A method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm

Abstract

The present invention proposes a method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm, belonging to the field of numerical simulation technology. First, a general grid data format is defined to store the geometric information of the grid, making it independent of the dimension and cell type of the grid. The number of real grid cells, the total number of all cells, the grid cell data structure, the grid sub-cell data structure, and the grid cell face data structure are defined respectively. Then, the traditional grid data is converted into the new general format, and a numerical simulation program suitable for the new data format is written to ensure that the new program can correctly process grids of different dimensions and types, and verify its accuracy. The present invention does not depend on the specific shape and dimension of the grid, does not need to save the dimension and cell type information of the grid, and only needs to write the code once to be applicable to calculation grids of any dimension and cell type.

Description

Technical Field

[0001] The present invention belongs to the technical field of numerical simulation, and specifically relates to a method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm. Background Art

[0002] With the rapid development of computer science and technology, numerical simulation technology has been applied in more and more fields. The numerical simulation method is to discretize the equation (or system of equations) to be solved on a computational grid to obtain a discrete system of equations that is compatible with the original equation (or system of equations), and then use a computer to solve the discrete system of equations to obtain an approximate solution of the original equation (or system of equations).

[0003] Since discretization needs to be performed on a computational grid, usually the form of the discrete system of equations is closely related to the computational grid. Different dimensions and different cell shapes of the computational grid result in different discrete systems of equations. Taking the finite volume method commonly used in fluid mechanics numerical simulation as an example: when calculating the flux through the side face of a grid cell, a one-dimensional cell is a straight line segment and its side face is a point, so the calculation of the flux does not need to consider the size of the side face; while the side face of a two-dimensional cell is an edge, and the length of the edge needs to be considered when calculating the flux; similarly, the side face of a three-dimensional cell is a plane, and the area of the plane needs to be considered when calculating the flux. In this way, when designing numerical simulation algorithms and writing numerical simulation software, different algorithms need to be designed and different software needs to be written according to different computational grid dimensions and different grid cells used. This greatly increases the workload of algorithm design and simulation software development. Summary of the Invention

[0004] To solve the above problems, the present invention proposes a method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm, which does not depend on the specific shape and dimension of the grid and converts the geometric information of all grids into a unified format.

[0005] The present invention is realized through the following technical solutions:

[0006] A method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm,

[0007] The method specifically includes the following steps:

[0008] Step 1: Define a general grid data format according to the CESE algorithm to store the geometric information of the grid, making it independent of the dimension and cell type of the grid;

[0009] Step 2: Convert the grid data, converting the traditional grid data into a new general format;

[0010] Step 3: Build a simulation framework suitable for the new data format in Step 2;

[0011] Write code to handle the calculations of grid cells, sub-cells, and cell faces; implement time stepping and spatial discretization in the CESE algorithm; ensure that the program can handle grids of arbitrary dimensions and cell types;

[0012] Step 4: Test and verify. Select grids of different dimensions and types for testing to ensure that the new program can correctly handle grids of different dimensions and types, and compare with known solutions or the results of traditional methods to verify its accuracy;

[0013] Step 5: Optimize the program based on the test results to improve efficiency and accuracy.

[0014] Furthermore, in Step 1, specifically:

[0015] Define the number of real grid cells Nre and the total number of all cells Ne;

[0016] Define the data structure of grid cell Element, including volume, center point coordinates, and the group of adjacent cell numbers;

[0017] Define the data structure of grid sub-cell SubElement, including the volume of the sub-cell, center point coordinates, and the numbers of the two cells that make up the sub-cell;

[0018] Define the data structure of grid cell face Face, including the area of the cell face, center point coordinates, unit outer normal vector components, and the numbers of the adjacent grid cells.

[0019] Furthermore, in Step 1, the defined general grid data format is:

[0020]

[0021] where Nse is the number of grid sub-cells and Nf is the data of grid cell faces.

[0022] Furthermore, in Step 2, specifically:

[0023] Calculate the volume (Volume) of each grid cell; determine the coordinates (X, Y, Z) of the center point of each grid cell; determine the group of adjacent cell numbers of each grid cell;

[0024] Calculate the volume and center point coordinates of each sub-cell; determine which two cells each sub-cell is composed of;

[0025] Calculate the area and center point coordinates of each cell face; determine the unit outer normal vector of each cell face; determine the numbers of the adjacent grid cells of each cell face.

