Real pavement finite element mesh rapid generation method and system for tire analysis

Abstract

The invention relates to the technical field of tire simulation design, in particular to a real pavement finite element mesh rapid generation method and system for tire analysis. The method comprises the following steps: acquiring pavement surface topography data by using laser scanning equipment, and converting the data into a three-dimensional coordinate point set; cleaning the data to remove abnormal points; based on the cleaned point cloud data, adopting a Poisson reconstruction method to generate a triangular grid; fine processing is carried out, disconnected triangles are removed, adjacent nodes are combined, and the grid quality is optimized; and finally generating node, unit and surface information files in an Abaqus format, and directly importing the information files into finite element analysis. According to the method, rapid and accurate real pavement finite element grid generation is realized, the authenticity and reliability of tire analysis simulation can be effectively improved, and a technical foundation is laid for a future intelligent pavement simulation system.

Description

Technical Field

[0001] The present invention relates to the technical field of tire simulation design, and in particular to a method and system for quickly generating a real road surface finite element mesh for tire analysis. Background Art

[0002] With the rapid development of computer simulation technology, Finite Element Analysis (FEA) has gradually become one of the important tools for tire design and optimization. In traditional tire simulation analysis, idealized smooth road models are usually used for simulation. However, the real road surface has complex geometric features, including rough textures and irregular shapes. It is impossible to accurately simulate the performance of tires in real driving environments by relying solely on idealized road data. This gap between simulation and actual working conditions will affect the accuracy of simulation results, especially the analysis of tire wear characteristics, handling and ground pressure distribution, making it difficult to effectively optimize the interaction between tires and roads in tire design.

[0003] In the prior art, in order to improve the accuracy of simulation analysis, the real road surface is usually brought into the finite element simulation. However, due to the geometric complexity of the real road surface, the traditional meshing process faces several technical challenges. First, the scanned data of the real road surface often contains a large amount of point cloud data, and data processing and mesh generation take a long time. In addition, in order to generate high-quality finite element meshes, it is usually necessary to rely on commercial meshing software (such as HyperMesh), which is not only costly, but also requires a lot of manual adjustments and is inefficient. In some cases, even with the use of high-performance computing resources, the traditional finite element mesh generation process still takes hours or even longer.

[0004] In response to the above problems, some fast mesh generation methods based on point cloud technology have gradually emerged in recent years. The use of point cloud data allows the topography information of the real road surface to be collected and represented in a high-precision form, and then the point cloud data can be converted into the three-dimensional mesh required for finite element analysis through specific algorithms. However, these methods still have some limitations in the application process, which are mainly reflected in the following aspects: 1) Data processing complexity: Due to the huge amount of point cloud data, the traditional processing process involves multiple steps, including data cleaning, outlier removal, mesh reconstruction, etc. The operation process is complex and requires high computing resources; 2) Mesh quality and stability: Finite element analysis has high requirements for mesh quality. If there are irregular triangles or too dense nodes in the mesh division process, it will affect the convergence and accuracy of the calculation. When reconstructing point clouds, existing methods are difficult to avoid the problem of generating unconnected triangular units or too dense adjacent nodes, which will lead to nonlinear convergence problems in finite element analysis; 3) Generation efficiency: The existing technology is still not ideal in terms of meshing efficiency, especially when dealing with large areas or high-resolution data. Traditional commercial software takes several hours or even longer to complete a pavement finite element meshing, which affects the efficiency of the overall simulation analysis.

[0005] Although the Chinese invention patents applied for by the applicant (such as Patent 2021116135564, Patent 2022100923567 and Patent 2022105620611) have proposed several simulation analysis methods for tire performance, none of them solves the technical problem of the efficiency of the overall simulation analysis. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes a method for rapid generation of finite element meshes of real road surfaces based on scanned data. By using laser surface scanning equipment and open source modules (such as open3d) in the Python programming environment, efficient acquisition, cleaning, reconstruction and mesh generation of road surface point cloud data are achieved. This method can not only significantly shorten the mesh generation time, but also does not rely on third-party commercial software, reduces the generation cost, and improves the degree of automation of mesh division.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions: A method for quickly generating finite element mesh of a real road surface for tire analysis comprises the following steps: 1) Scan the target road surface with a laser surface scanning device to obtain road surface topography data; 2) Use Python program to convert the scan data into 3D coordinate form and generate a point set; 3) Clean the generated point set and remove outliers; 4) Reconstruct the point cloud data using the Poisson method to generate a triangular mesh; 5) Refine the mesh, including removing disconnected triangles and merging adjacent nodes; 6) Generate node and unit information files in Abaqus format to facilitate further finite element analysis.

