Finite element mesh automatic division method and system

Abstract

The invention provides a finite element mesh automatic division method and system. The division method comprises the steps that key features of a target geometric model are extracted; calling a first grid division computer program to perform hexahedral grid division on the key feature region; calling a first grid division computer program to perform hexahedral grid division on the important area; if the hybrid grid division succeeds, calling a second grid division computer program to perform tetrahedral grid division on the non-important region, and then outputting a hybrid grid and tetrahedral grid file; and if the hybrid grid division fails, calling a third grid division computer program to perform tetrahedral grid division on the important region and the non-important region, and then outputting a tetrahedral grid file. According to the dividing method, the first grid dividing computer program, the second grid dividing computer program and the third grid dividing computer program are used for conducting grid dividing on the key features of the target geometric model, and the grid dividing quality can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of finite element analysis, and in particular to a finite element mesh automatic division method and system. Background Art

[0002] In finite element analysis, the quality of the finite element mesh has an important influence on the accuracy and speed of finite element analysis. A good mesh makes the finite element analysis fast and good.

[0003] For 3D models, the best mesh currently is a hexahedral mesh, followed by a wedge mesh. Although second-order or higher-order tetrahedral meshes can also achieve high accuracy, the computational complexity is still relatively high. Second-order hexahedral meshes, however, are fewer in number and offer faster computational speeds.

[0004] To achieve hexahedral meshing or hexahedral-based meshing, meshing takes up more than 50% of the engineering time, and for some models, meshing takes up more than 70% of the time. Therefore, meshing is an important function of finite element analysis software.

[0005] Existing commercial finite element software has the function of finite element mesh division, such as ANSYS, ABAQUS and NASTRAN, all of which have mesh division functions. However, for complex geometric models, these software cannot directly obtain good hexahedral meshes.

[0006] In addition, HyperMesh and ICEM are software specifically used for finite element meshing, but using these finite element meshing software, meshing still takes a lot of time.

[0007] Specifically, HyperMesh primarily uses geometric segmentation to reduce the shape complexity of geometric entities, ensuring that each geometric partition meets mapping conditions, thereby achieving finite element meshing. However, Boolean operations on complex geometries are slow and unstable (often crashing), and manual cutting is labor-intensive.

[0008] ICEM reduces geometric complexity through block partitioning, but it has very high requirements for the mapping between geometry and blocks. Actual mesh division requires an overall partitioning concept and requires users to accumulate more experience.

[0009] ANSYS has difficulty in implementing hexahedral meshing. When the geometry is complex, a hexahedron-based mesh is generally used. The geometric surface is divided into quadrilaterals and then stretched into the interior of the geometry to form a hexahedron. A large number of tetrahedrons and transition meshes are still required to fill the interior.

[0010] The meshing of ABAQUS is mainly based on tetrahedrons. Hexahedral meshes can only be obtained when the geometry is simple and easy to map.

[0011] In practical engineering, if mesh quality requirements are low, tetrahedral mesh calculations can be used. Automatic tetrahedral mesh generation already has mature theories and programs, and can be directly called to automatically generate tetrahedral meshes. Finite element software such as ANSYS, ABAQUS, and NASTRAN can all achieve this. However, when mesh quality requirements are very high, specialized finite element meshing software such as HyperMesh and ICEM is required, which consumes a significant amount of time to generate hexahedral meshes.

[0012] The technology for automatically generating hexahedral meshes for arbitrary 3D models is currently immature, with no commercially available software implementing this functionality. Many papers only address specific types of 3D models, using customized programs to automatically generate hexahedral meshes. This approach, however, renders meshing impossible for a specific part, resulting in limited generalizability. Papers investigating automated hexahedral mesh generation methods, tested using model libraries, have found that generating hexahedral meshes for highly complex geometries, such as impellers, valve bodies, and steam generator lower heads, is difficult.

[0013] Based on this, the inventors of this application designed a finite element mesh automatic division method and system to overcome the above technical problems. Summary of the Invention

[0014] The technical problem to be solved by the present invention is to overcome the defects of the prior art in that meshing of complex geometric models takes a long time or the mesh quality is low, and to provide a finite element mesh automatic partitioning method and system.

