrated in FIG. 8, the vertex data 212 may include at least the identification number “id” of the vertex V and the position information “x, y, z” of the vertex V. FIG. In the example of FIG. 8, the suffixes “1” to “t” of the vertices V ₁ to V _t are examples of the respective identification numbers of the vertices V ₁ to V _t . The position information may be, for example, coordinate information in the three-dimensional space in which the analytical model 11 is displayed. The vertex data 212 may include various information belonging to the vertex V in addition to the identification number and position information.

FIG. 9 is a diagram showing an example of the surface information 21d. As illustrated in FIG. 9, the surface information 21d may include surface data 213 of a plurality of unit surfaces included in the surface 132 (for example, forming the surface 132). In the example of FIG. 9, the surface information 21d has s surface data 213 of surfaces F ₁ to F _s . s is an integer indicating the number of unit surfaces included in the surface 132 .

As illustrated in _FIG . 9, the surface data 213 includes an identification number "id" of the surface F, and a set of _a plurality of vertex data "V1, V2, V may contain at least ₃ ". In the example of FIG. 9, the suffixes “1” to “s” of the surfaces F ₁ to F _s are examples of identification numbers of the surfaces F ₁ to F _s respectively. A set of multiple vertex data may include the number of vertices V according to the shape of the unit face. Note that the face data 213 may include various information belonging to the face F in addition to the identification number and the set of a plurality of vertex data.

FIG. 10 is a diagram showing an example of the unit surface 214. As shown in FIG. FIG. 10 shows a surface 132 containing s surfaces F surrounding a partial model 13 containing m particles. As shown in FIG. 10, the surface 132 may be represented by a combination of multiple unit surfaces 214 (surfaces F ₁ to F _s ). Assume that the unit plane 214 illustrated in FIG. 10 is a triangle. For example, _one unit face 214 can be expressed as a unit face F1 having _three vertices V1 _, V2, and V3, and _each unit face 214 is expressed by a combination of vertex data 212 and face data 213. . Note that the unit face 214 is not limited to a triangle, and may be a quadrangle represented by four vertices, or a polygon or geometric shape represented by five or more vertices. good.

Various methods may be used as a method for generating the surface 132 based on the particle information 21a. As an example, the surface generation unit 25 may generate the surface 132 at a location corresponding to the surface position of the partial model 13 by the marching cube method.

The marching cubes method utilizes a regularly spaced grid surrounding a group of particles. The surface generation unit 25 calculates the existence rate of the particles P within a certain range from the vertex of each grid as the value of the vertex of the grid, and calculates the values of eight vertices for one grid. For example, if the particle P does not exist near the vertex, it is calculated as "0", and if it exists sufficiently, it is calculated as "1". can be positioned.

For example, the surface generation unit 25 converts the particle information 21a into vertex information 21c and surface information 21d, which are examples of information indicating the surface 132, by creating an isosurface at a location determined to have a value of “0.5”. be able to. Note that the position of the value "0.5" can be easily calculated by linear interpolation or the like based on the positional coordinates of the lattice vertex and the value of the existence rate.

FIG. 11 is a diagram for explaining an example of surface generation processing by the marching cube method. In the example of FIG. 11, for the sake of simplicity, the particle P and the grid are shown in a two-dimensional space, and the grid is shown as a square.

In FIG. 11, attention is paid to the grid A2 within the dashed line region labeled with reference A1 and the grid B2 within the dashed line region labeled with reference B1. In FIG. 11, the circles indicated by A3 to A6 and B3 to B6 are the four vertices of grid A2 and the four vertices of grid B2, respectively.

As shown in FIG. 11, particles P are present near each of the four vertices A3 to A6 of the lattice A2. Therefore, the surface generation unit 25 determines that the existence ratio of the particles P at the vertices A3 to A6 is all "1", and determines that the isosurface does not exist for the lattice A2.

On the other hand, as shown in FIG. 11, particles P do not exist near three vertices B3 to B5 of lattice B2, and particles P exist near vertex B6. Therefore, the surface generating unit 25 determines that the existence ratio of the particles P at the vertices B3 to B5 is "0", and the existence ratio of the particle P at the vertex B6 is "1". In this case, the surface generation unit 25 determines that there are isosurfaces between vertices B4 and B6 and between vertices B5 and B6 whose existence ratios of adjacent vertices are “0” and “1”. Then, the surface generation unit 25 sets an isosurface B7 passing through the midpoint between the vertices B4 and B6 and the midpoint between the vertices B5 and B6, where the presence ratio is "0.5", as indicated by reference symbol B7. do.