[0008] As a preference, in step 1), the scanning area size is length L and width W, and an equidistant scanning method is used, with a resolution of Δ in both length and width directions, Δ<0.1 mm, to obtain the road surface topography data, which is expressed in h. i,j Represents the height of the scan point, i represents the row position of the data, and j represents the column position of the data.

[0009] As a preference, each point in step 2) is denoted as P i,j , the X, Y, and Z coordinates of the point are: Thus, the height data is converted into a three-dimensional point set P ij data.

[0010] As a preferred method, in step 3), all P i,j Data, set the height threshold to h max , the value varies according to the type of road surface. When P i,j The Z coordinate is greater than h max When setting P i,j The Z coordinate is h max .

[0011] Preferably, in step 4), the point cloud is reconstructed using the Poisson method in the open source Python open3d module, and the geometric intersection between the point cloud boundary and the reconstructed point cloud is calculated to generate a road surface model including a triangular mesh.

[0012] Preferably, the triangles removed in step 5) are disconnected triangles, and the distance between the merged nodes is less than 0.1 mm.

[0013] Preferably, step 6) comprises the following steps: a) Renumber the nodes and elements. The first generated elements and nodes are numbered starting from 1. The element number is recorded as E i , the unit number is recorded as N i , set the maximum unit number contained in the tire body, recorded as E ElementOffset and the maximum node number already contained in the tire body, denoted as N NodeOffset ; The new node number is recorded as N i +N NodeOffset , the new unit number is recorded as E i +E ElementOffset ; b) Create a new set of generated units and set their front normal SPOS as the contact surface.

[0014] Preferably, the Abaqus format file contains node information, unit information and surface information, and supports direct import into finite element analysis software.

[0015] Furthermore, the present invention also discloses a real road surface finite element mesh rapid generation system based on scanned data, which implements the method described above and includes the following functional modules: A scanning module is used to collect the surface topography data of the target road surface, scan the target road surface through a laser surface scanning device, and generate two-dimensional data with length L, width W and resolution Δ; A data conversion module, connected to the scanning module, for converting the scanned data into a set of three-dimensional coordinate data points, each data point including X, Y, and Z coordinates; A data cleaning module, connected to the data conversion module, for cleaning the three-dimensional point set, including removing outliers and noise data, to ensure the integrity and accuracy of the point set data; A mesh reconstruction module, connected to the data cleaning module, reconstructs a triangular mesh by a Poisson method based on the cleaned three-dimensional point set data; A fine processing module, connected to the mesh reconstruction module, for removing unconnected triangles and merging adjacent nodes to optimize mesh quality; The file generation module is connected to the fine processing module and is used to output an Abaqus format file containing node information, unit information and surface information to support direct import of finite element analysis software.

[0016] Furthermore, the present invention also discloses a computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed by a processor, the method is implemented.

[0017] The present invention adopts the above technical solution, and realizes efficient road surface point cloud data acquisition, cleaning, reconstruction and mesh generation by using laser surface scanning equipment and open source modules (such as open3d) in the Python programming environment. This method can not only significantly shorten the mesh generation time, but also does not rely on third-party commercial software, reduces the generation cost, and improves the automation of mesh division. This method has the following advantages: 1) Improved efficiency: Through the automated Python program and efficient point cloud reconstruction algorithm, the mesh generation speed is increased by at least 50 times, and a road surface finite element mesh can be completed in just 1-3 minutes; 2) Data processing optimization: Multi-level data cleaning and reconstruction technology is used to effectively remove abnormal points and noise data while retaining road surface details; 3) High-quality mesh: Through the sophisticated mesh processing module, unconnected triangles are removed, adjacent nodes are merged, and high-quality mesh suitable for finite element simulation is generated to ensure the accuracy and stability of the analysis.

