JP6092543B2 - Information processing apparatus and method - Google Patents

Description

  The present invention relates to information processing for creating an analysis model from a three-dimensional model.

  Computer aided design (CAD) is widely used to design parts and products. An analysis using the finite element method can be cited as a method of utilizing a three-dimensional model (hereinafter referred to as CAD model) created using CAD. When a CAD model is used for analysis, if a complicated shape or a fine shape exists, the number of meshes increases and a large amount of calculation time is required. Therefore, in general, a CAD model for analysis (hereinafter referred to as an analysis model) is generated by simplifying the shape of the CAD model while maintaining a certain degree of analysis accuracy.

  Shape simplification in thermal fluid analysis includes “shape deletion” that deletes minute parts of parts and “gap” that fills minute gaps (hereinafter referred to as contact parts) that are judged to be in contact between parts. There are two types of “filling”. Currently, the user determines a location that is considered to have little influence on the analysis result, and performs “shape deletion” or “gap filling” on the location. In order to reduce such a user's work load, the method of filling a contact part is proposed.

  The invention of Patent Document 1 divides the shape of a part into a plurality of surface elements, measures the distance between each surface element and the surface element facing it, and extracts and extracts the surface elements present in the gap between the parts Create a gap model using the selected face elements.

  Since the method of Patent Document 1 simply fills a gap of a minute distance, if the shape of a part is changed during the shape simplification process, the contact relationship of the gap before the shape simplification is not maintained, and the gap to be left In some cases, an appropriate analysis model cannot be created by filling in or leaving a gap to be filled. Eventually, the user manually simplifies the shape so that the correct “gap filling” is performed while maintaining the contact relationship of the gap, and the user work takes a lot of labor and time.

JP 2004-265050 A

  An object of the present invention is to efficiently create a highly accurate analysis model from a three-dimensional model.

  The present invention has the following configuration as one means for achieving the above object.

The information processing according to the present invention creates an initial mesh model representing the surface shape of a three-dimensional model created by computer-aided design, and the surface of another part represented by the initial mesh model is within a preset threshold. in some, the initial top point of the components mesh model represents detected as a proximity point, the deviation of the shape between the initial mesh model to the a simplified mesh model obtained by performing Ejjikorapusu predetermined number initial mesh model an evaluation value representing a calculated vertex your capital of the initial mesh model, the shape of the pre-Symbol initial mesh model to create an analysis model simplified, the analysis model, the apex in the order the evaluation value is smaller Selecting, determining whether the selected vertex is the proximity point and determining whether the other end of the edge having the vertex as one end is the proximity point; When the vertex or the vertex at the other end is the proximity point, the vertex and the vertex at the other end are evaluated with the evaluation value representing the shape deviation between the initial mesh model and the surface corresponding to the proximity point. It is created by repeating a series of processes consisting of performing the edge collapse combined with merge vertices determined so that the sum of evaluation values representing distances is minimized to a predetermined number of executions less than or equal to the predetermined number of times. characterized in that that.

  According to the present invention, it is possible to efficiently create a highly accurate analysis model from a three-dimensional model.

The block diagram explaining the structural example of the information processing apparatus which performs the shape simplification process of an Example. The flowchart explaining a shape simplification process. The flowchart explaining a shape simplification process. The figure which shows the example of a screen which is a user interface for inputting the threshold value of gap filling. The figure which shows the example of a screen which is UI which sets a simplification level. The figure which shows the example of a screen which is UI for setting the coefficient of an evaluation function. The figure explaining function E1. The figure explaining function E2. The figure which shows an example of the proximity relationship table which shows the correspondence of a proximity vertex and a proximity polygon. The figure which shows the example of a screen of UI for confirming the relationship between a proximity vertex and a proximity polygon. The figure which shows an example of a deviation | shift amount table. The figure explaining edge collapse. The figure which shows the example of a screen which is UI which shows the execution result of a shape simplification process.

