A method for merging and visualizing multi-partition grid flow field data

Abstract

The present invention provides a method for merging and visualizing flow field data of multiple partitioned grids, which relates to the field of computational fluid dynamics and solves the problem that the integrity of the grid in key flow areas is easily damaged, which affects the accuracy of flow field data visualization analysis. The method comprises: obtaining an original grid and partitioning the grid to obtain multiple block grids, and constructing a grid element mapping relationship between the original grid and the block grids; using CFD technology to calculate and obtain flow field data corresponding to the block grids; according to the grid element mapping relationship, indexing and obtaining the grid elements corresponding to the original grid through the grid elements of the block grids, and reconstructing a virtual grid that matches the original grid; reconstructing the grid topology relationship of the virtual grid, and storing the flow field data corresponding to the block grids in the corresponding area of ​​the virtual grid, obtaining virtual grid information with flow field data, and outputting it to a visualization file. The present invention ensures data integrity and lays a foundation for subsequent flow field characteristic analysis.

Description

Technical Field

[0001] The present invention relates to the field of computational fluid dynamics, is applied to the processing and display of flow field data, and specifically relates to a multi-partition grid flow field data merging and visualization method. Background Art

[0002] Computational Fluid Dynamics (CFD) is an interdisciplinary field that uses computer science and numerical algorithms to simulate and analyze fluid flows. The technology is developed to address critical aerodynamic issues in aerospace vehicle development and has broad applications in numerous other industrial sectors. Early research in CFD focused primarily on the development of theoretical models and fundamental algorithms, and was limited to simple geometric shapes such as two-dimensional cylinders and airfoils.

[0003] With the rapid advancement of computer hardware performance and the emergence of advanced methods such as the Reynolds-averaged Stokes equations (RANS), large eddy simulation (LES), and direct numerical simulation (DNS), CFD technology has been able to break through its original limitations and rapidly develop towards complex geometries, ultra-large grids, multidisciplinary cross-pollination, and multi-physics coupling. This transformation has significantly enhanced CFD's ability to simulate high-precision fluid flow behavior. However, single serial program calculations can no longer meet the needs of modern engineering computing, especially when large-scale calculations are involved. Therefore, program parallelization has become a key means to improve computational efficiency and expand the scale of operations.

[0004] In CFD, one of the most common parallel computing methods is the domain decomposition method. This involves partitioning the original computational domain into several sub-domains through mesh partitioning, and assigning these sub-domains to different computing cores. Each core independently performs computational tasks, while data between adjacent sub-domains is exchanged through parallel communication mechanisms, thereby completing the parallel computation of the entire computational domain. The quality of the mesh partitioning has a direct impact on the efficiency of parallel computing.

[0005] Currently, there are various mesh partitioning methods, such as METIS and its parallel version PARMETIS for unstructured meshes, and greedy algorithms for structured meshes. While these methods can ensure load balancing and reduce data exchange between computing cores to a certain extent, they generally overlook the importance of flow characteristics in meshing. In particular, in critical flow regions such as the boundary layer, flow separation points, or near shock waves, improper mesh partitioning can lead to loss or distortion of flow characteristics, thus affecting the accuracy of the calculation results and subsequent flow field visualization analysis and data processing.

[0006] Therefore, how to maintain grid partitioning efficiency while ensuring grid integrity in key flow areas has become one of the important technical challenges facing the current CFD field. Summary of the Invention

[0007] The present invention aims to address the prior art problem of parallel computation of multi-partitioned grids, which compromises grid integrity in critical flow regions and thus affects the accuracy of flow field data visualization analysis. Therefore, a method for merging and visualizing multi-partitioned grid flow field data is proposed. By applying a mapping relationship between number information and employing a virtual grid to store and output flow field data, the present invention achieves merging and visualizing flow field data from multiple partitioned grids, ensuring data integrity and laying the foundation for subsequent flow field characteristic analysis.

[0008] The present invention adopts the following technical solutions to achieve the purpose:

[0009] A method for merging and visualizing multi-partition grid flow field data, the method comprising the following steps:

[0010] S1, obtain the original grid and perform grid partitioning process, after partitioning, obtain multiple block grids;

[0011] S2, constructing a grid element mapping relationship between the original grid and each block grid;

[0012] S3. Use CFD technology to calculate and obtain the flow field data corresponding to each block grid;

[0013] S4. According to the grid element mapping relationship, the grid elements of each block grid are indexed to obtain the grid elements corresponding to the original grid, and a virtual grid matching the original grid is reconstructed;

[0014] S5. Reconstruct the grid topology of the virtual grid, and store the flow field data corresponding to each block grid into the corresponding area of ​​the virtual grid to obtain virtual grid information with flow field data;

[0015] S6. Output the virtual grid information to a visualization file to complete the merging and visualization of multi-partition grid flow field data.