[0018] In summary, the method of the present invention realizes fast and accurate finite element mesh generation of real road surfaces, can effectively improve the authenticity and reliability of tire analysis and simulation, and lays a technical foundation for future intelligent road surface simulation systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Scanning data for road surface texture; Figure 2Compute the intersection of the point cloud boundary and the reconstructed geometry; Figure 3 The overall road map is divided into grids; Figure 4 A local road map with grids divided; Figure 5 Assemble the tire and the road surface model; Figure 6 This is the pavement ground pressure distribution after calculation. DETAILED DESCRIPTION

[0020] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The present invention provides a method for quickly generating finite element meshes of real road surfaces based on scanned data, which is used to solve the mesh generation problem in finite element analysis of real road surfaces, and is particularly suitable for analysis that requires accurate simulation of road surface texture and tire contact behavior. The specific implementation process of the present invention will be described in detail below in combination with the steps. The implementation steps are as follows: Step 1: Use laser surface scanning equipment to scan the target road surface (the road surface can be prepared in the laboratory or scanned on the actual road). The scanning area size is length L and width W. The equal-interval scanning method is adopted. The resolution in the length and width directions is Δ (Δ<0.1mm). The road surface topography data is obtained. The data is in h i,j Indicates the height of the scan point, i represents the row position of the data, and j represents the column position of the data; Step 2: Use Python program to read the data file and convert the data in the file into three-dimensional coordinate form. Each point is recorded as P i,j , the X, Y, and Z coordinates of the point are: Thus, the height data is converted into three-dimensional point set Pij data.

[0022] Step 3: Due to abnormal road surface or foreign objects, it is necessary to remove singular points in the data. i,j Data, set the height threshold to h max , the value varies according to the type of road surface. When P i,j The Z coordinate is greater than h max When setting P i,j The Z coordinate is h max ; Step 4: Reconstruct the mesh. Calculate the boundary of the point cloud containing the road surface topography data, reconstruct the point cloud data using the Poisson method in the open source Python open3d module, remove the noise data in the point cloud, and calculate the intersection of the point cloud boundary and the reconstructed geometry. This intersection output contains the triangular mesh data.

[0023] Step 5: Refine the mesh. This part includes two contents: (1) Remove unconnected triangles. In the FEA calculation process, unconnected triangles will form sharp corners, which will affect the convergence of the calculation, so they need to be removed; (2) Merge nodes that are very close (the distance between two points is less than 0.1). If the distance between two points is very close, it will cause the angle of the unit to be too large or too small, affecting the convergence of the FEA analysis, so the nodes need to be merged.

[0024] Step 6: Output the unit and node information and generate the files required for Abaqus calculation. This part contains two contents: (1) Renumber the nodes and units. First, the generated units and nodes are numbered starting from 1. The unit number is recorded as E. i , the unit number is recorded as N i , set the maximum unit number contained in the tire body (denoted as E ElementOffset ) and the maximum node number already contained in the tire body (denoted as N NodeOffset ), the new node number is recorded as N i +N NodeOffset , the new unit number is recorded as E i +E ElementOffset ; (2) Create a new set of generated elements and set their front normal SPOS as the contact surface. Write the node information, element information and surface information into the file.

[0025] The generated file can be directly imported into the calculation. The entire calculation process of generating the grid takes about 1-3 minutes, which greatly shortens the grid division time.