  Hereinafter, information processing according to an embodiment of the present invention will be described in detail with reference to the drawings.

[Device configuration]
A configuration example of an information processing apparatus that executes the shape simplification process of the embodiment will be described with reference to the block diagram of FIG.

  In FIG. 1, a central processing unit (CPU) 102 sets various parameters of a unit to be designed in accordance with an instruction input from an input device 104, and executes processing for shape input. Further, the CPU 102 displays the three-dimensional shape of the unit, input information (various parameters, route information), processing progress, and the like on the display device 101 in accordance with the processing.

  The input device 104 includes a keyboard, a mouse, a pointing device, and the like, and inputs various information necessary for processing, menu selection instructions, other user instructions, and the like. The storage device 103 includes a ROM, a RAM, a hard disk drive (HDD), and a solid state drive (SSD). The storage device 103 stores a program executed by the CPU 102, data of a three-dimensional model (hereinafter, CAD model) created using computer-aided design (CAD), and the like.

  In addition, a printer (not shown) for recording information displayed on the display device 101 on recording paper may be connected to the CPU 102, and other peripheral devices may be connected as necessary. Of course, a dedicated device may be used as the information processing device of the embodiment, but a general-purpose computer device such as a personal computer supplied with a program for executing the shape simplification processing of the embodiment may be used.

[Shape simplification process]
The shape simplification process will be described with reference to the flowcharts of FIGS. 2A and 2B.

  The CPU 102 creates a mesh model representing the surface shape of the CAD model according to the user instruction (S201). The mesh model is composed of a plurality of polygons.

● Parameter setting Next, the CPU 102 determines a small gap (hereinafter, referred to as a contact between a set of polygons representing the shape of a certain component (hereinafter referred to as the shape of a component) and the shape of another component. A threshold value for filling the contact portion (hereinafter referred to as gap filling) is input (S202). FIG. 3 shows an example of a screen that is a user interface (UI) for inputting a gap filling threshold. The user inputs a threshold value (5 mm in the example of FIG. 3) to the threshold value input unit 301 and presses an OK button 302 to determine the threshold value. Further, the cancel button 303 is pressed to cancel the threshold value input.

  Next, the CPU 102 sets a simplification level in deleting a fine part of the shape of the part (hereinafter, shape deletion) for the created mesh model (S203). FIG. 4 shows an example of a screen that is a UI for setting the simplification level. The user operates the sliding bar 401 to set a simplification level according to the purpose. The user presses the OK button 402 to determine the simplification level, and presses the cancel button 403 to cancel the setting of the simplification level.

  The simplification level indicates, for example, the rate at which edge collapse is performed, but other criteria may be provided. For example, when the simplification level is set to “low” (sliding bar 401 is moved to “low” at the left end), for example, 90% of the maximum number of times of edge collapse is executed. When the number of executions of edge collapse is large, the deviation between the shape of the mesh model before simplification (hereinafter referred to as initial mesh model) and the shape of the mesh model after simplification (hereinafter referred to as simplified mesh model) increases. That is, a simplified mesh model having a large shape difference with respect to the shape of the initial mesh model is created.

  Further, when the simplification level is moved to the vicinity of the center of the sliding bar 401, for example, 50% of the maximum number of times of edge collapse is executed. Furthermore, when the simplification level is set to “high” (sliding bar 401 is moved to “high” on the right end), for example, 10% of the maximum number of times of edge collapse is executed. When the number of executions of edge collapse is small, the difference between the shape of the initial mesh model and the shape of the simplified mesh model is small. That is, a simplified mesh model with a small difference in shape with respect to the shape of the initial mesh model is created.

  Thus, the “simplification level” indicates the degree of change in the shape of the simplified mesh model from the shape of the initial mesh model, and the simplification level “low” indicates a large change in shape, and the simplification level “high”. The change in shape is small. Increasing the simplification level makes the simplified mesh model more detailed.