FIG. 12 is a diagram showing an example of processing for generating the face data model 134. As shown in FIG. In the example of FIG. 11, the isosurfaces obtained from each grid are connected throughout as indicated by arrow 133 to form a surface data model 134 representing the surface of surface 132 . In the example of FIG. 12, for the sake of simplicity, the particle P and the grid are shown in a two-dimensional space, and the grid is shown as a square. The model of the plane 132 illustrated in FIG. 10 is a model displaying s unit planes 214 (triangles) created from m particles P of the partial model 13. For example, a plane data model 134.

Note that the method for generating the surface 132 based on the particle information 21a is not limited to the marching cube method, and various methods may be employed. In addition, although the surface generation unit 25 generates the vertex information 21c and the surface information 21d as the information indicating the surface 132, the present invention is not limited to these, and various methods according to the method of generating the surface 132 can be used. information may be generated.

The grouping processing unit 26 calculates the boundaries of the planes 214 based on, for example, the angles of adjacent unit planes 214 among the plurality of unit planes 214 included in the plane 132, and groups the planes 214. FIG.

FIG. 13 is a diagram for explaining an example of grouping processing. As illustrated in FIG. 13 , the grouping processing unit 26 may generate a plurality of surfaces 14 , 15 and 16 based on a surface 132 corresponding to the surface of the partial model 13 . In the example of FIG. 13, surfaces 14, 15, and 16 are denoted as surfaces A, B, and C, respectively. Hereinafter, for the sake of convenience, the faces grouped by the grouping processing unit 26 may be referred to as "group faces". Each of the surfaces 14 to 16 is formed by a group of particles included in a part of the surface 132, in other words, a group of particles existing on the surface of the partial model 13. FIG. In the example of FIG. 13, the planes 14 to 16 are displayed separated from the plane 132 for convenience, but they may be displayed overlapping the plane 132 or the partial model 13 .

For example, in order to determine the boundary between the adjacent surfaces 214, the grouping processing unit 26 separates the adjacent surfaces 214 from each other when the angle difference between the adjacent surfaces 214 is greater than a predetermined threshold value Th_r. The faces 214 may be grouped to classify the surfaces of . Note that the angle threshold may be appropriately changed by the user via an input device, for example.

14 and 15 are diagrams for explaining an example of group determination processing. For example, the grouping processing unit 26 may calculate a normal vector as an index for calculating the angle difference between adjacent surfaces 214 . A normal vector is a vector perpendicular to a certain surface and is an example of information representing the orientation of the surface 214 . For example, the grouping processing unit 26 may calculate the normal vector of the surface 214 by a known technique based on the coordinates of the vertices included in the surface 214 .

For example, as shown in FIGS. 14 and 15, the grouping processing unit 26 divides two surfaces 141 (surface 1) and 142 (surface 2) adjacent to each other into normal vectors of surface 1 and normal of surface 2. , and the angle θ formed by the calculated normal vectors may be calculated.

As an example, based on the vertex information 21c and the surface information 21d, the grouping processing unit 26 selects, for example, two surface data having two or more vertex data 212 in common (or neighboring) as two surfaces 214 adjacent to each other. 213 may be specified. Then, the grouping processing unit 26 may calculate the normal vector for each of the two specified surface data 213 based on each vertex data 212 by a known method, and calculate the angle θ between the normal vectors. .

As illustrated in FIG. 14, when the angle θ formed by the two normal vectors is larger than a threshold (angle threshold) Th_r, the grouping processing unit 26 determines that the surface 1 and the surface 2 are different group surfaces. In other words, it may be determined that they belong to different group planes. Then, the grouping processing unit 26 may set the surface 1 as the group surface A and set the surface 2 as the group surface B, for example.

On the other hand, as illustrated in FIG. 15, when the angle θ formed by the two normal vectors is equal to or less than the threshold Th_r, the grouping processing unit 26 determines that the surface 1 and the surface 2 are the same group surface. It may be determined that they belong to the same group surface. Then, the grouping processing unit 26 may set the surface 1 and the surface 2 to the group surface A, for example.

