A Parallel Boundary Layer Mesh Generation Method and Device for Computational Fluid Dynamics

Abstract

The present invention discloses a parallel boundary layer mesh generation method and device for computational fluid dynamics. The method includes: first, generating an initial background mesh with boundary layer elements according to the original CAD geometric model; then, obtaining the physical surface boundary of the background mesh and the mesh elements connected thereto based on the initial background mesh and its topological connection relationship to construct a fixed closed region; further, performing regional decomposition on the initial background mesh using a graph partitioning tool; secondly, densifying the surface mesh of the sub-region; then, performing parallel calculations on the normal vectors of the surface mesh points and the layer advancement distance according to the boundary layer elements, and generating triangular prism elements by applying the layer advancement method; finally, performing quality inspection and intersection judgment on all boundary layer elements to obtain a complete boundary layer mesh. The present invention can make up for the regret of the lack of a parallel generation method for boundary layer meshes in large-scale mesh generation, realize the rapid parallel generation of large-scale boundary layer meshes, and overcome the performance bottleneck in terms of generation efficiency.

Description

Technical Field

[0001] The present invention relates to the field of unstructured grid generation in computational fluid dynamics, and particularly to a parallel boundary layer grid generation method and device for computational fluid dynamics. Background Art

[0002] Partial differential equations (PDEs) are important forms of scientific computing, such as Maxwell's equations in electromagnetic field applications, Navier-Stokes equations and Euler equations in fluid mechanics, etc. These equations can effectively conduct theoretical analysis on related problems. However, in actual engineering, analytical solutions cannot be obtained through direct solution. With the rapid development of computer technology, numerical simulation methods such as the finite element method (FEM), finite difference method (FDM), and finite volume method (FVM) are increasingly used to solve problems in actual engineering.

[0003] The unstructured grid generation technology has currently been widely applied in the field of computational fluid dynamics (CFD), and one of the most typical applications is in the aerospace professional direction. For the critical boundary layer region of viscous flow calculation, tetrahedral grids cannot guarantee the accuracy and efficiency of numerical analysis, and the grids in this region need to maintain a certain structured area. The most common choice is to use flat structured elements in the boundary layer (quadrilateral elements in two dimensions and triangular prism elements in three dimensions) to adapt to the anisotropic physical phenomena nearby; in the region far from the object surface, isotropic unstructured grids (triangle elements in two dimensions and tetrahedron elements in three dimensions) are used to adapt to the complex geometric characteristics of this region. Classical viscous boundary layer grid generation mainly includes two steps: First, starting from the surface grid corresponding to the geometric model, select appropriate parameters such as the initial boundary layer height, growth layer number, layer height ratio, etc., and use the advancing front method to generate triangular prism elements and stop when the elements approach isotropy; then, the closed region from the outermost elements of the triangular prism to the far field is filled with tetrahedrons. The current key research problem lies in how to generate high-quality boundary layer grids for complex geometries.

[0004] In fields such as computational fluid dynamics (CFD) and computational electromagnetics (CEM), grids containing billions or even tens of billions of cells can perform more accurate computational simulations of the problem domain, so large-scale grid generation methods have also attracted much attention. However, it is difficult for serial grid generation algorithms to achieve large-scale grid generation of more than 100 million cells. The upper limit of single-machine memory has become the main limiting bottleneck, and how to ensure the efficiency of grid generation is also a challenging problem. At present, most major numerical simulation software adopts the "quasi-parallel" method of "serial generation + parallel solution", which will inevitably introduce the cost of data conversion and data transmission during the mode switching process. Therefore, it is necessary to develop a true parallel mode, that is, a full-process parallel mode of "parallel generation + parallel solution" to solve these problems.

[0005] At present, the specific steps taken by the commonly used technical solutions are as follows: (1) serially generate a mixed grid containing boundary layer units and tetrahedral units as a background grid; (2) regionally decompose the background grid, and send each part of the sub-grid data after decomposition to each independent core through communication between computer cores; (3) according to a unified unit subdivision template, each core uniformly subdivides each unit of the background grid; (4) using the subdivided grid, geometrically project the grid points of the boundary units of each sub-grid; (5) mesh deform the boundary layer grid near the boundary unit of each sub-grid.