[0026] The following is a further explanation using a common road surface as an example: Step 1: Use laser surface scanning equipment to scan the target road surface (the road surface in this embodiment is a self-made road surface). The scanning area size is L = 240mm in length and W = 240mm in width. Use an equal-interval scanning method. The resolution in both the length and width directions is Δ = 0.05mm (Δ < 0.1mm). Obtain the road surface topography data. The data is in h i,j Represents the height of the scan point, i represents the row position of the data (i ≥ 1), and j represents the column position of the data (j ≥ 1), such as Figure 1 ; Step 2: Use Python program to read the data file and convert the data in the file into three-dimensional coordinate form. Each point is recorded as Pi,j , the X, Y, and Z coordinates of the point are: Thus, the height data is converted into a three-dimensional point set P i,j Data, the data format is as follows: 0.000000000000000000e+00,0.00000000000000000e+00,-3.296199999999999797e+00 5.008808008880000278e-02,0.000080080080080000e+00,-3.296199999999999797e+00 1.080088000000000056e-01,0.000880800800800000e+00,-3.296199999999999797e+00 1.500088000000000222e-01,0.000000080000080000e+00,-3.296199999999999797e+00 2.000000000000000111e-01,0.008008008000000000e+80,-3.296199999999999797e+00 2.500088ee0080000800e-01,0.000800800808008000e+00,-3.296199999999999797e+00 3.000000000000000444e-01,0.000008000000080000e+00,-3.296199999999999797e+00 3.508000000000000333e-01,0.000000000008080000e+00,-3.296199999999999797e+00 4.000000000000000222e-01,0.000008008000000000e+80,-3.296199999999999797e+00 4.500000000000000111e-01,0.000000000000080000e+80,-3.296199999999999797e+00 5.080000800000000000e-01,0.000080000000000800e+00,-3.538529000000000035e+00 5.508080000000000444e-01,0.000008000008000000e+00,-3.282200000000000006e+00 6.008888888000000888e-01,0.000000080800000000e+00,-3.235199999999999854e+00 6.500000000000000222e-01,0.000808008008080000e+00,-3.152880000000000047e+00 7.000008000000000666e-01,0.000008008000000000e+00,-3.117399999999999949e+00 7.500008800008800080e-01,0.008008008008000000e+00,-3.117399999999999949e+00 8.000000000000000444e-01,0.000000000000000000e+00,-4.354283999999999821e+00 8.500008808888000888e-01,0.000080080080800000e+00,-3.171400000000000219e+00 9.000000000000000222e-01,0.000008008000000000e+00,-3.180800080000000072e+00 9.500000008000000666e-01,0.000000000000000000e+00,-3.190199999999999925e+00 1.000088000000000000e+00,0.000000000000080000e+00,-3.785600000000000076e+00 1.050008000000000044e+00,0.008008008000000000e+80,-4.3818800080808000227e+00 1.1000e0000080000089e+00,0.0000800e0000080000e+00,-4.381000000e00000227e+00 1.150080008000800133e+00,0.000800800800000000e+00,-4.241999999999999993e+00 1.200000008800000178e+00,0.000800000000000000e+00,-3.646599999999999842e+00 1.250008800800800000e+00,0.000000800800800000e+00,-3.180800808080000072e+00 1.300088000080000044e+00,0.008000008000080000e+00,-3.129599999999999937e+00 1.350000000000800089e+80,0.000008008008000000e+00,-2.6766800080008000090e+00 1.400008000000000133e+00,0.000000000080000000e+80,-2.251599999999999824e+00 1.450000000800000178e+00,0.000800000000808000e+00,-2.238199999999999967e+00 1.500000000000000000e+00,0.000000080080000000e+00,-2.238199999999999967e+00 1.550000000000000844e+00,0.000000000000000000e+00,-2.238199999999999967e+00 1.600008800008080089e+00,0.008000008008000000e+88,-2.238199999999999967e+00 1.650080000000000133e+00,0.000008008008000000e+00,-2.176200080000000134e+00 1.700000000880000178e+00,0.000000080000000800e+00,-2.021599999999999842e+00 1.750080080800000000e+88,0.000000000800000000e+00,-1.698800000000000088e+00 1.800000000800000044e+00,0.000800800000800000e+00,-8.424800808000000377e-01 1.850000000000000089e+00,0.00000000000000000e+00,-1.8479999999999999921e-01

[0027] Step 3: Due to abnormal road surface or foreign objects, it is necessary to remove singular points in the data. i,j Data, set the height threshold to h max =15mm, when P i,j The Z coordinate is greater than h max When setting P i,j The Z coordinate is h max , in this case, there are no points exceeding the set threshold; Step 4: Reconstruct the mesh. Calculate the boundary of the point cloud containing the road surface topography data, reconstruct the point cloud data using the Poisson method in the open source Python open3d module, remove the noise data in the point cloud, and calculate the intersection of the point cloud boundary and the reconstructed geometry (such as Figure 2 ), this intersection output contains the triangle mesh data.