14 and 15, one or both of the surfaces 141 and 142 may be the unit surface 214, or may be a group surface including two or more unit surfaces 214. .

As described above, the grouping processing unit 26 may generate a plurality of group surfaces by dividing the surface 132 of the partial model 13 based on the orientations of the unit surfaces 214 included in the surface 132 .

The grouping processing unit 26 may generate group plane information 21e, for example, when setting (creating) group planes.

FIG. 16 is a diagram showing an example of processing for generating group plane information 21e. The grouping processing unit 26 may generate group surface information 21e including a plurality of group tables 215 storing a plurality of grouped surface data 213, for example. In the example of FIG. 16, the group plane information 21e may include a group table 215 of a plurality of group planes including group planes A, B, and C. In the example of FIG.

For example, the grouping processing unit 26 may store the surface data 213 of the surfaces F ₁ to F _s of the surface information 21d in the group table 215 of the group surface determined by grouping. As an example, the grouping processing unit 26 may store planes F ₂ , F ₃ , F ₄ , F ₇ , F ₈ , F ₁₅ , . . . Each surface data 213 included in the group table 215 may be the same as the surface data 213 of the surface information 21d shown in FIG.

The particle search unit 27 acquires, from the input control unit 22, operation information indicating the group plane closest to the plane for which the user wants to set the calculation conditions, among the plurality of group planes specified (for example, picked) by the user through the input device. and search for particles P in the vicinity of the group plane. The particle search unit 27 may store, for example, information about the particles P in the vicinity of the specified group surface in the memory unit 21 as the surface particle information 21f.

As a method for specifying a group surface by an input device, for example, various methods such as selection of surfaces 14 to 16 of the partial model 13 using a mouse or a touch panel, input of information identifying the surfaces 14 to 16 using a keyboard, etc. is mentioned.

FIG. 17 is a diagram for explaining an example of particle search processing. FIG. 18 is a diagram showing an example of processing for calculating the distance d, and FIG. 19 is a diagram showing an example of processing for generating the surface particle information 21f.

In FIG. 17, it is assumed that designation A has been made for surface A of partial model 13 (see arrow (1)). Note that arrow (2) in FIG. 17 is a view of a portion of surface A, which is the target of designation A, viewed from the plane direction of surface A, in other words, intersects surface A and is perpendicular to surface A or substantially perpendicular to surface A. 4 is a diagram showing a vertical plane (a cross section of the partial model 13); FIG.

For example, as indicated by an arrow (2), the particle search unit 27 selects a unit surface 214 belonging to the surface A in the partial model 13 according to the designation A (surface selection) of the surface A input from the input device, A distance d between each of the m particles 17 included in the partial model 13 may be calculated. In the example of FIG. 18, the particle search unit 27 calculates the distance d between each of the surface data 213 included in the group table 215 of the group surface A and each of the particle data 211 included in the selected particle information 21b. do.

The particle searching unit 27 may extract the particles P whose calculated distance d is equal to or less than the threshold Th_d as the surface particles 18 and generate the surface particle information 21f. In the example of FIG. 19, the particle search unit 27 generates surface particle information 21f including particle data 211 of P ₄ , P ₉ , P ₁₀ , P ₁₃ , . Each particle data 211 included in the surface particle information 21f may be the same as the particle data 211 of the particle information 21a shown in FIG.

The particle searching unit 27 may calculate the distance d based on, for example, the particle arrangement distance or the radius of influence. The particle arrangement distance is the distance between particles P arranged in the analysis model 11 . The influence radius is a value such as several times the particle arrangement distance, and is calculated by calculation. Also, the threshold Th_d indicating the search range of the surface particles may be appropriately changed by the user via the input device, for example.

The particle search unit 27 causes the display control unit 23 to select the particles P extracted as the surface particles 18 in the analysis model 11 displayed on the screen of the display device such as a monitor, as indicated by an arrow (3). 19 may be displayed. The “selected state” may include, for example, placing the surface particles 18 in a “selectable” state in addition to the state in which the surface particles 18 are “selected” in the analytical model 11 . The "selectable" state includes, for example, displaying a list of the surface particles 18 on the screen of the display device based on the surface particle information 21f, highlighting the portion of the surface particles 18 in the analysis model 11, etc. may include displaying, etc. In the “selectable” state, it may be possible to transition to the “selected” state of the surface particles 18 according to selection (designation) of the list display or highlighted portion.