[0006] In summary, the existing methods have the following disadvantages: (1) the transition between the density distribution of mesh cells after subdivision is not optimized; (2) it is necessary to introduce a related geometry engine to perform the mesh-to-geometry projection step, which has a high learning cost and is relatively complex to operate; (3) the mesh deformation takes up a large proportion of time, and this step is sensitive to some parameters set by manual experience. If the values ​​are inappropriate, the mesh quality near the boundary cells may deteriorate or even cause cell distortion and cell intersection. Summary of the invention

[0007] The purpose of the present invention is to provide a parallel boundary layer grid generation method and device for computational fluid dynamics in view of the deficiencies of the prior art.

[0008] The objective of the present invention is achieved through the following technical solutions: In a first aspect, an embodiment of the present invention provides a parallel boundary layer grid generation method for computational fluid dynamics, comprising the following steps:

[0009] (1) The original CAD geometry model is discretized as input to the mesh generation software to generate an initial background mesh with boundary layer elements;

[0010] (2) Extract the boundary layer cells in the initial background grid based on the initial background grid and its topological connection relationship obtained in the step (1), so as to obtain the object surface boundary of the background grid and the grid cells connected thereto, and construct a fixed closed area;

[0011] (3) Perform region decomposition on the surface grid of the object surface boundary obtained in the step (2), and send the surface grid data of each decomposed sub-region to multiple processes;

[0012] (4) Perform parallel isotropic grid encryption on the sub-region surface grids in each process in the step (3);

[0013] (5) Use the encrypted sub-region surface grids in the step (4) as the initial boundary for generating boundary layer cells by the progressive method, perform parallel calculations of the normal vector and the progressive step length distance of the surface grid points according to the boundary layer cells obtained in the step (1), and generate triangular prism cells by applying the progressive method;

[0014] (6) Fill transition cells at the triangular prism cells with different layer heights in the step (5), and perform quality inspection and intersection judgment on all boundary layer cells to obtain a complete boundary layer grid.

[0015] Optionally, the object surface boundary is a surface grid formed by geometric discretization of a CAD model.

[0016] Optionally, the surface grid data includes node numbers, node coordinates, and element topological connections.

[0017] Optionally, the parallel isotropic grid encryption of the sub-region surface grids in each process in the step (4) is realized through the topological structure of the boundary cells of the sub-region surface grids in each process.

[0018] Optionally, the normal vector and the progressive step length distance of the surface grid points in the step (5) are obtained by interpolation calculation based on the boundary layer cells obtained in the step (1).

[0019] Optionally, the normal vector of the surface grid points is obtained by the following formula:

[0020]

[0021] where represents the normal vector at the i-th node of the surface grid element; is the unit length normal vector of the j-th node of the only boundary layer prism element in the background grid that contains this node, and its vector direction is the directed side of this prism element, with the starting point being the point located at the bottom triangle of the triangular prism and the ending point being located at the top triangle; ω j is The weight coefficient.

[0022] Optionally, the layer advancement distance of the surface grid points is obtained according to the following formula:

[0023]

[0024] where L i represents the layer advancement distance value at the i-th node of the surface grid cell; α is the initial layer height scaling factor, that is, the ratio of the height of the current first-layer boundary layer cell to the height of the first-layer cell of the background grid; l j is the side length of the unit corresponding to the j-th node of the prism unit; μ j is the weight coefficient of l j The weight coefficient.

[0025] In the second aspect of the embodiments of the present invention, a parallel boundary layer grid generation device for computational fluid dynamics is provided, which is used to implement the above-mentioned parallel boundary layer grid generation method for computational fluid dynamics. The device includes:

[0026] A construction module, configured to generate an initial background grid with a boundary layer according to the original geometry;

[0027] A preprocessing module, configured to obtain all prism units constituting the boundary layer region and their physical surface boundaries;

[0028] A first processing module, configured to perform regional decomposition of the initial background grid;

[0029] A generation module, configured to adaptively encrypt the distributed surface grid and generate boundary layer cells;

[0030] A second processing module, configured to judge the quality of the boundary layer cells and the possible intersection problems of the grids.

[0031] In the third aspect of the embodiments of the present invention, an electronic device is provided, including a memory and a processor. Among them, the memory is used to store one or more programs, and the processor is used to execute the program data to implement the above-mentioned parallel boundary layer grid generation method for computational fluid dynamics.

[0032] In the fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, they are used to implement the above-mentioned parallel boundary layer grid generation method for computational fluid dynamics.