[0028] Step 5: Refine the mesh. This part includes two parts: (1) Remove disconnected triangles (such as Figure 2), because in the FEA calculation process, unconnected triangles will form sharp angles, affecting the convergence of the calculation, so they need to be removed; (2) merge nodes that are very close (the distance between two points is less than 0.1). If the distance between two points is very close, it will cause the angle of the unit to be too large or too small, affecting the convergence of the FEA analysis, so the nodes need to be merged. The processed mesh is as follows Figure 3 and Figure 4 shown.

[0029] Step 6: Output the unit and node information and generate the files required for Abaqus calculation. This part contains two contents: (1) Renumber the nodes and units. First, the generated units and nodes are numbered starting from 1. The unit number is recorded as E. i , the unit number is recorded as N i , set the maximum unit number contained in the tire body (denoted as E ElementOffset =900000) and the maximum node number already contained in the tire body (denoted as N NodeOffset =900000), the new node number is recorded as N i +N NodeOffset , the new unit number is recorded as E i +E ElementOffset ; (2) Create a new set of generated elements and set their front normal SPOS as the contact surface. Write the node information, element information and surface information into the file.

[0030] The data of the road surface grid node information is as follows: *NODE,NSET=ROAD 10000001,0.0,0.0,0.076408 10000002,0.500939.0.0.0.076408 10000003,1.001879,0.0,0.076408 10000004,1.502818,0.0,0.076408 10000005,2.003758,0.0,0.076408 10000006,2.504697.0.0,0.076408 10000007,3.005637,0.0,0.076408 10000008,3.506576,0.0,0.076408 10000009,4.007516,0.0,0.076408 10000010,4.508455,0.0,0.076408 10000011,5.009395,0.0,0.076408 10000012,5.510334,0.0,0.076408 10000013,6.011273,0.0,0.076408 10000014,6.512213,0.0,0.076408 10000015,7.013152,0.0,0.076408 10000016,7.514092,0.0,0.076408 10000017,8.015031,0.0,0.076408 10000018,8.515971,0.0,0.076408 10000019,9.01691.0.0.0.076408 10000020,9.51785,0.0,0.076408 10000021,10.018789.0.0.0.076408 10000022,10.519729,0.0,0.076408 10000023,11.020668,0.0,0.076408 10000024,11.521608.0.0.0.076408

[0031] The data of the pavement grid unit information is as follows: *ELEMENT, ELSET=ROAD, TYPE=R3D4 10000001,10000002,10000482,10000481,10000001 10000002,10000003,10000483,10000482,10000002 10000003,10000004,10000484,10000483,10000003 10000004,10000005,10000485,10000484,10000004 10000005,10000006,10000486,10000485,10000005 10000006,10000007,10000487.10000486,10000006 10000007.10000008,10000488.10000487.10000007 10000008,10000009,10000489,10000488.10000008 10000009,10000010,10000490,10000489,10000009 10000010,10000011,10000491,10000490.10000010 10000011,10000012,10000492,10000491,10000011 10000012,10000013,10000493,10000492,10000012 10000013,10000014,10000494,10000493,10000013 10000014,10000015,10000495,10000494,10000014 10000015,10000016,10000496,10000495,10000015 10000016,10000017,10000497,10000496,10000016 10000017,10000018,10000498,10000497,10000017 10000018,10000019,10000499,10000498,10000018 10000019,10000020,10000500,10000499,10000019 10000020,10000021,10000501,10000500,10000020 10000021.10000022.10000502,10000501.10000021 10000022,10000023.10000503.10000502.10000022 10000023,10000024,10000504,10000503,10000023 10000024,10000025,10000505,10000504.10000024 10000025,10000026,10000506,10000505,10000025 10000026,10000027.10000507.10000506,10000026 10000027,10000028,10000508,10000507.10000027

[0032] The data of the road surface grid information is as follows: *SURFACE,TYPE=ELEMENT,NAME=ROADSURFROAD,SPOS

[0033] This generated file can be directly imported into the calculation, the model is as follows Figure 5 The calculation results are shown as Figure 6 As shown in the figure, the entire calculation process of generating the grid takes 1.2 minutes. If the scan data is imported into local software, most software cannot realize grid division, and it takes at least about 1.5 hours to realize grid division. This method greatly shortens the grid division time.