[0026] Furthermore, the definition of the grid cell Element is as follows:

[0027]

[0028] The definition of the grid sub - cell SubElement is as follows:

[0029]

[0030] The definition of the grid cell face Face is as follows:

[0031]

[0032] Furthermore, in step 3, the simulation framework includes a core calculation module, an input - output module, and an interaction interface;

[0033] The input - output module is used to read network data, parse the data structures of Element, SubElement, and Face, construct a grid data structure based on the parsed data, and output the simulation structure;

[0034] The core calculation module is used to write functions to calculate the volume of grid cells, the volume of sub - cells, and the area of cell faces, and implement the CESE algorithm;

[0035] The interaction interface is used for display, user interaction, and control.

[0036] An electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above - mentioned method are implemented.

[0037] A computer - readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the steps of the above - mentioned method are implemented.

[0038] Advantages of the present invention

[0039] The present invention proposes a new general grid data format applicable to the CESE method. Different from the traditional grid data recording format, the new format no longer needs to save the dimension and cell type information of the grid, but converts the grid geometric information into data such as area, coordinates, and normal vectors. Regardless of the specific shape and dimension of the grid, all grid geometric information (such as volume, area, coordinates, etc.) is converted into a unified format, and grids of any shape or dimension can be processed by the same method.

[0040] The advantages of the present invention over the existing methods are mainly reflected in two aspects:

[0041] First, traditional grid data formats require different data storage formats for different dimensions and different cell types, and the organizational structure of grid information is complex. In contrast, the new data format of the present invention uses the same organizational structure for grids of different dimensions and different cell types, thus greatly simplifying the data structure of the grid and facilitating the reading and writing of grid data.

[0042] Second, when writing numerical simulation programs, using traditional grid data formats requires writing corresponding calculation codes for various dimensions and grid cell types respectively. The work of writing and debugging the program is extensive, and the development time is long. However, when using the new format proposed by the present invention, only one piece of code needs to be written, which can be applied to computational grids of any dimension and cell type. In this way, the development speed of numerical simulation programs can be greatly accelerated, and the development time can be saved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of a two-dimensional unstructured triangular grid in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] The experimental methods used in the following embodiments are all conventional methods unless otherwise specified. The materials, reagents, methods, and instruments used are all conventional materials, reagents, methods, and instruments in this field, and those skilled in the art can obtain them through commercial channels without special instructions.

[0046] Among various computational fluid dynamics methods, the Space-Time Conservation Elements and Solution Elements method (generally abbreviated as: CESE method) is a class of high-precision finite volume methods. This method discretizes the governing equations simultaneously in both the spatial and temporal dimensions, is a multi-dimensional algorithm, and has relatively high computational accuracy. Like traditional finite volume methods, this method uses unstructured grids as computational grids.

[0047] The data of unstructured grids generally includes at least the following parts:

[0048] 1) The dimension of the grid;

[0049] 2) Coordinates of all grid nodes, and the above node coordinates should be arranged in a certain order. According to different dimensions, the number of parameters representing node coordinates is different: for a two-dimensional grid, each node requires two coordinate parameters; while for a three-dimensional grid, each node's coordinates require three coordinate parameters;

[0050] 3) Types of grid cells;

[0051] 4) Composition of all grid cells.

[0052] However, when using the CESE method for numerical simulation, the calculation program does not directly use the above unstructured grid data, but uses a transformed form of the above data.

[0053] Taking the solution of the Euler equations using the CESE method as an example. The general form of the Euler equations is as follows:

[0054]

[0055] Among them,

[0056]

[0057] In the formula, ρ represents density, u, v, and w are the components of velocity in three directions, E represents total internal energy, and p represents pressure.

[0058] Therefore, on any grid cell, the formula for the CESE algorithm to calculate the parameter values at the n+1 time level is:

[0059]

[0060] In the formula, m is the number of side faces of the grid cell and the number of sub-cells. The number of outer side faces of the grid cell is equal to the number of sub-cells. S i is the area of the i-th side face, V i is the volume of the i-th sub-cell, V is the volume of the entire grid cell, and it satisfies:

[0061]

[0062] In addition,

[0063]

[0064] is the spatial unit outer normal vector of the i-th side face;

[0065]

[0066] is the parameter value at the center point of the i-th side face, which is calculated by first-order Taylor series interpolation using the parameters at the n-th time level corresponding to the boundary face (the parameters at the n-th time level are known parameters); is the parameter value at the center point of the $i$-th sub-unit, which is calculated by using the first-order Taylor series interpolation of the parameters at the $n$-th time layer corresponding to the sub-unit; $\Delta t$ is the time step.

