CN112685935B - Two-dimensional multi-block structured grid topology division method - Google Patents
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Abstract
The invention discloses a two-dimensional multi-block structured grid topology dividing method, which comprises the following steps: s1, calculating a geometric outline according to a point set of given geometric data points or a given region, and extracting corner points according to the geometric outline to form a group of key points; s2, performing triangle gridding treatment on the area in the geometric outline to form a plurality of triangle units; s3, searching a central axis in the geometric outline by using the triangular unit, and dividing the central axis into a main central axis and central axis branches; s4, mesh topology division is carried out by utilizing the central axis, the central axis branches and the key points. According to the method and the device, the geometric key points of the original structural grid are extracted, the central axis is calculated, and the grid topology is automatically divided, so that the structural grid is automatically segmented, manual intervention is not needed completely, the method and the device are efficient and stable, and errors possibly caused by manual operation are avoided.
Description
Technical Field
The disclosure belongs to the field of preprocessing of computational fluid mechanics, and particularly relates to a two-dimensional multi-block structured grid topology division method.
Background
The flow calculation generally comprises an inlet, an outlet and complex flow channels, and how to automatically and quickly generate a plurality of structural grids is one of the bottleneck problems of Computational Fluid Dynamics (CFD) engineering application. The topology division is realized by manually interactively picking up geometric information through the upper curve and the lower curve of a given channel, but the work is time-consuming and troublesome, the quality is low, and the quality of the topology division depends on manual experience; when the configuration changes, the topology is not reusable. Therefore, the realization of rapid automatic topology division is necessary, and the CFD engineering grid generation efficiency is accelerated.
Disclosure of Invention
To solve at least one of the above technical problems, the present disclosure provides a two-dimensional multi-block structured grid topology partitioning method.
The technical scheme of the present disclosure is as follows:
a two-dimensional multi-block structured grid topology partitioning method, comprising the steps of:
s1, calculating a geometric outline according to a point set of given geometric data points or a given region, and extracting corner points according to the geometric outline to form a group of key points;
s2, performing triangle gridding treatment on the area in the geometric outline of the point set to form a plurality of triangle units;
s3, searching a central axis in the geometric outline by using the triangular unit, and dividing the central axis into a main central axis and central axis branches;
s4, mesh topology division is carried out by utilizing the central axis, the central axis branches and the key points.
Optionally, the specific implementation method for extracting the geometric outline corner of the point set in step S1 is as follows:
s101, encrypting geometric data points respectively to form a anticlockwise or clockwise closed line;
s102, acquiring key points by adopting one or more of the following three methods;
corner key point: capturing the corner characteristics of the closed line, and marking geometric data points when the corner is larger than a first preset value as key points;
curvature characteristic key points: capturing the bending characteristics of the closed line, wherein geometric data point marks are key points when the folding angle change of the geometric data points in the closed line reaches a preset value;
directed bounding box keypoints: the closed line distribution feature is captured and marked as a key point when the aspect ratio of the bounding box of the segment is greater than a third preset value.
Optionally, in the step S102, the first preset value is a value in a range of 25 to 35 degrees; the second preset value is a value ranging between an angle value of 40 to 50 degrees; the third preset value is a value ranging between 0.1 and 0.2.
Optionally, the specific implementation method of the step S3 is as follows:
s301, the triangular units comprise connecting units and corner units, wherein the connecting units are connected with the three triangular units at the same time, the corner units are connected with only one triangular unit, and the opposite angles of the connected edges of the corner units are smaller than 160 degrees, and the connecting units and the corner units are triangular units; dividing the central axis into branches through the connecting unit, searching and extending the branches of the angle unit to corresponding geometric data points, and adding the inlet and the outlet into branch extension;
s302, determining an undirected graph through branch connection relations of the central axis;
s303, determining a main central axis through the inlet midpoint, the outlet midpoint and the undirected graph.
Optionally, the triangle gridding processing in the step S3 is performed by Delaunay triangle processing; the outside triangle unit for removing the closed line is used for removing the outside triangle by calculating the center of the circumcircle of each triangle and then by a ray method.