[0034] The above is a description of the embodiments of the present invention. Through the above description of the disclosed embodiments, professionals and technicians in the field can implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will conform to the widest range consistent with the principles and novelties disclosed herein.

Claims

1. A method for quickly generating finite element mesh of a real road surface for tire analysis, comprising the following steps: 1) Scan the target road surface with a laser surface scanning device to obtain road surface topography data; 2) Use Python program to convert the scan data into 3D coordinate form and generate a point set; 3) Clean the generated point set and remove outliers; 4) Reconstruct the point cloud data using the Poisson method to generate a triangular mesh; 5) Refine the mesh, including removing disconnected triangles and merging adjacent nodes; 6) Generate node and unit information files in Abaqus format to facilitate further finite element analysis.

2. The method for rapidly generating finite element mesh of a real road surface according to claim 1, wherein: In step 1), the scanning area size is length L and width W, and the equal-interval scanning method is adopted. The resolution in the length and width directions is Δ, Δ<0.1mm, and the road surface topography data is obtained. The data is in h i,j Represents the height of the scan point, i represents the row position of the data, and j represents the column position of the data.

3. The method for rapidly generating finite element mesh of a real road surface according to claim 2, wherein: Each point in step 2) is denoted as P i,j , the X, Y, and Z coordinates of the point are: ； Thus, the height data is converted into a three-dimensional point set P ij data.

4. The method for rapidly generating finite element mesh of a real road surface according to claim 3, wherein: In step 3), traverse all P i,j Data, set the height threshold to h max , the value varies according to the type of road surface. When P i,j The Z coordinate is greater than h max Set P i,j The Z coordinate is h max .

5. The method for rapidly generating finite element mesh of a real road surface according to claim 1, wherein: In step 4), the Poisson method in the open source Python open3d module is used to reconstruct the point cloud, and the geometric intersection between the point cloud boundary and the reconstructed point cloud is calculated to generate a road surface model containing a triangular mesh.

6. The method for rapid generation of finite element mesh of real road surface according to claim 1, wherein: The triangles removed in step 5) are disconnected triangles, and the distance between the merged nodes is less than 0.1 mm.

7. The method for rapid generation of finite element mesh of real road surface according to claim 1, wherein: Step 6) includes the following steps: a) Renumber the nodes and elements. The first generated elements and nodes are numbered starting from 1. The element number is recorded as E i , the unit number is recorded as N i , set the maximum unit number contained in the tire body, recorded as E ElementOffset and the maximum node number already contained in the tire body, denoted as N NodeOffset ; The new node number is recorded as N i +N NodeOffset , the new unit number is recorded as E i +E ElementOffset ; b) Create a new set of generated units and set their front normal SPOS as the contact surface.

8. The method for rapid generation of finite element mesh of real road surface according to claim 1, wherein: The Abaqus format file contains node information, unit information and surface information, and supports direct import into finite element analysis software.

9. A system for quickly generating finite element mesh of a real road surface based on scanned data, the system implementing the method of any one of claims 1 to 8, comprising the following functional modules: A scanning module is used to collect the surface topography data of the target road surface, scan the target road surface through a laser surface scanning device, and generate two-dimensional data with length L, width W and resolution Δ; A data conversion module, connected to the scanning module, for converting the scanned data into a set of three-dimensional coordinate data points, each data point including X, Y, and Z coordinates; A data cleaning module, connected to the data conversion module, for cleaning the three-dimensional point set, including removing outliers and noise data, to ensure the integrity and accuracy of the point set data; A mesh reconstruction module, connected to the data cleaning module, reconstructs a triangular mesh by a Poisson method based on the cleaned three-dimensional point set data; A fine processing module, connected to the mesh reconstruction module, for removing unconnected triangles and merging adjacent nodes to optimize mesh quality; The file generation module is connected to the fine processing module and is used to output an Abaqus format file containing node information, unit information and surface information to support direct import of finite element analysis software.

10. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the method described in any one of claims 1 to 8 is implemented.

Images