[0067] It can be seen from here that the geometric information used in the calculation formula includes: the volume of the grid cell, the number of sub-units and boundary faces, the volume of the sub-unit, the area of the boundary face, and the spatial distance between the sub-unit and the boundary face cell to the known parameter point. Obviously, the specific type information of the grid cell is not required here. If both one-dimensional and two-dimensional coordinates are extended to three dimensions (only need to set the values in the extra dimensions to 0), then the calculation formulas for grids of different dimensions will also be consistent in form (both adopt the three-dimensional format).

[0068] From the above analysis, it can be seen that the geometric data information representing the grid cell can be completely converted into the above-mentioned abstract geometric data that is independent of the grid cell and dimension, and a numerical simulation algorithm can be constructed based on the above geometric data. In this way, only one set of numerical simulation algorithms and calculation programs is needed to perform numerical simulations on the computational grids of any grid cell type and dimension, thus greatly reducing the workload of constructing numerical simulation algorithms and writing programs.

[0069] Therefore, the present invention proposes a method for constructing a general numerical simulation computational grid data format based on the CESE algorithm, which is characterized in that:

[0070] The method specifically includes the following steps:

[0071] Step 1: Define a general grid data format according to the CESE algorithm; that is, create a new data format to store the geometric information of the grid, making it independent of the dimension and cell type of the grid;

[0072] Define the number of real grid cells $N_{re}$ and the total number of all cells $N_e$;

[0073] Define the data structure of the grid cell Element, including volume, center point coordinates, and an array of adjacent cell numbers;

[0074] Define the data structure of the grid sub-unit SubElement, including the volume of the sub-unit, center point coordinates, and the numbers of the two cells that make up the sub-unit;

[0075] Define the data structure of the grid cell face Face, including the area of the cell face, center point coordinates, unit outer normal vector components, and the numbers of the adjacent grid cells.

[0076]

[0077] Nre is the number of real grid cells, and Ne is the total number of all cells including real grid cells and virtual grid cells. Here, real grid cells refer to the grid cells located within the computational domain, and virtual grid cells refer to the grid cells added outside the grid domain for additional calculations.

[0078] Element is the data structure of grid cells (real grid cells and virtual grid cells), and the specific definition is as follows.

[0079] 1) Definition of grid cells

[0080]

[0081] Nse is the number of grid sub - elements, and SubElement is the data structure of grid sub - elements, and the specific definition is as follows.

[0082] 2) Definition of grid sub - elements

[0083]

[0084] Nf is the data of grid cell faces, and Face is the data structure of grid cell faces, and the specific definition is as follows:

[0085] 3) Definition of grid cell faces

[0086]

[0087]

[0088] Taking a triangular element and its adjacent elements as an example, the specific explanations of the parameters in the above data structure are as follows. As Figure 1 shown, the triangular element is composed of points A, B, and C, and it has three adjacent elements, namely triangles ABD, ACE, and BCF. Points O, P, Q, and R are the geometric centers of triangles ABC, ABD, ACE, and BCF respectively. Each grid is divided into three sub - domains according to its boundary edges. In the figure, triangle ABC is divided into three sub - domains: triangles ABO, BCO, and CAO. The adjacent sub - domains of adjacent grid cells form a grid sub - element. Figure 1 In [reference], the quadrilateral AQBO is a grid sub - element, which is jointly composed of two sub - domains (triangle ABO and triangle ABQ). The boundary edge of the grid cell (for example: Figure 1 the line segment AB in [reference]) is a grid cell face.

[0089] Step 2: Convert grid data. Convert the traditional grid data into a new general format.

[0090] Calculate the volume of each grid cell; determine the coordinates (X, Y, Z) of the center point of each grid cell; determine the group of adjacent cell numbers for each grid cell;

[0091] Grid cell (Element): Record the volume, center point coordinates, and information of adjacent cells of each grid cell.

[0092] Calculate the volume and center point coordinates of each sub-cell; determine which two cells each sub-cell consists of;

[0093] Grid sub-cell (SubElement): Record the volume and center point coordinates of the part (sub-cell) shared by two grid cells.