Optionally, step S31 is further performed between steps S3 and S4:
s31, searching key points outside the main central axis and the central axis branches from the key points in the step S1, and connecting the searched key points with the main central axis to form auxiliary lines;
and in the step S4, grid topology division is performed by combining auxiliary lines.
Optionally, the method for connecting the auxiliary line in step S31 is as follows: searching key points outside the main central axis and the branches, searching the nearest point on the central axis, which is nearest to the key point, and connecting the key point with the nearest point.
Optionally, in the step S31, it is further determined whether the included angle between the bisector of the key point and the main central axis is greater than 30 degrees,
if yes, forming an auxiliary line, otherwise, judging whether the internal angle of the key point is larger than 250 degrees, and if yes, forming two auxiliary lines.
Optionally, the step S4 includes the following steps:
s41, branching the auxiliary line and the central axis to generate an undirected graph;
s42, determining each sub-graph of the undirected graph through a minimum loop;
s43, mapping the nodes of each subgraph into grid blocks;
s44, smoothing each central axis branch and each auxiliary line by using spline lines;
s45, mapping the sub-blocks with corresponding spline lines;
s46, generating a multi-block structural grid.
Optionally, the specific implementation method of step S43 is as follows:
when the node number of the subgraph is greater than 4, mapping four vertexes of the block to the subgraph nodes, and ensuring that the angle of a line segment formed by the nodes is smaller than 45 degrees for each edge in the block;
when the node number of the subgraph is equal to 4, the four subgraph nodes correspond to four vertexes of the block;
when the node number of the subgraph is equal to 3, adding a central point in the subgraph, decomposing the subgraph into three quadrilateral graphs through the central point, and processing the quadrilateral graphs according to the node number of the subgraph being equal to 4.
According to the method and the device, the grid topology is divided according to the geometric key point extraction and the central axis calculation of the original structural grid, so that the structural grid is segmented.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
FIG. 1 is a method schematic diagram of a two-dimensional multi-block structured grid topology partitioning method in accordance with an embodiment of the present disclosure;
FIG. 2 is a method schematic diagram of a two-dimensional multi-block structured grid topology partitioning method of a second embodiment of the present disclosure;
FIG. 3 is a method schematic diagram of a two-dimensional multi-block structured grid topology partitioning method of embodiment three of the present disclosure;
FIG. 4 is an effect diagram of the geometric profile of the present disclosure;
FIG. 5 is an effect diagram of the present disclosure after key points are extracted;
FIG. 6 is an initial effect diagram of the triangle meshing process in the present disclosure;
FIG. 7 is a final effect diagram of the triangle meshing process of the present disclosure;
FIG. 8 is an effect diagram of the present disclosure after finding the central axis;
FIG. 9 is an effect diagram of the present disclosure after the addition of an auxiliary line;
FIG. 10 is a processing effect diagram of a diagram of three nodes in the present disclosure;
FIG. 11 is a final effect diagram of the two-dimensional multi-block structured grid topology partitioning method of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the drawings and the embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant content and not limiting of the present disclosure. It should be further noted that, for convenience of description, only a portion relevant to the present disclosure is shown in the drawings.
In addition, embodiments of the present disclosure and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Example 1
Referring to fig. 1, a two-dimensional multi-block structured grid topology dividing method is characterized by comprising the following steps:
s1, calculating a geometric outline according to a point set of given geometric data points or a given region, and extracting corner points according to the geometric outline to form a group of key points; referring to fig. 4 and 5, if a set of points is given that are geometric data points, the given geometric data points are discrete points of two disjoint curves; and converting the geometric data points into a closed geometric outline, and extracting each corner point in the geometric outline. If you are the region, then the region is converted into a closed geometric outline, and each corner point in the geometric outline is extracted; the extraction of the corner points can adopt methods such as Moravec operator, forstner operator, harris operator, SUSAN operator, shi-Tomasi operator and the like.