[0033] The beneficial effects of the present invention are that the present invention can realize the parallel automatic generation of boundary layer grids without manual interaction; the present invention does not need to rely on introducing a geometric engine for geometric projection; the present invention can greatly improve the efficiency of parallel generation of boundary layer grids. Description of the Drawings

[0034] Figure 1 is the overall flowchart of the present invention;

[0035] Figure 2 is the schematic diagram of unit isotropic encryption;

[0036] Figure 3 is the schematic diagram of the conversion from physical coordinates to parametric coordinates;

[0037] Figure 4 is the schematic diagram of invalid boundary layer units;

[0038] Figure 5 is the schematic diagram of the intersection of boundary layer units;

[0039] Figure 6 is the rendering of the boundary layer mesh generation for the DLR-F6 aircraft model;

[0040] Figure 7 is the local rendering of the boundary layer mesh generation at the positions of complex geometric features of the DLR-F6 aircraft model. Detailed implementation manners

[0041] Here, exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims. It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit the present application.

[0042] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms of "a", "the" and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0043] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0044] See Figure 1 , the parallel boundary layer grid generation method for computational fluid dynamics of the present invention, and the specific application field of this method is the generation of large-scale unstructured grids for typical aircraft in the field of computational fluid dynamics. Specifically, this method includes the following steps:

[0045] (1) Discretize the original CAD geometric model as the input of the grid generation software to generate an initial background grid with boundary layer elements.

[0046] Specifically, taking a three-dimensional CAD model file (such as STEP, IGES, etc. formats) as the input, importing it into mainstream grid generation software such as Pointwise, Hypermesh, StarCCM+, etc., after setting basic parameters such as the grid generation type, grid global size value, grid minimum size value, etc., the model can be successfully discretized into a surface grid composed of triangular patches. Conduct a quality check on this surface grid to ensure that all triangular patches do not have problems such as intersection and overlap, and a high-quality initial background grid can be generated, and all triangular patches form a closed three-dimensional region. Taking this as the initial boundary, set boundary layer related parameters, such as the initial layer step length, layer progression growth factor, layer progression maximum number of layers, etc., and call the relevant modules for generating boundary layer grids in the software to output and obtain a complete hybrid grid with boundary layer elements.

[0047] It should be understood that this initial background grid can provide effective input for parallel boundary layer generation.

[0048] (2) Extract the boundary layer elements in the initial background grid according to the initial background grid and its topological connection relationship obtained in step (1) to obtain the physical surface boundary of the background grid and the grid elements connected thereto, so as to construct a fixed closed region.

[0049] In this embodiment, the physical surface boundary is the surface grid formed by geometric discretization of the CAD model. It should be understood that the physical surface boundary is an intermediate output, a process between geometry and the background grid; the closed region is the surface grid of the physical surface as the physical surface boundary.

[0050] Specifically, with triangular patches as the input, the boundary layer cells generated by the progressive method are mainly triangular prism cells. Therefore, the triangles in the surface mesh are the bottom triangles of the first layer of triangular prism cells in the boundary layer mesh, and the top triangles of the first layer of triangular prism cells have the same topological structure as the bottom triangles of the second layer of triangular prism cells, that is, this triangle is shared by two triangular prism cells in two layers, and so on. According to the above structural characteristics, perform a topological structure analysis on the topological connection relationship of the initial background mesh generated in step (1): Starting from the triangles of all surface meshes, all generated triangular prism cells can be obtained layer by layer according to the structural characteristics of the triangular prism cells and the connection relationship between adjacent cells in each layer. Since the surface meshes of the initial background mesh generated in step (1) located at the boundary are closed, correspondingly, all obtained triangular prism cells also form a three-dimensional closed region.

[0051] It should be understood that the closed region constructed in this embodiment provides a source for interpolation calculation for parallel boundary layer mesh generation.

[0052] (3) Decompose the surface mesh of the object surface boundary obtained in step (2), and send the data of each sub-region surface mesh after decomposition to multiple processes.

[0053] Among them, the surface mesh data includes node numbers, node coordinates, element topological connections, etc.