[0094] Calculate the area and center point coordinates of each cell face; determine the unit outer normal vector of each cell face; determine the grid cell numbers adjacent to each cell face.

[0095] Grid cell face (Face): Record the area, center point coordinates, and information of adjacent cells of the face (such as an edge or a plane) of the grid cell.

[0096] Step 3: Build a simulation framework suitable for the new data format in Step 2;

[0097] Write code to handle the calculations of grid cells, sub-cells, and cell faces; implement the time stepping and spatial discretization in the CESE algorithm; ensure that the program can handle grids of arbitrary dimensions and cell types;

[0098] Take the grid in Figure 1 as an example to illustrate the meanings of the parameters in the data structures of grid cells, grid sub-cells, and grid cell faces:

[0099] 1) Element data structure

[0100] Volume refers to the volume of the grid cell. For example, in Figure 1 , for the grid cell triangle ABC, Volume is the area of triangle ABC. Note: Figure 1 is a two-dimensional grid, so the so-called volume of the grid cell is actually the area of the grid cell. If it is a one-dimensional grid, the volume of the grid cell is actually the length of the grid cell. Only for a three-dimensional grid, Volume is the actual volume of the grid cell. However, whether it is length, area, or volume, numerically it is a floating-point number. From the perspective of the data file, there is no difference among the three. X, Y, Z are the coordinate components of the center point of the grid cell. For Figure 1In the triangular ABC element, these are the coordinates of point O. Similarly, since the triangular ABC is a two-dimensional element, the center point has only two coordinates, X and Y. In this case, Z needs to be assigned a value of 0 to complete the three coordinates. Similarly, for a one-dimensional element, Y and Z both need to be assigned a value of 0. N is the number of groups of adjacent element numbers. Then there are groups of three adjacent element numbers. The composition method of the number group is as follows: Connect the center points of all adjacent elements in pairs, and take the outer boundary of the formed geometric shape. Then the element numbers connected by each outer boundary form a number group. For example Figure 1 In it, the center points of the adjacent elements of the triangular ABC are points P, Q, and R. These three points form the triangle PQR. The boundaries of the triangle are the line segments PQ, QR, and PR. Thus, the numbers of the triangles ACE and ABD, the triangles ABD and BCF, and the triangles BCF and ACE form three groups of number groups. Figure 1 Because it is a two-dimensional grid, each number group has only two numbers. The following number needs to be repeated once to form a number group of three numbers. If it is a one-dimensional grid, it needs to be repeated twice.

[0101] 2) SubElement data structure

[0102] Volume refers to the volume of the subelement. For example Figure 1 In it, for the subelement AQBO, it refers to the area of the quadrilateral AQBO. Similar to the grid element, only for a three-dimensional element, Volume is the actual volume. For a two-dimensional element, Volume is actually the area, and for a one-dimensional element, it is actually the length. X, Y, and Z are the coordinate components of the center point of the subelement. For example, for the subelement AQBO, these three numbers are the coordinates of the geometric center of the quadrilateral AQBO. Similarly, for subelements with less than three dimensions, the missing coordinate parameters need to be assigned a value of 0 to complete the three coordinates. Each subelement is composed of a sub-domain combination of two elements. The El and Er parameters are the numbers of these two elements.

[0103] 3) Face data structure

[0104] Area refers to the area of the element face. For a two-dimensional element, the element face is a line segment (for example, line segment AB is an element face of element ABC), which has only length. Therefore, Area is actually the length of the boundary line segment. If it is a one-dimensional element, the boundary is a point, and in this case, Area is directly assigned a value of 1. Only for three-dimensional elements, Area is the real area. Similarly, for meshes of different dimensions, the physical meaning of the element face area is different, but they are all floating-point numbers and there is no difference in the data format. X, Y, and Z are the coordinate components of the center point of the element face, Nx, Ny, and Nz are the components of the unit outer normal vector of the element face, and El and Er are the numbers of the mesh elements adjacent to the element face. Note that the unit outer normal vector needs to point from mesh element El to mesh element Er. As before, if the mesh dimension is less than three, the missing components need to be filled in.

[0105] As can be seen from the above definitions, the mesh data does not contain either the mesh dimension parameter or the mesh element type parameter. That is, for computational meshes of any dimension and element type, their mesh data is the same in form.