[0015] The present invention solves the above technical problems through the following technical solutions:

[0016] A first aspect of the present invention provides a method for automatic finite element mesh generation, which is characterized by comprising:

[0017] Step 1: Extract key features of the target geometric model;

[0018] Step 2: Calling a first meshing computer program to perform hexahedral meshing on the key feature area; if the hexahedral meshing is successful, outputting a hexahedral mesh file; if the hexahedral meshing fails, partitioning the key feature area and selecting important areas and non-important areas;

[0019] Step 3: calling the first meshing computer program to perform hexahedral meshing on the important area; if the hexahedral meshing is successful, calling the second meshing computer program to perform tetrahedral meshing on the non-important area, and then outputting hexahedral and tetrahedral mesh files; if the hexahedral meshing fails, calling the third meshing computer program to perform mixed meshing on the important area;

[0020] Step 4. In step 3, if the hybrid mesh division is successful, the second mesh division computer program is called to perform tetrahedral mesh division on the non-important area, and then the hybrid mesh and the tetrahedral mesh file are output; if the hybrid mesh division fails, the third mesh division computer program is called to perform tetrahedral mesh division on the important area and the non-important area, and then the tetrahedral mesh file is output.

[0021] According to one embodiment of the present invention, in step 1, the key features of the target geometric model are extracted by automatically analyzing the complexity of the target geometric model; wherein, the complexity is evaluated based on one or more of the number of geometric features, topological structure and surface complexity.

[0022] According to one embodiment of the present invention, after the hexahedral mesh is successfully divided in step 2, a quality analysis is performed on the hexahedral mesh; if the quality analysis is qualified, the hexahedral mesh file is output; if the quality analysis is unqualified, the mesh mapping is adjusted to generate a hexahedral mesh file that meets the requirements.

[0023] According to one embodiment of the present invention, after the hexahedral mesh division fails in step 2, the key feature area is partitioned manually and / or by establishing a partition model.

[0024] According to one embodiment of the present invention, when partitioning the key feature area by establishing a partition model, the steps of establishing the partition model are as follows:

[0025] Step 21: Collect geometric models of various types and complexities to form a database;

[0026] Step 22: manually partition each geometric model and record partition information; wherein the partition information includes the boundaries and geometric elements of the regions;

[0027] Step 23: extracting geometric features of the geometric model; wherein the geometric features include shape features, topological features, and curvature features;

[0028] Step 24: Select a prediction model to train the data set, and adjust the model parameters so that the partition scheme predicted by the model is close to the partition information of the manual partition, thereby obtaining a partition model.

[0029] According to one embodiment of the present invention, in step 3, if the hexahedral mesh division fails, the key feature area is first re-partitioned; after partitioning, if calling the first mesh division computer program to perform hexahedral mesh division on the important area still fails, then calling the third mesh division computer program to perform hybrid mesh division on the important area.

[0030] According to a second aspect of the present application, a finite element mesh automatic division program adopts the above-mentioned finite element mesh automatic division method, and the division system includes:

[0031] Complexity analysis module, hexahedral mesh automatic generation module, hybrid mesh automatic generation module, partitioning module, tetrahedral mesh automatic generation module and mesh quality inspection module; among them,

[0032] The complexity analysis module is used to analyze the complexity of the target geometric model; the hexahedral mesh automatic generation module is used to call the first mesh division computer program to perform hexahedral mesh division on the target area; the hybrid mesh automatic generation module is used to call the third mesh division computer program to perform hybrid mesh division on the target area; the partitioning module is used to partition the target area of the target geometric model; the tetrahedral mesh automatic generation module is used to call the second mesh division computer program to perform tetrahedral mesh division on the target area, and the mesh quality inspection module is used to perform quality inspection on the generated mesh.

[0033] A computer program product according to a third aspect of the present application includes a computer program, which, when executed by a processor, implements the steps performed by a computer in the method according to the first aspect.

[0034] According to a fourth aspect of the present application, a computer-readable storage medium has a computer program, which, when executed by a processor, implements the steps performed by the computer in the method described in the first aspect.

[0035] According to a fifth aspect of the present application, a control system includes: a memory capable of storing instructions executable by a processor; and a processor capable of executing the instructions to implement the steps performed by the computer in the method described in the first aspect.