[0054] Specifically, decompose the surface mesh of the object surface boundary obtained in step (2). For example, the surface mesh can be decomposed by the mainstream graph decomposition software Metis. According to the number of processes required for parallelism finally, a complete surface mesh is decomposed into sub-region surface meshes with corresponding numbers and load balancing; and the data such as node numbers, node coordinates, and element topological connections of each sub-region surface mesh after decomposition are sent to each process to realize distributed parallel computing based on multiple processes, and are used as the input for the subsequent boundary layer mesh generation process in the form of a distributed surface mesh.

[0055] It should be understood that the data of each sub-region surface mesh after decomposition can be sent to multiple processes through MPI communication.

[0056] In this embodiment, by decomposing the surface mesh of the object surface boundary, the decomposition of the closed region in step (2) can be realized, and the region for generating the entire boundary layer mesh is divided into independent sub-regions to achieve parallelism.

[0057] (4) Perform parallel isotropic mesh encryption on the sub-region surface meshes in each process in step (3).

[0058] In this embodiment, isotropic mesh encryption is performed in parallel on the sub-region surface meshes in each process, that is, isotropic mesh encryption is performed in parallel in the form of distributed surface meshes, reducing the mesh size value and expanding the scale of the surface mesh.

[0059] In this embodiment, isotropic mesh encryption can be performed in parallel according to the topological structure of the boundary elements of the sub-region surface meshes in each process.

[0060] Specifically, for each mutually independent sub-region surface mesh, each process in parallel simultaneously traverses all triangular patches of the surface mesh, inserts an equal number of new mesh points on each edge, and then connects these new mesh points in sequence to obtain a new list of triangular patches, and removes the original triangles, as Figure 2 shown.

[0061] (5) Using the encrypted sub-region surface meshes in step (4) as the initial boundary for generating boundary layer elements by the progressive method, parallel calculations of the normal vectors and progressive step distances of the surface mesh points are performed according to the boundary layer elements obtained in step (1), and triangular prism elements are generated using the progressive method.

[0062] In this embodiment, the normal vectors and progressive step distances of the surface mesh points are obtained by interpolation calculation using the boundary layer elements obtained in step (1), and parallel boundary layer meshes that do not require communication between processes can be generated. At the same time, high-quality prism elements can be quickly generated using the progressive method.

[0063] Specifically, the normal vector at the i-th node of the surface mesh can be obtained according to the following formula:

[0064]

[0065] where, represents the normal vector at the i-th node of the surface mesh element; is the unit length normal vector of the j-th node of the only boundary layer prism element in the background volume mesh that contains this node, and its vector direction is the directed side of this prism element, with the starting point being the point located at the bottom triangle of the triangular prism and the ending point being located at the top triangle; ω j is the weight coefficient of.

[0066] Furthermore, the calculation formula for the weight coefficient is as follows:

[0067] ω 1 =(1 - u - v)*(1 - w)

[0068] ω 2 =u*(1 - w)

[0069] ω 3= v * (1 - w)

[0070] ω 4 = (1 - u - v) * w

[0071] ω 5 = u * w

[0072] ω 6 = v * w

[0073] Wherein, u, v, and w represent the parametric coordinates of the i-th node of the surface mesh located inside the prismatic element in the boundary layer region. The conversion from physical coordinates to parametric coordinates is as Figure 3 shown. Since the prismatic element adopted contains 6 vertices, the range of j is from 1 to 6; since all the surface meshes taken as input are triangular elements, the range of i is from 1 to 3.

[0074] The layer progression distance of the i-th node of the surface mesh is calculated according to its position inside the prismatic element in the boundary layer region. Specifically, it can be obtained according to the following formula:

[0075]

[0076] Wherein, L i represents the layer progression distance value at the i-th node of the surface mesh element; α is the initial layer height scaling factor, that is, the ratio of the height of the current first boundary layer element to the height of the first layer element of the background mesh; l j is the side length of the element corresponding to the j-th node of the prismatic element; μ j is the weight coefficient of l j , and its calculation method is as follows:

[0077] Project this node onto the three side edges of the boundary layer prismatic element containing it, and calculate the distances between this node and the projection points located on the three side edges respectively, denoted as S 1 S 2 S 3 , so the weight factor

[0078] (6) Fill transition elements at the triangular prism elements with different layer heights in step (5), and perform quality inspection and intersection judgment on all boundary layer elements to obtain a complete boundary layer mesh.

[0079] In this embodiment, the generated boundary layer mesh in parallel is subjected to element validity detection and judgment and processing of possible element intersection problems, and the validity and integrity of the boundary layer mesh are checked.