S2, performing triangle gridding treatment on the area in the geometric outline of the point set to form a plurality of triangle units; referring to fig. 6, the triangle meshing process may employ Delaunay triangulation algorithm, array plane propulsion method, etc.; referring to fig. 7, after triangle gridding, triangles outside the geometric outline are removed, leaving triangles in the geometric outline. Triangles that are outside the geometric outline are generally removed include area and discriminant, angle and discriminant, ray, and the like.
S3, searching a central axis in the geometric outline by using the triangular unit, and dividing the central axis into a main central axis and central axis branches; referring to fig. 8, the primary central axis search may find the primary central axis by using a minimum path method of the graph from the inlet to the outlet, and the primary central axis is not branched. This step may also be performed by the Zhang-Suen refinement algorithm, etc.
S4, mesh topology division is carried out by utilizing the central axis, the central axis branches and the key points.
According to the method and the device, the geometric key points of the original structural grid are extracted, the central axis is calculated, and the grid topology is automatically divided, so that the structural grid is automatically segmented, manual intervention is not needed completely, the method and the device are efficient and stable, and errors possibly caused by manual operation are avoided.
Referring to fig. 2, in one embodiment, the specific implementation method for extracting geometric contour corner points of the point set in step S1 is as follows:
s101, encrypting the geometric data points respectively to form a anticlockwise or clockwise closed line. N-polygons may also be represented, including vertices of n, defining p= { P1..the term, pn }, for storing coordinates of key points.
S102, acquiring key points by adopting one or more of the following three methods;
corner key point: capturing the corner characteristics of the closed line, and marking geometric data points when the corner is larger than a first preset value as key points;
curvature characteristic key points: capturing the bending characteristics of the closed line, wherein geometric data point marks are key points when the folding angle change of the geometric data points in the closed line reaches a preset value;
directed bounding box keypoints: the closed line distribution feature is captured and marked as a key point when the aspect ratio of the bounding box of the segment is greater than a third preset value.
In a preferred embodiment, in the step S102, the first preset value is a value ranging from an angle value of 25 to 35 degrees; the second preset value is a value ranging between an angle value of 40 to 50 degrees; the third preset value is a value ranging between 0.1 and 0.2. Selecting values in this range allows for both higher accuracy and lower computational effort. In another embodiment of the present application, the first preset value is selected to be 30 degrees, the second preset value is selected to be 45 degrees, and the third preset value is selected to be 0.15; the arrangement can divide a circle of 360-degree more evenly, and the calculation is convenient.
In another preferred embodiment, the triangle gridding process in step S2 is performed by Delaunay triangle processing; the triangle unit outside the closed line is removed by calculating the center of the circumscribed circle (circle center or geometric key point) of each triangle, then the triangle outside the closed line is removed by a ray method, and the Delaunay triangle relation is reconstructed.
In another embodiment, the specific implementation method of the step S3 is as follows:
s301, the triangular units comprise connecting units and corner units, wherein the connecting units are connected with the three triangular units at the same time, the corner units are connected with only one triangular unit, and the opposite angles of the connected edges of the corner units are smaller than 160 degrees, and the connecting units and the corner units are triangular units; dividing the central axis into branches through the connecting unit, searching and extending the branches of the angle unit to corresponding geometric data points, namely nearest key points, and adding the inlet and the outlet into branch extension; the triangle unit further includes: the transition unit comprises two connected units, only one connected unit is provided, and the diagonal angle of the connected side is 160 degrees or more, and the transition unit is a continuous unit.
S302, determining an undirected graph through branch connection relations of the central axis;
s303, determining a main central axis through the inlet midpoint, the outlet midpoint and the undirected graph. The determination mode of the main circumference axis can be determined by a shortest path method from an inlet key to an outlet key; and outside the main central axis is a central axis branch.
Example two
As shown in fig. 2 and 9, this embodiment is different from embodiment 1 in that step S31 is further performed between steps S3 and S4:
s31, searching key points outside the main central axis and the central axis branches from the key points in the step S1, and connecting the searched key points with the main central axis to form auxiliary lines; specifically, the step may connect the key point with the nearest point by searching for the nearest point on the central axis that is closest to the key point. The nearest neighbor searching can adopt a kd-Tree searching method, and the calculation is accurate.