The display control unit 23 generates display information of the analysis model 11 in which the surface particles 18 extracted by the particle search unit 27 are selected by the above-described method (see arrow (3)), and outputs the display information to the display device. good. The surface particles 18 in the selected state 19 may be treated as, for example, surface elements to which calculation conditions are given in a simulation using the particle method.

The display control unit 23 controls, for example, the analytical model 11 (FIG. 3), the rectangular area 12 and the partial model 13 (FIG. 5), the surfaces 14 to 16 (FIG. 13), and the specification A of the surface 14 (FIG. 17). The display information indicated by the arrow (1)) may be generated for each process and output to the display device.

As described above, the server 2 according to one embodiment provides information indicating the surface 132 from the particle group for the particles P within the range specified by the user using the mouse or the like, among the particles P included in the analysis model 11. can be created. Then, the server 2 can extract the surface particles 18 corresponding to the surface position based on the distance from the designated surfaces 14 to 16 of the surfaces 132, and display the surface particles 18 as the selected state 19 in the analysis model 11. .

In this way, according to the server 2, the particles P near the surface of the analysis model 11 can be extracted at high speed on the pre-post based on the distance d from the group plane grouped by distinguishing the boundaries between the planes 214 and 214. , and the surface particles 18 can be easily selected collectively. In addition, the particles P for which the surface 132 is to be generated are limited to m particles P included within the range of the specified partial model 13 among the n particles included in the analytical model 11. , the processing load on the server 2 can be reduced, and high-speed processing can be realized.

[1-3] Application Example So far, the case where the analytical model 11 is a simple rectangular parallelepiped model has been described as an example, but the selection of surface particles becomes more difficult as the shape of the analytical model 11 becomes more complicated.

FIG. 20 is a diagram showing an example of the original data 30 and the analysis model 31 (particle model). An application example of the server 2 according to one embodiment will be described below, taking as an example the case where the analysis model 31 is a model generated based on the original data 30 including curved surfaces as illustrated in FIG. 20 .

FIG. 21 is a diagram showing an example of a rectangular area 32 for selecting part of the analytical model 31 shown in FIG. As shown in FIG. 21, it is assumed that the user selects the surface particles 321 of the curved portion by the rectangular area 32 . When the analytical model 31 has a shape including a curved surface, even if the user changes the direction of the analytical model 31 by rotating the position of the analytical model 31, the rectangular region 32 contains not only the surface particles 321 on the curved surface but also other particles. Particles 322 in portions that are not desired to be selected are also erroneously included. The selected particle acquisition unit 24 and the surface generation unit 25 generate a partial model including the particles P within the rectangular area 32 (not shown).

FIG. 22 is a diagram showing an example of the surface 33 generated based on the particle P (partial model) within the rectangular area 32. As shown in FIG. The surface generation unit 25 generates vertex information 21c and surface information 21d as information indicating the surface 33 based on the selected particle information 21b representing the partial model.

FIG. 23 is a diagram showing an example of the group planes 34-37. As illustrated in FIG. 23 , the grouping processing unit 26 may generate a plurality of planes 34 , 35 , 36 and 37 based on the plane 33 . In the example of FIG. 23, surfaces 34, 35, 36, and 37 are denoted as surfaces A, B, C, and D, respectively.

FIG. 24 is a diagram showing an example of surface particles 38 extracted when surface A shown in FIG. 23 is specified. FIG. 24 is a view of the analysis model 31 viewed from the plane D (see FIG. 23).

For example, the particle searching unit 27 selects the unit surface 214 belonging to the surface A in the partial model and each particle included in the partial model in accordance with the designation of the surface A (surface selection) input from the input device. , the distance d may be calculated. In the example of FIG. 24, the particle searching unit 27 calculates the distance d between each of the surface data 213 included in the group table 215 of the group surface A and each of the particle data 211 included in the selected particle information 21b. do.

Then, the particle searching unit 27 extracts the particles P whose calculated distance d is equal to or less than the threshold Th_d as the surface particles 38, and generates the surface particle information 21f.