[0080] Specifically, taking the coordinates of each grid point as the base point, according to the calculation methods of the upper-layer advancing normal vector and the step distance, the result of multiplying the two is used as a displacement increment, and a new coordinate (candidate point) is calculated as the grid point of the higher layer. After confirming the validity of the new coordinate, it replaces the previous grid point and becomes the new base point, and so on. If the newly calculated candidate point exceeds the boundary layer closed area of the background grid, this point is regarded as an invalid point, and the flag to stop advancing is triggered, and the subsequent calculation of the normal vector and the layer advancement step distance is no longer performed. According to the result of the region decomposition in step (3), the surface grids of each sub-region are independent of each other (there is no overlap, interference or intersection of surface triangular patches), and according to the layered connection relationship between triangles and prism elements described in step (2), the closed areas composed of prisms in the background grid are also independent of each other. And since the validity of the background grid generated serially is guaranteed, this strategy can ensure that the newly generated boundary layer elements are completely inside the sub-regions of the prism closed area, thus avoiding the problem of global intersection of elements.

[0081] For models with relatively complex shapes such as space shuttles, invalid results of normal interpolation calculations may also occur at positions with special geometric features locally. The boundary layer grid generation effect of the aircraft model is as Figure 6 shown, and the effect of the local boundary layer grid generated at the position with complex geometric features is as Figure 7 shown. Since the generated boundary layer grids are distributed in parallel processes and there is no interference between sub-regions, it is necessary to perform mesh element quality and intersection detection for each sub-region to ensure the correctness of the mesh. The former ensures that the normal vector calculated by interpolation is valid, that is, no self-intersection or distortion occurs in each unit, as Figure 4 shown; the latter avoids problems such as intersection, overlap, and penetration that may occur between boundary layer elements in the sub-region, as Figure 5 shown. In this embodiment, the isogonal skew index of the mesh element is used to define the deviation degree of any mesh element from the regular element (such as regular triangle, regular tetrahedron). The physical meaning of this index is the cosine value of the minimum dihedral angle in each unit, and the value range is [0,1], where 0 represents the best unit quality and 1 represents the worst unit quality, so that the three-dimensional unit is compressed to be flat, making the unit an invalid unit. Generally, units with a value greater than 0.8 are considered poor-quality units, and units with a value greater than 0.9 are considered unacceptable in quality, so quality optimization or direct deletion is required. Similarly, if pairwise intersection of elements occurs, element deletion is also required to ensure the correctness of the mesh.

[0082] In this embodiment, each link can be automatically completed, which can overcome the dependence on the geometry engine in the prior art solutions, can greatly reduce the time consumption caused by mesh deformation, and improve the efficiency and magnitude of boundary layer mesh generation.

[0083] In summary, finally, a boundary layer mesh applicable to large-scale parallelism can be obtained, including a CAD model with a certain complex geometric shape. Since this embodiment can directly generate the boundary layer mesh in parallel based on the background mesh automatically, without performing complex steps of element subdivision - geometric projection - mesh deformation, it can reduce a large amount of time consumption, generate a mesh that meets the calculation requirements of the numerical solver, and avoid self-intersection problems caused by excessive mesh deformation.

[0084] Corresponding to the foregoing embodiments of the method for parallel boundary layer mesh generation for computational fluid dynamics, the present invention also provides an embodiment of an apparatus for parallel boundary layer mesh generation for computational fluid dynamics.

[0085] It is worth mentioning that the embodiment of the present invention also provides an apparatus for parallel boundary layer mesh generation for computational fluid dynamics, which is used to implement the method for parallel boundary layer mesh generation for computational fluid dynamics in the above embodiments.

[0086] In this embodiment, the apparatus includes a construction module, an extraction module, a first processing module, a generation module, and a second processing module. Among them, the construction module is used to generate an initial boundary layer mesh; the extraction module is used to obtain all the prismatic elements constituting the boundary layer region; the first processing module is used to construct the relationship between the mesh and the weighted dual graph, and perform regional decomposition of the initial background mesh; the generation module is used to adaptively encrypt the distributed surface mesh and generate boundary layer units; the second processing module is used to judge the different layer heights between units, unit quality detection, and intersection processing.