In the step S4, grid topology division is further performed by combining auxiliary lines, so that grid division precision is improved.
Because the main central axis and the central axis branches can cover all key points when searching the central axis of the simple geometric outline, the main central axis and the central axis can carry out general grid division on the geometric outline, and only the refined topological division on the grid is needed in the follow-up process;
in the geometric outline of the complex graph, the geometric outline is initially divided simply through the axle wire searching, and for the area far away from the axle wire or more complex, part of key points are not on the main axle wire or axle wire branches, so that the graph dividing accuracy is poor when the network topology is divided, therefore, the key points which are not on the main axle wire or axle wire branches are required to be connected with the main axle wire, the auxiliary wire carries out the initial network division on the area far away from or more complex, and the grid divided by the auxiliary wire can be combined in the subsequent step S4 to carry out the refined grid topology division on the more complex area.
The accuracy of final calculation is improved by searching key points outside the main central axis and the central axis branches, dividing auxiliary lines and carrying out grid topology division by combining the auxiliary lines.
The connection method of the auxiliary line in step S31 is as follows: searching key points outside the main central axis and the branches, searching the nearest point on the central axis, which is nearest to the key point, and connecting the key point with the nearest point to form an auxiliary line.
In one embodiment, the auxiliary line dividing method further includes determining in step S31 whether the included angle between the bisector of the key point and the main central axis is greater than 30 degrees,
if yes, forming an auxiliary line, otherwise, judging whether the internal angle of the key point is larger than 250 degrees, and if yes, forming two auxiliary lines.
Example III
Referring to fig. 3, the difference between the present embodiment and the first embodiment is that the step S4 includes the following steps:
s41, branching the auxiliary line and the central axis to generate an undirected graph; for subsequent generation of the structural grid.
S42, determining each sub-graph of the undirected graph through a minimum loop;
s43, mapping the nodes of each subgraph into grid blocks;
s44, smoothing each central axis branch and each auxiliary line by using spline lines;
s45, mapping the sub-blocks with corresponding spline lines;
s46, generating a multi-block structural grid. Referring to fig. 11, automatic partitioning of the two-dimensional multi-block structured grid topology is finally achieved.
In another embodiment, the specific implementation method of the step S43 is as follows:
when the node number of the subgraph is greater than 4, mapping four vertexes of the block to the subgraph nodes, and ensuring that the angle of a line segment formed by the nodes is smaller than 45 degrees for each edge in the block;
when the node number of the subgraph is equal to 4, the four subgraph nodes correspond to four vertexes of the block;
referring to fig. 10, when the node number of the sub-graph is equal to 3, a center point is added in the sub-graph, the sub-graph is decomposed into three quadrilateral graphs through the center point, and then the quadrilateral graphs are processed when the node number of the sub-graph is equal to 4. Three quadrangles are formed by connecting the center point with the nearest points on three sides of the triangle.
The present application may be in Python.
In the description of the present specification, reference to the terms "one embodiment/manner," "some embodiments/manner," "example," "specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/manner or example is included in at least one embodiment/manner or example of the present application. In this specification, the schematic representations of the above terms are not necessarily for the same embodiment/manner or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/modes or examples described in this specification and the features of the various embodiments/modes or examples can be combined and combined by persons skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless explicitly defined otherwise.
It will be appreciated by those skilled in the art that the above-described embodiments are merely for clarity of illustration of the disclosure, and are not intended to limit the scope of the disclosure. Other variations or modifications will be apparent to persons skilled in the art from the foregoing disclosure, and such variations or modifications are intended to be within the scope of the present disclosure.