[0036] The positive progress effect of the present invention is:

[0037] The automatic finite element meshing method of the present invention utilizes a first meshing computer program, a second meshing computer program, and a third meshing computer program to mesh key features of a target geometric model, thereby improving the success rate of hexahedral mesh generation and the proportion of hexahedral meshes, thereby improving the meshing quality, thereby improving the accuracy and speed of finite element analysis and reducing the amount of manual participation consumed by finite element analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The above and other features, properties and advantages of the present invention will become more apparent through the following description in conjunction with the accompanying drawings and embodiments, in which:

[0039] Figure 1Flowchart of the automatic finite element mesh partitioning method of the present invention;

[0040] Figure 2 is a schematic diagram of an implementation method of a target geometric model;

[0041] Figure 3 for Figure 2 Schematic diagram of key features in the target geometric model;

[0042] Figure 4 Schematic diagram of mesh division for automatically generating hexahedral mesh;

[0043] Figure 5 Schematic diagram of mesh division for automatically generating tetrahedral mesh;

[0044] Figure 6 This is a structural diagram of the partitioning system of the present invention. DETAILED DESCRIPTION

[0045] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0046] Embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Reference will now be made in detail to preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numerals will be used throughout the drawings to represent the same or similar parts. In addition, although the terms used in the present invention are selected from commonly known and commonly used terms, some of the terms mentioned in this specification may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description herein. Furthermore, it is required that the present invention be understood not only by the actual terms used, but also by the meaning implied by each term.

[0047] Please refer to Figures 1 to 5 The present invention proposes a finite element mesh automatic division method, comprising:

[0048] S1. Extract key features of the target geometric model.

[0049] Specifically, in step 1, the key features of the target geometric model are extracted by automatically analyzing the complexity of the target geometric model.

[0050] The complexity is assessed based on one or more of the number of geometric features, topological structure, and surface complexity.

[0051] Specifically, the number of geometric features includes the number of holes and openings, which increase the geometric complexity. Specifically, a boundary representation data structure can be used to traverse the faces of the target geometric model and identify faces with non-trivial boundary rings, where each inner ring corresponds to a hole.

[0052] The number of geometric features also includes the number of sharp internal angles and edges. Sharp internal angles and small-radius edges increase meshing difficulty. Sharp internal angles can be identified by analyzing the angles between adjacent faces. For edges, the curvature or radius can be checked. If the radius is less than a certain value, it is considered a small-radius edge. Related algorithms are implemented in the computational geometry algorithm library.

[0053] The number of geometric features also includes the number of tiny features. These features, such as small protrusions, depressions, or thin shells, can increase meshing difficulty without affecting overall mechanical properties. You can set an absolute size threshold based on the size range of the target geometry, or a relative size threshold based on the overall size of the target geometry. By comparing the size of the measured geometric features with the threshold, you can identify tiny features.

[0054] For topological structures, complex connectivity structures, such as multi-component connections or complex internal channels, increase model complexity. Using graph theory, we construct a topological graph using the faces, edges, or bodies of a geometric model as nodes and the connections between them as edges. We then evaluate the connectivity complexity of the target geometric model by analyzing metrics such as the number of connected components and the shortest path length.

[0055] Furthermore, non-manifold structures, such as two faces that share a point but not an edge, can cause meshing failures. Using the B-Rep data structure, we can check the adjacency of geometric elements. If we find adjacencies that do not meet the fluid definition, we can determine that a non-manifold structure exists.

[0056] Surface complexity includes curvature variation, surface type, and continuity. High-curvature areas and surfaces with frequent curvature variations are difficult to create high-quality meshes. By calculating the Gaussian curvature and mean curvature at each point on the surface, the range and frequency of curvature variation can be analyzed. The surface can be discretized and the curvature calculated at each discrete point using the surface's parametric or implicit equations.

[0057] Free-form surfaces are more complex than planes and simple quadratic surfaces.

[0058] When performing complexity analysis, you can assign weights to different indicators, then multiply each indicator by its weight and add them together to get the total score. For example, the weight for the number of holes is 0.3, the weight for the number of sharp internal angles is 0.3, and the weight for the change in surface curvature is 0.4.

[0059] Based on the complexity analysis, the key features of the target geometric model are obtained. The key features correspond to the feature areas with high complexity and need to be analyzed in detail later. Figure 2 and Figure 3 Part A in the diagram is the key feature.

[0060] S2. Calling a first meshing computer program to perform hexahedral meshing on the key feature area; if the hexahedral meshing is successful, outputting a hexahedral mesh file; if the hexahedral meshing fails, partitioning the key feature area, and selecting important areas and non-important areas.

[0061] It should be noted that the important areas and the non-important areas can be determined or manually specified based on the physical characteristics of the model, the purpose of analysis, and the geometric complexity, and are not limited here.