[0087] Regarding the apparatus in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0088] For the apparatus embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial descriptions of the method embodiments. The apparatus embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present application. Those of ordinary skill in the art can understand and implement it without creative work.

[0089] An embodiment of the present invention further provides an electronic device, including a memory and a processor; wherein, the memory is used to store one or more programs; the processor is used to execute program data to implement the parallel boundary layer grid generation method for computational fluid dynamics described in any one of the above embodiments.

[0090] Correspondingly, an embodiment of the present invention further provides a computer-readable storage medium, on which computer instructions are stored, and characterized in that when the instructions are executed by the processor, they are used to implement the above-mentioned parallel boundary layer grid generation method for computational fluid dynamics.

[0091] The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium may also be any device with data processing capabilities, such as a plug-in hard disk, a Smart Media Card (SMC), an SD card, a Flash Card, etc. equipped on the device. Further, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capabilities and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or will be output.

[0092] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A parallel boundary layer grid generation method for computational fluid dynamics, characterized in that: The following steps are involved: (1) The original CAD geometry model is discretized as input to the mesh generation software to generate an initial background mesh with boundary layer elements; (2) extracting boundary layer units in the initial background grid according to the initial background grid obtained in step (1) and its topological connection relationship, so as to obtain the object surface boundary of the background grid and its connected grid units, so as to construct a fixed closed area; (3) performing regional decomposition on the surface mesh of the object surface boundary obtained in step (2), and sending the decomposed surface mesh data of each sub-region to multiple processes; (4) performing parallel isotropic mesh encryption on the surface meshes of the sub-regions in each process in step (3); (5) using the surface meshes of each sub-region encrypted in step (4) as the initial boundaries of the boundary layer units generated by the layer-wise method, performing parallel calculations of the normal vectors of the surface mesh points and the layer-wise step length based on the boundary layer units obtained in step (1), and applying the layer-wise method to generate triangular prism units; (6) Fill transition units at the triangular prism units of different layer heights in step (5), and perform quality inspection and intersection judgment on all boundary layer units to obtain a complete boundary layer grid.

2. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 1, characterized in that: The object surface boundary is a surface mesh formed by geometric discretization located in the CAD model.

3. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 1, characterized in that: The surface mesh data includes node numbers, node coordinates and unit topological connections.

4. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 1, characterized in that: In the step (4), the parallel isotropic mesh encryption of the sub-region surface meshes in each process is achieved through the topological structure of the boundary cells of the sub-region surface meshes in each process.

5. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 1, characterized in that: The normal vectors and layer step lengths of the surface grid points in step (5) are obtained by interpolating the boundary layer units obtained in step (1).

6. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 5, characterized in that: The normal vector of the surface grid point is obtained by the following formula: in, Represents the normal vector at the i-th node of the surface mesh unit; is the unit length normal vector of the jth node of the only boundary layer prism unit in the background grid that contains this node. Its vector direction is the directed side of the prism unit. The starting point is the point located at the bottom triangle of the triangular prism and the end point is located at the top triangle. j for The weight coefficient of .

7. The parallel boundary layer grid generation method for computational fluid dynamics according to claim 5, characterized in that: The layer-by-layer distance of the surface grid points is obtained according to the following formula: Among them, L i represents the layer distance value at the i-th node of the surface grid unit; α is the initial layer height scaling factor, that is, the ratio of the current first layer boundary layer unit height to the first layer unit height of the background grid; l j is the length of the element side corresponding to the jth node of the prismatic element; μ j for l j The weight coefficient of .

8. A parallel boundary layer grid generation device for computational fluid dynamics, used to implement the parallel boundary layer grid generation method for computational fluid dynamics as claimed in any one of claims 1 to 7, characterized in that: The device comprises: A construction module for generating an initial background mesh with a boundary layer based on the original geometry; A preprocessing module, used to obtain all prismatic elements and their object surface boundaries constituting the boundary layer region; A first processing module is used for performing regional decomposition of an initial background grid; Generation module, used for adaptive encryption of distributed surface meshes and generation of boundary layer units; The second processing module is used to determine the quality of the boundary layer units and possible intersection problems of the grid.

9. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory is used to store one or more programs, and the processor is used to execute the program data to implement the parallel boundary layer grid generation method for computational fluid dynamics as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the instructions are executed by a processor, they are used to implement the parallel boundary layer grid generation method for computational fluid dynamics described in any one of claims 1 to 7.

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