FIG. 25 is a diagram showing an example of a selection state 39 of surface particles 38. As shown in FIG. As exemplified in FIG. 25 , the particle searching unit 27 may display the surface particles 38 in the analytical model 31 in the selected state 39 by the display control unit 23 .

As described above, in the application example, by applying the method of the server 2 according to one embodiment as the method of selecting the surface A in the analysis model 31, the selected curved surface is appropriately grouped based on the surface A, and the curved surface portion can be easily selected.

[1-4] Operation Example FIG. 26 is a flowchart for explaining an operation example of selection processing by the server 2 according to one embodiment. An operation example of selection processing of the surface particles 18 corresponding to the surface of the analysis model 11 by the server 2 will be described below with reference to FIG. 26 .

As shown in FIG. 26, the input control unit 22 of the server 2 acquires the particle information 21a of the analysis model 11 (step S1) and stores it in the memory unit 21. FIG.

The display control unit 23 generates display information representing the entire analysis model 11 based on the particle information 21a, and causes the display device to display the display information (step S2).

The input control unit 22 receives selection of a part of the analysis model 11 by the user (step S3). For example, the input control unit 22 acquires operation information indicating the rectangular area 12 selected by the user via the input device.

The selected particle acquisition unit 24 acquires information about the particles P within the selection range of the rectangular area 12 based on the selection information indicating the rectangular area 12 (step S4). For example, the selected particle acquisition unit 24 extracts the particles P within the selection range of the rectangular area 12 from the particle information 21 a to generate the selected particle information 21 b and stores it in the memory unit 21 .

The surface generation unit 25 generates information indicating the surface 132, such as vertex information 21c and surface information 21d, based on the selected particle information 21b (step S5). For example, the plane generation unit 25 generates a grid 131 surrounding the particle P represented by the selected particle information 21b, and generates a plane 132 at a location corresponding to the surface position of the grid 131 by a technique such as the marching cube method.

The grouping processing unit 26 groups the planes (unit planes 214) based on the information indicating the planes 132 (step S6), and generates group plane information 21e. For example, the grouping processing unit 26 calculates the normal vectors of the adjacent unit surfaces 214, and determines whether the adjacent unit surfaces 214 are the same group surface or not depending on whether the angle between the normal vectors is equal to or less than the threshold Th_r. is the group face of

Based on the group plane information 21e, the display control unit 23 generates display information representing a plurality of group planes together with, for example, the partial model 13, and displays it on the display device (step S7).

The input control unit 22 receives selection of a group surface by the user (step S8). For example, the input control unit 22 acquires operation information indicating the group surface selected by the user via the input device.

The particle search unit 27 searches for surface particles 18 within a certain distance range from the selected group plane based on the operation information indicating the group plane (step S9). For example, the particle search unit 27 calculates the distance d between the group table 215 of the selected group surface in the partial model 13 and each piece of particle data 211 included in the selected particle information 21b. Then, the particle search unit 27 extracts particles P whose distance d is equal to or less than the threshold Th_d from the selected particle information 21b, generates surface particle information 21f, and stores it in the memory unit 21. FIG.

Based on the surface particle information 21f, the display control unit 23 generates display information in which the surface particles 18 are in the selected state 19 in the analysis model 11, causes the display device to display it (step S10), and the process ends.

[1-5] Hardware Configuration Example The server 2 according to one embodiment may be a virtual server (VM; Virtual Machine) or may be a physical server. Also, the functions of the server 2 may be implemented by one computer, or may be implemented by two or more computers. Furthermore, at least some of the functions of the server 2 may be implemented using HW (Hardware) resources and NW (Network) resources provided by the cloud environment.

FIG. 27 is a block diagram showing a hardware (HW) configuration example of the computer 10 that implements the functions of the server 2. As shown in FIG. When a plurality of computers are used as HW resources for realizing the functions of the server 2, each computer may have the HW configuration illustrated in FIG.

As shown in FIG. 27, the computer 10 exemplarily includes a processor 10a, a memory 10b, a storage unit 10c, an IF (Interface) unit 10d, an IO (Input/Output) unit 10e, and a reading unit 10f as an HW configuration. Be prepared.

The processor 10a is an example of an arithmetic processing device that performs various controls and operations. The processor 10a may be communicatively connected to each block in the computer 10 via a bus 10i. Note that the processor 10a may be a multiprocessor including a plurality of processors, a multicore processor having a plurality of processor cores, or a configuration having a plurality of multicore processors.