  Next, the CPU 102 sets the coefficient of the evaluation function for evaluating the result of executing the shape simplification process including gap filling and shape deletion for the initial mesh model (S204). FIG. 5 shows a screen example that is a UI for setting the coefficient of the evaluation function. A function E1 included in the evaluation function E indicated by reference numeral 501 is a function representing a deviation from the shape (initial shape) of the initial mesh model due to shape deletion. The function E2 is a function representing the distance between the shapes of two parts due to gap filling. That is, the sum of the functions E1 and E2 becomes the evaluation function E for evaluating the deviation from the initial shape at the contact portion between the shapes of the two parts.

Function E1
The function E1 is a calculation formula for minimizing the sum of squares (QEM: quadric error metrics) of a distance from a plane including one polygon to a point. The function E1 will be described with reference to FIG. As shown in FIG. 6, a plane including one polygon can be algebraically expressed by the following equation using a normal vector n of the plane.
n ^T x + d = 0… (1)

Therefore, the distance D between the point V and the surface f shown in FIG.
D = | n ^T v + d |… (2)

And if we define the sum of the squares of the distances D of the vertices v (f∋v) of the surface f as elements as the QEM of the vertices v, the function E1 can be expressed in quadratic form as Can be represented.
E1 = Σarea (f) | n _f ^T v + d _f | ²
= v ^T Av + 2b ^T v + c (3)
Where A is a 3 × 3 symmetric matrix,
b is a column vector,
c is a scalar,
area (f) is the area of the surface f.

Function E2
The function E2 will be described with reference to FIG. The function E2 is the distance between the vertex v of the polygon of the shape 701 of a part and the surface of the shape 702 of the other part (hereinafter referred to as the proximity polygon) that is close to the vertex v. It can be expressed in the following form:
E2 = Σd ² (v, Pmin)
= v ^T A'v + 2b ' ^T v + c'… (4)
Here, Pmin is the surface of the component shape 702 closest to the vertex v (proximity polygon).

Therefore, the CPU 102 calculates a merge vertex, which will be described later, so as to minimize the evaluation function E shown below.
E = αE1 + βE2
= α (v ^T Av + 2b ^T v + c) + β (v ^T A'v + 2b ' ^T v + c')… (5)
Here, α is a value set in the coefficient input unit 502,
β is a value set in the coefficient input unit 503.

  The user inputs the coefficient α (0 ≦ α ≦ 1) of the function E1 for evaluating the deviation from the initial shape due to the shape deletion to the coefficient input unit 502, and sets the distance between the component shapes due to gap filling in the coefficient input unit 503. Enter the coefficient β (0 ≦ β ≦ 1) of the function E2 to be evaluated.

  When α = 1 and β = 0 are set, only evaluation regarding shape deletion is performed, and evaluation regarding gap filling is not performed. Conversely, when α = 0 and β = 1 are set, only the evaluation for gap filling is performed, and the evaluation for shape deletion is not performed. The user presses the OK button 505 to determine the coefficient, and presses the cancel button 506 to cancel the coefficient setting.

● Creation of proximity relationship table When the settings up to step S204 are completed, the CPU 102 detects the vertex of the shape of a part and its proximity polygon for the initial mesh model, and stores it in the storage device 103 as a proximity relationship table indicating the detection result. Save in a predetermined area (S205). The detected pair is a vertex of a shape of a certain part and a proximity polygon of the shape of another part that is within the gap filling threshold set in step S202 for the vertex. Hereinafter, the vertex corresponding to the detected proximity polygon is referred to as “proximity vertex”. FIG. 8 shows an example of the proximity relationship table indicating the correspondence between the proximity vertex and the proximity polygon.

  FIG. 9 shows an example of a UI screen for confirming the relationship between the proximity vertex and the proximity polygon. When the user selects a vertex 905 on the display screen 903 to display the proximity polygon and presses the “display proximity polygon” button 901 in the proximity relationship display dialog, a pair of the vertex 905 and the proximity polygon 906 is displayed as shown in the display screen 904. Is highlighted. In addition, when the “proximity polygon non-display” button 902 of the proximity relation display dialog is pressed, the highlight display of the pair of the proximity vertex and the proximity polygon is canceled.