[0016] Specifically, in step S1, the original grid is a two-dimensional unstructured grid; the grid elements of the original grid and the block grid both include points, surfaces, cells, and grid blocks.

[0017] Specifically, for grid elements, grid blocks are several areas divided from the flow field calculation domain for independent calculation of flow field data. Each grid block is composed of multiple units, and each grid block stores corresponding flow field data after CFD technology calculation; each unit is defined by multiple points to form a two-dimensional shape, and adjacent units have common points and common surfaces; each surface connects two points and constitutes the boundary of the corresponding unit; each point has a unique number and / or position coordinates, and is a geometric point in the corresponding grid.

[0018] Furthermore, in step S2, the points, surfaces, cells and grid blocks of the original grid before partitioning and the block grid after partitioning are sequentially numbered to obtain corresponding numbering information; based on the numbering information, a grid element mapping relationship is constructed.

[0019] Specifically, based on the numbering information of the original grid and the block grid, the numbers of each type of grid elements at different positions in the block grid are associated with the numbers of the corresponding positions of the same type of grid elements in the original grid, thereby completing the construction of the grid element mapping relationship.

[0020] Specifically, in step S3, the number information of each grid block is obtained and the corresponding CFD calculation process is performed; after the CFD calculation is completed, the calculated flow field data is stored in multiple grid blocks corresponding to the grid block.

[0021] Specifically, the flow field data stored in each grid block includes the density, velocity, pressure and temperature of the flow field area where the grid block is located.

[0022] Furthermore, in step S4, based on the grid element mapping relationship, the numbering information of each block grid is used to index the numbers of the same type of grid elements at corresponding positions in the original grid; and then, based on the numbers obtained by the indexing, the multiple block grids are reconstructed into a virtual grid.

[0023] Specifically, in step S5, based on the reconstructed virtual grid, the topological relationships between the same type of grid elements and different types of grid elements in the virtual grid are analyzed and reconstructed by determining the number of adjacent elements to meet the needs of the visualization file.

[0024] Specifically, after completing the reconstruction of the grid topology, the flow field data stored in multiple grid blocks of the block grid are filled into the corresponding area of ​​the virtual grid, so that the virtual grid has all the flow field data of the flow field calculation domain, thereby forming virtual grid information that can be visualized.

[0025] In summary, due to the adoption of this technical solution, the beneficial effects of the present invention are as follows:

[0026] During the grid partitioning process, the method of the present invention establishes a mapping relationship between the numbering information of the original grid and the partitioned block grids. This method, after the parallel iterative calculation is completed, can reconstruct the virtual grid based on the pre-established mapping relationship, and store the flow field data of each block grid in the corresponding area of ​​the virtual grid, ultimately achieving seamless merging and visualization of flow field data from multiple partitioned grids.

[0027] The proposed method for merging multi-partitioned mesh flow field data not only effectively avoids the loss of mesh integrity often associated with traditional methods in critical flow regions, such as boundary layers, flow separation points, or near shock waves, due to multiple partitions, but also ensures the integrity and consistency of the merged flow field data. This provides a reliable foundation for subsequent flow field characteristic analysis, enhances the credibility of the calculation results, and simplifies the complexity of flow field visualization, thereby improving the accuracy and efficiency of overall computational fluid dynamics simulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A diagram briefly describing the overall process of the method of the present invention;

[0029] Figure 2 is a schematic diagram of the numbering of the two-dimensional unstructured grid in the present invention;

[0030] Figure 3 Schematic diagram of the mapping relationship between grid elements before and after grid partitioning in the present invention;

[0031] Figure 4 Schematic diagram of flow field data in each grid block after CFD calculation in the present invention;

[0032] Figure 5 A schematic diagram of indexing the numbers of similar mesh elements in the original mesh in the present invention;

[0033] Figure 6 is a schematic diagram of a virtual grid reconstructed in the present invention;

[0034] Figure 7 A schematic diagram of a grid topology relationship for reconstructing a virtual grid in the present invention;

[0035] Figure 8 A schematic diagram of storing corresponding flow field data in a virtual grid in the present invention;

[0036] Figure 9 A schematic diagram of the visual output of virtual grid information in the present invention;

[0037] Figure 10 This is a schematic diagram of the flow field results without using flow field data merging in the example;

[0038] Figure 11This is a schematic diagram of the flow field results using flow field data merging in the example. DETAILED DESCRIPTION

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0040] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0041] Example

[0042] A method for merging and visualizing multi-partition grid flow field data. Figure 1 The overall process of the method is briefly described in the following figure, which can be viewed simultaneously. The various steps of the method are summarized as follows:

[0043] S1, obtain the original grid and perform grid partitioning process, after partitioning, obtain multiple block grids;

[0044] S2, constructing a grid element mapping relationship between the original grid and each block grid;

[0045] S3. Use CFD technology to calculate and obtain the flow field data corresponding to each block grid;

[0046] S4. According to the grid element mapping relationship, the grid elements of each block grid are indexed to obtain the grid elements corresponding to the original grid, and a virtual grid matching the original grid is reconstructed;

[0047] S5. Reconstruct the grid topology of the virtual grid, and store the flow field data corresponding to each block grid into the corresponding area of ​​the virtual grid to obtain virtual grid information with flow field data;

[0048] S6. Output the virtual grid information to a visualization file to complete the merging and visualization of multi-partition grid flow field data.