Examples of the processor 10a include integrated circuits (ICs) such as CPUs, MPUs, GPUs, APUs, DSPs, ASICs, and FPGAs. A combination of two or more of these integrated circuits may be used as the processor 10a. CPU is an abbreviation for Central Processing Unit, and MPU is an abbreviation for Micro Processing Unit. GPU is an abbreviation for Graphics Processing Unit, and APU is an abbreviation for Accelerated Processing Unit. DSP is an abbreviation for Digital Signal Processor, ASIC is an abbreviation for Application Specific IC, and FPGA is an abbreviation for Field-Programmable Gate Array.

The memory 10b is an example of HW that stores information such as various data and programs. Examples of the memory 10b include one or both of a volatile memory such as a DRAM (Dynamic Random Access Memory) and a nonvolatile memory such as a PM (Persistent Memory).

The storage unit 10c is an example of HW that stores information such as various data and programs. Examples of the storage unit 10c include magnetic disk devices such as HDDs (Hard Disk Drives), semiconductor drive devices such as SSDs (Solid State Drives), and various storage devices such as nonvolatile memories. Examples of nonvolatile memory include flash memory, SCM (Storage Class Memory), ROM (Read Only Memory), and the like.

The memory unit 21 shown in FIG. 2 may be realized by at least one storage area of the memory 10b and the storage unit 10c. In other words, each information 21a to 21f shown in FIG. 2 may be stored in at least one storage area of the memory 10b and the storage section 10c.

Further, the storage unit 10c may store a program 10g (display program) that implements all or part of various functions of the computer 10. FIG.

For example, the processor 10a of the server 2 expands the program 10g stored in the storage unit 10c into the memory 10b and executes it, thereby realizing the functions of the server 2 (eg, blocks 22 to 27) illustrated in FIG. .

The IF unit 10d is an example of a communication IF that controls connection and communication with a network. For example, the IF unit 10d may include an adapter conforming to LAN (Local Area Network) such as Ethernet (registered trademark) or optical communication such as FC (Fibre Channel). The adapter may support one or both of wireless and wired communication methods.

For example, the server 2 may be connected to a computer such as the terminal device 3 via the IF section 10d so as to be able to communicate with each other. For example, the input control unit 22 may acquire the particle information 21a and the operation information from the terminal device 3 via the network. Further, the display control unit 23 may output (transmit) display information to the terminal device 3 via the network. Furthermore, the program 10g may be downloaded from the network to the computer 10 via the communication IF and stored in the storage section 10c.

The IO unit 10e may include one or both of an input device and an output device. Input devices include, for example, a keyboard, a mouse, and a touch panel. Examples of output devices include monitors, projectors, and printers. For example, the input control unit 22 shown in FIG. 2 may acquire one or both of the particle information 21a and the operation information via the input device of the IO unit 10e. Further, for example, the display control unit 23 shown in FIG. 2 may output and display display information to the output device of the IO unit 10e.

The reading unit 10f is an example of a reader that reads data and program information recorded on the recording medium 10h. The reading unit 10f may include a connection terminal or device to which the recording medium 10h can be connected or inserted. Examples of the reading unit 10f include an adapter conforming to USB (Universal Serial Bus), a drive device for accessing a recording disk, and a card reader for accessing flash memory such as an SD card. The recording medium 10h may store the program 10g, or the reading unit 10f may read the program 10g from the recording medium 10h and store it in the storage unit 10c.

Examples of the recording medium 10h include non-temporary computer-readable recording media such as magnetic/optical discs and flash memories. Examples of magnetic/optical discs include flexible discs, CDs (Compact Discs), DVDs (Digital Versatile Discs), Blu-ray discs, and HVDs (Holographic Versatile Discs). Examples of flash memories include semiconductor memories such as USB memories and SD cards.

The HW configuration of the computer 10 described above is an example. Therefore, HW in the computer 10 may be increased or decreased (for example, addition or deletion of arbitrary blocks), division, integration in arbitrary combinations, addition or deletion of buses, or the like may be performed as appropriate. For example, in the server 2, at least one of the IO unit 10e and the reading unit 10f may be omitted.

Note that the terminal device 3 shown in FIG. 2 may have the same HW configuration as the computer 10 shown in FIG. 27 .