Creation of deviation amount table Next, the CPU 102 applies edge collapse of the maximum number of executions to the initial mesh model (S206). The maximum number of executions is a predetermined number corresponding to a predetermined ratio of the total number of vertices of the initial mesh model. That is, when the predetermined ratio is set to 20%, for example, a simplified mesh model in which 20% of all vertices of the initial mesh model are reduced by edge collapse.

  Next, the CPU 102 calculates a function E1 representing a deviation in shape from the simplified mesh model simplified by edge collapse for all the vertices of the initial mesh model (S207). Then, a deviation amount table in which pairs of vertexes and evaluation values are arranged in ascending order of evaluation values indicated by the function E1 is stored in a predetermined area of the storage device 103 (S208).

  FIG. 10 shows an example of the deviation amount table. Although details will be described later, the CPU 102 acquires the vertices stored in the deviation amount table in order from the top (in ascending order of evaluation value), and when the acquired vertices are adjacent vertices stored in the proximity relationship table, the edge collapse is performed. Execute.

● Edge Collapse Edge collapse will be described with reference to FIG. Edge Collapse creates a new vertex (merge vertex) v 'that deletes edge e and merges two vertices v1 and v2 in an area where edge e and vertices v1 and v2 at both ends of edge e are adjacent. To do. The merge vertex v ′ is calculated so as to minimize the evaluation function E = αE1 + βE2. Edge collapse performs a simplification process by continuously executing operations for creating merge vertices. However, for example, when the simplification level is “high”, the execution of edge collapse ends when the number of edge collapse executions reaches, for example, 10% of the maximum number of edge collapse executions.

  In edge collapse, the CPU 102 initializes the counter i to i = 0 (S209), and acquires vertices in order from the top of the deviation amount table (S210). Then, referring to the proximity relationship table, it is determined whether or not the acquired vertex is a proximity endpoint (S211), and whether or not the other vertex of the initial mesh model edge having the acquired vertex as one end is a proximity vertex (S212) is performed.

  If either the acquired vertex or the vertex at the other end is a nearby vertex, the CPU 102 increments the counter i (S213). Then, the merged vertex obtained by combining these two vertices in the initial mesh model is set as the proximity vertex, and the proximity polygon corresponding to the proximity vertex before the connection is associated with the merge vertex (S214). If none of the vertices are adjacent vertices, the proximity relationship table including creation of merge vertices and correction of association is not performed.

  Next, the CPU 102 determines whether or not the execution of edge collapse has reached a preset number of executions (hereinafter, set number N, for example, 10% of the maximum number of executions) based on the count value of the counter i (S215). . If it is less than the set number (i <N), the process returns to step S210 to repeat the edge collapse. When the set number is reached (i = N), the shape simplification process is terminated.

  FIG. 12 shows an example of a screen that is a UI showing the execution result of the shape simplification process. A display screen 1201 shows a state in which the contact portion between the shapes of the two parts is filled by the gap filling process. When a “gap display” button 1203 in the gap filling execution location display dialog is pressed in this state, as shown in the display screen 1202, a portion (edge) 1205 that has a gap before the execution of edge collapse is highlighted. Also, when the “clear gap display” button 1204 is pressed, the highlight display of the portion where there was a gap before the execution of edge collapse is canceled.

  If the user can satisfy the created analysis model with reference to the UI indicating the execution result of the shape simplification process, the user proceeds to a stage such as thermal fluid analysis using the analysis model. If the created analysis model is not satisfactory, the gap simplification threshold, the simplification level, the coefficient of the evaluation function, etc. are corrected, and the shape simplification process is executed again.