Claims (8)
1. A two-dimensional multi-block structured grid topology partitioning method, comprising the steps of:
s1, calculating a geometric outline according to a point set of given geometric data points or according to a given region, extracting corner points according to the geometric outline to form a group of key points, wherein the method comprises the following steps:
s101, encrypting geometric data points respectively to form a anticlockwise or clockwise closed line;
s102, acquiring key points by adopting one or more of the following three methods;
corner key point: capturing the corner characteristics of the closed line, and marking geometric data points when the corner is larger than a first preset value as key points;
curvature characteristic key points: capturing the bending characteristics of the closed line, wherein geometric data point marks are key points when the folding angle change of the geometric data points in the closed line reaches a preset value;
directed bounding box keypoints: capturing the distribution characteristics of the closed line, and marking the closed line as a key point when the length-width ratio of the bounding box of the segment is larger than a third preset value;
s2, performing triangle gridding treatment on the area in the geometric outline to form a plurality of triangle units;
s3, searching a central axis in the geometric outline by the triangular unit, and dividing the central axis into a main central axis and a central axis branch, wherein the method comprises the following steps of:
s301, the triangular units comprise connecting units and corner units, wherein the connecting units are connected with the three triangular units at the same time, the corner units are connected with only one triangular unit, and the opposite angles of the connected edges of the corner units are smaller than 160 degrees, and the connecting units and the corner units are triangular units; dividing the central axis into branches through the connecting unit, searching and extending the branches of the angle unit to corresponding geometric data points, and adding the inlet and the outlet into branch extension;
s302, determining an undirected graph through branch connection relations of the central axis;
s303, determining a main central axis through an inlet midpoint, an outlet midpoint and an undirected graph;
s4, mesh topology division is carried out by utilizing the central axis, the central axis branches and the key points.
2. The two-dimensional multi-block structured grid topology partitioning method of claim 1, wherein: in step S102, the first preset value is a value ranging from an angle value of 25 to 35 degrees; the second preset value is a value ranging between an angle value of 40 to 50 degrees; the third preset value is a value ranging between 0.1 and 0.2.
3. The two-dimensional multi-block structured grid topology partitioning method of claim 1, wherein: the triangle gridding processing in the step S3 is processed through Del aunay triangle processing; the outside triangle unit for removing the closed line is used for removing the outside triangle by calculating the center of the circumcircle of each triangle and then by a ray method.
4. The two-dimensional multi-block structured grid topology partitioning method of claim 1,
step S31 is also performed between steps S3 and S4:
s31, searching key points outside the main central axis and the central axis branches from the key points in the step S1, and connecting the searched key points with the main central axis to form auxiliary lines;
in step S4, mesh topology division is performed in combination with the auxiliary lines.
5. The two-dimensional multi-block structured grid topology partitioning method of claim 4, wherein the auxiliary line connection method in step S31 is as follows: searching key points outside the main central axis and the branches, searching the nearest point on the central axis, which is nearest to the key point, and connecting the key point with the nearest point.
6. The method of claim 5, wherein in step S31, it is further determined whether the angle between the bisector of the key point and the major central axis is greater than 30 degrees,
if yes, forming an auxiliary line, otherwise, judging whether the internal angle of the key point is larger than 250 degrees, and if yes, forming two auxiliary lines.
7. The two-dimensional multi-block structured grid topology partitioning method of claim 5 or 6, wherein step S4 comprises the steps of:
s41, branching the auxiliary line and the central axis to generate an undirected graph;
s42, determining each sub-graph of the undirected graph through a minimum loop;
s43, mapping the nodes of each subgraph into grid blocks;
s44, smoothing each central axis branch and each auxiliary line by using spline lines;
s45, mapping the sub-blocks with corresponding spline lines;
s46, generating a multi-block structural grid.
8. The two-dimensional multi-block structured grid topology partitioning method of claim 7, wherein the specific implementation method of step S43 is:
when the node number of the subgraph is greater than 4, mapping four vertexes of the block to the subgraph nodes, and ensuring that the angle of a line segment formed by the nodes is smaller than 45 degrees for each edge in the block;
when the node number of the subgraph is equal to 4, the four subgraph nodes correspond to four vertexes of the block;
when the node number of the subgraph is equal to 3, adding a central point in the subgraph, decomposing the subgraph into three quadrilateral graphs through the central point, and processing the quadrilateral graphs according to the node number of the subgraph being equal to 4.
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| 二阶多面体网格中关键特征控制的表面重建技术;刘鹤丹;王成恩;;计算机科学(第01期);全文 * |
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