[2] Others The technique according to the embodiment described above can be modified and changed as follows.

For example, the input control unit 22, the display control unit 23, the selected particle acquisition unit 24, the surface generation unit 25, the grouping processing unit 26, and the particle search unit 27 included in the server 2 shown in FIG. may be used, or may be divided.

The particle information 21a, the selected particle information 21b, the vertex information 21c, the surface information 21d, the group surface information 21e, and the surface particle information 21f stored in the memory unit 21 shown in FIG. , or divided information.

Further, the server 2 shown in FIG. 2 may be a configuration (system) in which a plurality of devices cooperate with each other via a network to realize each processing function. As an example, the memory unit 21 is a DB server, the selected particle acquisition unit 24, the surface generation unit 25, the grouping processing unit 26, and the particle search unit 27 are application servers, and the input control unit 22 and display control unit 23 are web servers. may In this case, each processing function of the server 2 may be realized by the database server, the application server, and the web server cooperating with each other via a network.

[3] Supplementary Note The following Supplementary Note will be disclosed with respect to the above embodiment.

(Appendix 1)
display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
responsive to a second input, selecting a second plurality of points of the first plurality of points that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes;
A display program that causes a computer to perform processing.

(Appendix 2)
The processing for generating the plurality of surfaces includes forming a surface of the partial model, which is a partial model represented by the first plurality of points and which is a part of the model, into a plurality of unit surfaces included in the surface. including a process of generating the plurality of faces by dividing based on the orientation of
The display program according to appendix 1.

(Appendix 3)
In the process of generating the plurality of planes, the two unit planes are divided according to whether an angle between normal vectors of two unit planes adjacent to each other among the plurality of unit planes is equal to or less than an angle threshold. Including the process of determining whether the faces are included in the same face or in different faces,
The display program according to appendix 2.

(Appendix 4)
The process of generating the plurality of planes includes, among the plurality of unit planes, including two adjacent unit planes having an angle between the normal vectors equal to or less than the angle threshold in the same plane, and including a process of including two adjacent unit planes in which the angle between the vectors is greater than the angle threshold in different planes;
A display program according to appendix 3.

(Appendix 5)
the second input includes information indicative of the first face;
The process of placing the second plurality of points in a selected state includes:
extracting, from the first plurality of points, the second plurality of points where the distance between the first surface and each of the first plurality of points is equal to or less than the threshold;
outputting display information in which the second plurality of points in the model are selected;
The display program according to any one of Appendices 1 to 4.

(Appendix 6)
the first input includes information indicative of a predetermined region extent of the model;
The process of identifying the first plurality of points includes a process of identifying the first plurality of points included in the predetermined area range in the model, out of the point group.
The display program according to any one of Appendices 1 to 5.

(Appendix 7)
display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
responsive to a second input, selecting a second plurality of points of the first plurality of points that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes;
A display method in which processing is performed by a computer.

(Appendix 8)
The processing for generating the plurality of surfaces includes forming a surface of the partial model, which is a partial model represented by the first plurality of points and which is a part of the model, into a plurality of unit surfaces included in the surface. including a process of generating the plurality of faces by dividing based on the orientation of
The display method according to appendix 7.

(Appendix 9)
In the process of generating the plurality of planes, the two unit planes are divided according to whether an angle between normal vectors of two unit planes adjacent to each other among the plurality of unit planes is equal to or less than an angle threshold. Including the process of determining whether the faces are included in the same face or in different faces,
The display method according to appendix 8.

(Appendix 10)
The process of generating the plurality of planes includes, among the plurality of unit planes, including two adjacent unit planes having an angle between the normal vectors equal to or less than the angle threshold in the same plane, and including a process of including two adjacent unit planes in which the angle between the vectors is greater than the angle threshold in different planes;
The display method according to appendix 9.

(Appendix 11)
the second input includes information indicative of the first face;
The process of placing the second plurality of points in a selected state includes:
extracting, from the first plurality of points, the second plurality of points where the distance between the first surface and each of the first plurality of points is equal to or less than the threshold;
outputting display information in which the second plurality of points in the model are selected;
The display method according to any one of appendices 7 to 10.