  As described above, the edge collapse is repeated a predetermined number of executions with reference to the deviation amount table and the proximity relation table indicating the deviation from the initial shape of each vertex when the maximum number of executions of edge collapse is executed. Therefore, the shape simplification process is performed by executing the edge collapse from the adjacent vertex (vertex of the contact portion) with a small deviation from the initial shape. In other words, the proximity vertex at the contact part is moved in order from the one with the shortest movement distance due to edge collapse, and gap filling is executed, and a highly accurate analysis model for thermal fluid analysis is efficiently performed from the three-dimensional model. Can be created.

[Other Examples]
The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, etc.) of the system or apparatus reads the program. It is a process to be executed.

Claims (8)

Creating means for creating an initial mesh model representing the surface shape of a three-dimensional model created by computer-aided design;
A detector surface of the other component representing the initial mesh model is within a distance of a preset threshold, detecting the top point of the part in which the initial mesh model represents a proximity point,
Processing means for performing a predetermined number of edge collapses on the initial mesh model;
The evaluation value representing the deviation of the shape between the simplified mesh model and the initial mesh model obtained by said processing means, a calculation means for calculating the vertex your capital of the initial mesh model,
A simplified means for creating an analysis model by simplifying the shape of the pre-Symbol initial mesh model,
Have
The simplification means includes:
Select the vertices in ascending order of the evaluation value,
Determining whether the selected vertex is the proximity point and whether the other end of the edge where the vertex is one end is the proximity point;
In the case where the vertex or the vertex at the other end is the proximity point, the vertex and the vertex at the other end are represented by an evaluation value representing a deviation in shape between the initial mesh model and a surface corresponding to the proximity point, The edge collapse is performed to join the merge vertices determined so that the sum of the evaluation values representing the distance of
An information processing apparatus characterized by repeating a series of processes consisting of the above-mentioned predetermined number of executions equal to or less than the predetermined number of times .   The detecting means detects, as the proximity point, a vertex or an edge of a polygon that represents the surface shape of the component at which the polygon representing the surface shape of the other component is at a distance within the preset threshold. The information processing apparatus according to claim 1. 3. The information processing apparatus according to claim 1, wherein the predetermined number of times is a predetermined ratio of the number of vertices or edges of the initial mesh model. Furthermore, it has a setting means for setting the degree of execution of the edge collapse,
The preset number of executions, and an information processing apparatus according to any one of claims 1 to 3, characterized in that calculated from the degree and the predetermined number of times. Further, by an information processing apparatus according to any one of claims 1 to 4, characterized in that it comprises an input means for inputting the threshold value. The analysis model is an information processing apparatus according to claims 1, characterized in that an analysis model for thermal fluid analysis to any one of claims 5. An information processing method for an information processing apparatus having a creation unit, a detection unit, a processing unit, a calculation unit, and a simplification unit,
The creation means creates an initial mesh model representing the surface shape of a three-dimensional model created by computer-aided design,
The detection means, the other parts of the surface where the initial mesh model represents is within a distance of a preset threshold value, to detect the vertex of the part in which the initial mesh model represents a proximity point,
The processing means performs a predetermined number of edge collapses on the initial mesh model,
The calculating means, the evaluation value representing the deviation of the shape between the simplified mesh model and the initial mesh model obtained by said processing means calculates the vertex your capital of the initial mesh model,
The simplification means comprises:
Select the vertices in ascending order of the evaluation value,
Determining whether the selected vertex is the proximity point and whether the other end of the edge where the vertex is one end is the proximity point;
In the case where the vertex or the vertex at the other end is the proximity point, the vertex and the vertex at the other end are represented by an evaluation value representing a deviation in shape between the initial mesh model and a surface corresponding to the proximity point, The edge collapse is performed to join the merge vertices determined so that the sum of the evaluation values representing the distance of
An information processing method characterized in that an analysis model in which the shape of the initial mesh model is simplified is created by repeating a series of processes consisting of the above, a predetermined number of executions equal to or less than the predetermined number of times . A program for causing a computer to function as each unit of the information processing apparatus according to any one of claims 1 to 6 .