[0049] In this embodiment, the main idea of ​​the method is: first, in the grid partitioning process, a mapping relationship between the original grid before partitioning and the block grid after partitioning is constructed, and the mapping relationship between the point, surface, unit, and grid block numbering information from the original grid to the block grid is recorded. After the CFD calculation is completed and the flow field data of each block grid is obtained, according to the mapping relationship, the point, surface, unit, and grid block numbering information of each block grid is indexed to obtain the point, surface, unit, and grid block numbering information of the original grid and reconstruct the virtual grid. Then, based on the numbering information of the points, surfaces, units, etc. on the newly constructed virtual grid, the grid topology relationship is re-established on the virtual grid. Finally, after the flow field data information of each block grid is stored in the corresponding area of ​​the virtual grid, all the virtual grid information with flow field data is output to the visualization file, thereby realizing the merging and visualization of the flow field data of multiple partition grids.

[0050] This embodiment uses Figure 2 The method process is described in detail using the two-dimensional unstructured grid shown as an example. For two-dimensional unstructured grids, the grid elements of both the original grid and the block grid include points, faces, cells, and grid blocks. Among them, for grid elements, grid blocks are several areas divided from the flow field calculation domain for independent calculation of flow field data. Each grid block is composed of multiple cells. Each grid block stores the corresponding flow field data after CFD calculation. Each cell is defined by multiple points to form a two-dimensional shape, and adjacent cells have common points and common faces. The cells are usually triangles or quadrilaterals. Each face connects two points and constitutes the boundary of the corresponding cell. The face is also the basis for information transmission within and between cells. The face can belong to one or more cells. Each point has a unique number and / or position coordinates. It is a geometric point in the corresponding grid. They define the vertex of the cell. Each point can also be shared by multiple cells.

[0051] exist Figure 2 In the diagram, red numbers represent point numbers, green numbers represent surface numbers, pink numbers represent cell numbers, and blue letters and numbers represent grid block numbers.

[0052] During the grid partitioning process, the grid element mapping relationship between the original grid before partitioning and the block grid after partitioning is constructed, that is, the corresponding relationship between the point, surface, unit, and grid block numbers from the original grid to the block grid is recorded. Figure 3 As shown in the figure, it is a schematic diagram of the grid element mapping relationship before and after grid partitioning. Figure 3 Take the example of a grid block of the original grid being partitioned into two grid blocks of the block grid. Figure 3In the grid element position, the numbers in the brackets represent the numbering information of the original grid, and the numbers outside the brackets represent the numbering information of the block grid; and the elements involved in each grid block are numbered sequentially starting from 0, and the grid blocks themselves are also numbered sequentially starting from 0.

[0053] Then read in the relevant information of the partitioned grid and perform CFD calculations; for the partitioning process of the original grid, it is necessary to obtain the flow field data corresponding to each block grid after the calculation converges. Figure 4 As shown in the figure, pink q0 and green q1 represent the density density, velocity component u along the x-axis, velocity component v along the y-axis, pressure pressure and temperature temperature stored after the CFD calculation is completed on the grid block 0 and grid block 1 of the example, that is, the flow field data.

[0054] According to the previously constructed grid element mapping relationship, the number information of each partitioned grid block is used to index the point, surface, unit, and grid block number information of the original grid. Figure 5 As shown in the figure, arrows of different colors represent the process of obtaining the point, surface, cell, and grid block number information of the original grid by indexing the number information of the block grid. Then, the corresponding grid elements can be determined based on the original grid number information obtained by the index, and a virtual grid that matches the original grid can be reconstructed. The virtual grid can be found in Figure 6 's hint.

[0055] In the reconstructed virtual grid, by determining the number of adjacent elements, the topological relationship between the same type of grid elements and different types of grid elements in the virtual grid is analyzed and reconstructed to meet the needs of visualization files. Figure 7 As shown, Figure 7 In the example, the 0th point, 0th surface and 0th unit of the virtual grid are taken as an example, and the grid topology relationship of the virtual grid is formed by determining the number of adjacent elements of each.