(Appendix 12)
the first input includes information indicative of a predetermined region extent of the model;
The process of identifying the first plurality of points includes a process of identifying the first plurality of points included in the predetermined area range in the model, out of the point group.
The display method according to any one of appendices 7 to 11.

(Appendix 13)
display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
A control that selects, in response to a second input, a second plurality of points, among the first plurality of points, that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes. having a department,
Information processing equipment.

(Appendix 14)
In the process of generating the plurality of surfaces, the control unit may include a surface of the partial model represented by the first plurality of points, which is a part of the model, in the surface. generating the plurality of unit faces by dividing based on the orientation of the plurality of unit faces;
13. The information processing device according to appendix 13.

(Appendix 15)
In the process of generating the plurality of planes, the control unit performs , determining whether the two unit faces are included in the same face or in different faces;
15. The information processing device according to appendix 14.

(Appendix 16)
In the process of generating the plurality of planes, the control unit converts, among the plurality of unit planes, two adjacent unit planes having an angle between the normal vectors equal to or smaller than the angle threshold to the same plane. including two mutually adjacent unit faces in which the angle between the normal vectors is greater than the angle threshold as different faces;
16. The information processing device according to appendix 15.

(Appendix 17)
the second input includes information indicative of the first face;
The control unit, in the process of setting the second plurality of points to a selected state,
extracting, from the first plurality of points, the second plurality of points where the distance between the first surface and each of the first plurality of points is equal to or less than the threshold;
outputting display information in which the second plurality of points in the model are in a selected state;
The information processing apparatus according to any one of appendices 13 to 16.

(Appendix 18)
the first input includes information indicative of a predetermined region extent of the model;
wherein, in the process of specifying the first plurality of points, the control unit specifies the first plurality of points included in the predetermined area range in the model, out of the point group;
The information processing apparatus according to any one of appendices 13 to 17.

1 system 11 analysis model 12 rectangular area 13 partial model 14-16 group surface 17 particle 18 surface particle 19 selection state 2 server 20 control unit 21 memory unit 21a particle information 21b selected particle information 21c vertex information 21d surface information 21e group surface information 21f surface particle information 211 particle data 212 vertex data 213 surface data 214 unit surface 215 group table 22 input control unit 23 display control unit 24 selected particle acquisition unit 25 surface generation unit 26 grouping processing unit 27 particle search unit 3 terminal device

Claims (8)

display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
responsive to a second input, selecting a second plurality of points of the first plurality of points that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes;
A display program that causes a computer to perform processing. The processing for generating the plurality of surfaces includes forming a surface of the partial model, which is a partial model represented by the first plurality of points and which is a part of the model, into a plurality of unit surfaces included in the surface. including a process of generating the plurality of faces by dividing based on the orientation of
The display program according to claim 1. In the process of generating the plurality of planes, the two unit planes are divided according to whether an angle between normal vectors of two unit planes adjacent to each other among the plurality of unit planes is equal to or less than an angle threshold. Including the process of determining whether the faces are included in the same face or in different faces,
The display program according to claim 2. The process of generating the plurality of planes includes, among the plurality of unit planes, including two adjacent unit planes having an angle between the normal vectors equal to or less than the angle threshold in the same plane, and including a process of including two adjacent unit planes in which the angle between the vectors is greater than the angle threshold in different planes;
The display program according to claim 3. the second input includes information indicative of the first face;
The process of placing the second plurality of points in a selected state includes:
extracting, from the first plurality of points, the second plurality of points where the distance between the first surface and each of the first plurality of points is equal to or less than the threshold;
outputting display information in which the second plurality of points in the model are selected;
The display program according to any one of claims 1 to 4. the first input includes information indicative of a predetermined region extent of the model;
The process of identifying the first plurality of points includes a process of identifying the first plurality of points included in the predetermined area range in the model, out of the point group.
The display program according to any one of claims 1 to 5. display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
responsive to a second input, selecting a second plurality of points of the first plurality of points that are at a distance equal to or less than a threshold from a first plane included in the plurality of planes;
A display method in which processing is performed by a computer. display the model containing the point cloud,
identifying a first plurality of points of the point cloud in response to a first input;
generating a plurality of surfaces corresponding to the surface of the model based on the first plurality of points;
A control that selects a second plurality of points at a distance equal to or less than a threshold from a first plane included in the plurality of planes in response to a second input. having a department,
Information processing equipment.

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