[0106] The simulation framework includes a core calculation module, an input / output module, and an interactive interface;

[0107] The input / output module is used to read network data, parse the data structures of Element, SubElement, and Face, construct a mesh data structure based on the parsed data, and output the simulation structure;

[0108] The core calculation module is used to write functions to calculate the volume of mesh elements, the volume of sub-elements, and the area of element faces, and implement the CESE algorithm;

[0109] The interactive interface is used for display, user interaction, and control.

[0110] Step 4: Testing and verification. Select meshes of different dimensions and types for testing to ensure that the new program can correctly process meshes of different dimensions and types, and compare with known solutions or the results of traditional methods to verify its accuracy;

[0111] Step 5: Optimize the program according to the test results to improve efficiency and accuracy.

[0112] An electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0113] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the steps of the above method are implemented.

[0114] The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the method described in the present invention is intended to include but not limited to these and any other suitable types of memory.

[0115] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire, such as coaxial cable, optical fiber, digital subscriber line (DSL), or wirelessly, such as infrared, wireless, microwave, etc. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device, such as a server, data center, etc., that includes one or more integrated available media. The available media may be a magnetic medium, such as a floppy disk, hard disk, magnetic tape, an optical medium, such as a high-density digital video disc (DVD), or a semiconductor medium, such as a solid state disc (SSD), etc.

[0116] In the implementation process, the steps of the above method can be completed by the integrated logic circuit of the hardware in the processor or the instructions in the form of software. The steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by the hardware processor or completed by the combination of the hardware and software modules in the processor. The software module may be located in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0117] It should be noted that the processor in the embodiments of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the above method embodiments can be completed by the integrated logic circuit in the hardware of the processor or instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0118] The above has introduced in detail a method for constructing a general numerical simulation calculation grid data format based on the CESE algorithm proposed by the present invention, and expounded on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for constructing a universal numerical simulation computing grid data format based on a CESE algorithm, characterized in that: The method specifically comprises the following steps: Step 1: Define a general mesh data format based on the CESE algorithm to store the geometric information of the mesh, making it independent of the dimension and cell type of the mesh; Define the number of real grid cells Nre and the total number of all cells Ne; Define the data structure of the grid cell Element, including volume, center point coordinates and adjacent cell number groups; Define the data structure of the grid sub-unit SubElement, including the volume of the sub-unit, the coordinates of the center point and the serial numbers of the two units that constitute the sub-unit; Define the data structure of the mesh unit face Face, including the unit face area, center point coordinates, unit external normal vector components and adjacent mesh unit numbers; Step 2: Convert the grid data, convert the traditional grid data into a new universal format; Calculate the volume of each grid cell (Volume); determine the coordinates (X, Y, Z) of the center point of each grid cell; determine the adjacent cell number group of each grid cell; Calculate the volume and center point coordinates of each subunit; determine which two units each subunit is composed of; Calculate the area and center point coordinates of each unit face; determine the unit external normal vector of each unit face; determine the grid unit number adjacent to each unit face; Step 3: Build a simulation framework suitable for the new data format in step 2; Write code to handle computations on mesh cells, subcells, and cell faces; implement time stepping and spatial discretization in the CESE algorithm; ensure the program can handle meshes of arbitrary dimensions and cell types; In step 3, the simulation framework includes a core computing module, an input and output module, and an interactive interface; The input and output module is used to read network data, parse Element, SubElement and Face data structures, build a mesh data structure based on the parsed data, and output a simulation structure; The core calculation module is used to write functions to calculate the volume of grid cells, the volume of sub-cells and the area of ​​cell faces, and implement the CESE algorithm; The interactive interface is used for display, user interaction and control; Step 4: Test and verify. Select grids of different dimensions and types for testing to ensure that the new program can correctly handle grids of different dimensions and types. Compare the results with known solutions or traditional methods to verify its accuracy. Step 5: Optimize the program based on the test results to improve efficiency and accuracy.

2. The method according to claim 1, characterized in that: In step 1, the general grid data format is defined as: Where Nse is the number of grid sub-elements and Nf is the data of the grid cell face.

3. The method according to claim 2, characterized in that: The definition of grid unit Element is: The definition of grid sub-unit SubElement is: The mesh element face Face is defined as:

4. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

5. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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