[0056] Similarly, based on the previously constructed grid element mapping relationship and the flow field data stored on each grid block of the block grid after CFD calculation, the flow field data is filled into the corresponding area of ​​the virtual grid. Figure 8 As shown, the flow field data q0 and q1 corresponding to different grid blocks 0 and 1 in the block grid are filled in and stored in the corresponding areas of the virtual grid, thereby forming virtual grid information with flow field data.

[0057] Finally, all the virtual grid information is output to the visualization file. Since it also contains the calculated flow field data, the flow field data of multiple partitioned grids can be merged and visualized. Due to the characteristics of two-dimensional unstructured grids, the integrity of the grid and data in the key flow area is guaranteed after partitioning, mapping, reconstruction and merging. The results of the visualization output are as follows: Figure 9 shown.

[0058] Figure 10 and Figure 11 The following is a comparison of the results of the above method process of this embodiment after performing 4-partition 4-core parallel CFD calculation on a two-dimensional unstructured 30P30N airfoil; Figure 10 The data merging and visualization method of this embodiment is not adopted. Figure 11 The method of this embodiment is adopted.

[0059] according to Figure 10 and Figure 11 The flow field visualization results are compared. After merging the multi-partition grid flow field data using the method of this embodiment, the integrity of the flow field data in the key flow areas near the slats and flaps of the airfoil is guaranteed, and there will be no black gap boundaries formed by the visualization due to the unmerged data. Therefore, a better foundation is laid for the subsequent further flow field characteristic analysis.

Claims

1. A method for merging and visualizing multi-partition grid flow field data, characterized in that: The method comprises the following steps: S1, obtain the original grid and perform grid partitioning process, after partitioning, obtain multiple block grids; S2, constructing a grid element mapping relationship between the original grid and each block grid; S3. Use CFD technology to calculate and obtain the flow field data corresponding to each block grid; S4. According to the grid element mapping relationship, the grid elements of each block grid are indexed to obtain the grid elements corresponding to the original grid, and a virtual grid matching the original grid is reconstructed; S5. Reconstruct the grid topology of the virtual grid, and store the flow field data corresponding to each block grid into the corresponding area of ​​the virtual grid to obtain virtual grid information with flow field data; S6. Output the virtual grid information to a visualization file to complete the merging and visualization of multi-partition grid flow field data; In step S1, the original grid is a two-dimensional unstructured grid; the grid elements of the original grid and the block grid include points, surfaces, cells and grid blocks; In step S2, the points, surfaces, cells, and grid blocks of the original grid before partitioning and the block grid after partitioning are sequentially numbered to obtain corresponding numbering information; and a grid element mapping relationship is constructed based on the numbering information; Based on the numbering information of the original grid and the block grid, the numbers of each type of grid element at different positions in the block grid are associated with the numbers of the corresponding positions of the same type of grid elements in the original grid, thereby completing the construction of the grid element mapping relationship; In step S4, based on the grid element mapping relationship, the numbers of the same type of grid elements at corresponding positions in the original grid are indexed through the numbering information of each block grid; and then, based on the indexed numbers, the multiple block grids are reconstructed into a virtual grid.

2. The multi-partition grid flow field data merging and visualization method according to claim 1 is characterized by: For grid elements, grid blocks are several areas divided from the flow field calculation domain for independent calculation of flow field data. Each grid block is composed of multiple units, and each grid block stores corresponding flow field data after CFD technology calculation; each unit is defined by multiple points to form a two-dimensional shape, and adjacent units have common points and common surfaces; each surface connects two points and constitutes the boundary of the corresponding unit; each point has a unique number and / or position coordinates, and is a geometric point in the corresponding grid.

3. The multi-partition grid flow field data merging and visualization method according to claim 1 is characterized by: In step S3, the number information of each grid block is obtained and the corresponding CFD calculation process is performed; after the CFD calculation is completed, the calculated flow field data is stored in multiple grid blocks corresponding to the grid block.

4. The multi-partition grid flow field data merging and visualization method according to claim 3 is characterized by: The flow field data stored in each grid block includes the density, velocity, pressure and temperature of the flow field area where the grid block is located.

5. The multi-partition grid flow field data merging and visualization method according to claim 1 is characterized in that: In step S5, based on the reconstructed virtual grid, the topological relationships between the same type of grid elements and different types of grid elements in the virtual grid are analyzed and reconstructed by determining the number of adjacent elements to meet the requirements of the visualization file.

6. The multi-partition grid flow field data merging and visualization method according to claim 5 is characterized by: After completing the reconstruction of the grid topology, the flow field data stored in multiple grid blocks of the block grid are filled into the corresponding area of ​​the virtual grid, so that the virtual grid has all the flow field data of the flow field calculation domain, thereby forming virtual grid information that can be visualized.

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