[0062] Physical characteristics include stress and strain concentration areas, key heat transfer areas, and key fluid flow areas.

[0063] In structural analysis, areas where stress and strain are concentrated are crucial to the strength and stability of the structure, such as corners, around holes, and near welds, where stress concentration is prone to occur.

[0064] For thermal analysis, areas with high heat flux and high temperature gradient are key areas of heat transfer.

[0065] In fluid dynamics analysis, the boundary layer, vortex generation region, and the vicinity of the flow separation point have a significant impact on the fluid flow characteristics.

[0066] It can also be based on the purpose of the analysis. For example, if the purpose of the analysis is to study a specific physical response, then the area directly related to that response is the critical area. Alternatively, when the purpose of the analysis is to evaluate a certain failure mode of the structure, then the area that may cause that failure mode is the critical area.

[0067] It can also be based on geometric complexity. Geometrically complex areas, such as those with free-form surfaces, sharp internal angles, or complex topology, are more difficult to mesh and have a significant impact on the overall behavior of the model.

[0068] For details, please refer to Figure 4 After the hexahedral mesh is successfully generated in step 2, a quality analysis is performed on the hexahedral mesh. If the quality analysis is qualified, a hexahedral mesh file is output. If the quality analysis is unqualified, the mesh mapping is adjusted to generate a hexahedral mesh file that meets the requirements.

[0069] It can be seen that the first meshing computer program includes a quality analysis program, so the quality analysis program can be directly called to analyze the quality of the generated hexahedral mesh.

[0070] When the target geometry is too complex and the generated hexahedral mesh quality is low, manual adjustments can be made to the mesh mapping in addition to the automatic mapping to generate a hexahedral mesh that meets the requirements. This means adjusting the mapped feature lines so that the mesh is remapped to the required feature lines to obtain a hexahedral mesh file that meets the requirements.

[0071] After the hexahedral meshing fails in step 2, the key feature areas are partitioned manually and / or by establishing a partition model.

[0072] Among them, manual partitioning can be performed according to the complexity of the target geometric model, which will not be described in detail here.

[0073] When partitioning key feature areas by establishing a partition model, the steps for establishing the partition model are as follows:

[0074] S21. Collect geometric models of various types and complexities to form a database.

[0075] S22. Manually partition each geometric model and record partition information; wherein the partition information includes the boundaries and geometric elements of the regions.

[0076] S23. Extracting geometric features of the geometric model; wherein the geometric features include shape features, topological features, and curvature features.

[0077] Specifically, shape features include volume, surface area, and aspect ratio; topological features include the number of connected domains, the number of holes, and the connectivity between faces; and curvature features include Gaussian curvature and mean curvature. The extracted geometric features are then converted into tensor form that can be processed by deep learning frameworks.

[0078] S24. Select a prediction model to train the data set and adjust the model parameters so that the partition scheme predicted by the model is close to the partition information of the manual partition, thereby obtaining a partition model.

[0079] Specifically, a model based on a neural network or encoder-decoder architecture is selected, and the selected model is trained using a database. By adjusting the model parameters, the partitioning scheme predicted by the model is made close to the manually labeled partitioning information. Cross entropy loss or mean square error loss is used as the loss function during training.

[0080] For new geometric models to be input, their geometric features are first extracted and fed into the trained partitioning model to obtain a predicted partitioning scheme. Designers then review and adjust the predicted partitioning scheme, manually adding additional partitions or adjusting existing partition boundaries based on their experience and understanding of the geometric model.

[0081] Evaluation metrics are established to measure the quality of the partitioning results. Specifically, these metrics include the complexity of the sub-regions after partitioning, the rationality of the partition boundaries, and the number of partitions. The evaluation results are fed back into the model training process. If the model performs poorly on certain types of geometric models, these geometric models and their manually adjusted partitioning results are added to the training dataset and the model is retrained.

[0082] S3. Call the first meshing computer program to perform hexahedral meshing on the important area; if the hexahedral meshing is successful, call the second meshing computer program to perform tetrahedral meshing on the non-important area, and then output the hexahedral and tetrahedral mesh files; if the hexahedral meshing fails, call the third meshing computer program to perform mixed meshing on the important area.

[0083] As mentioned above, since the geometry is divided into important areas and non-important areas, the division can reduce the complexity of the geometry, which is conducive to improving the success rate of hexahedral mesh division.

[0084] In step 3, if the hexahedral mesh division fails, the key feature area is first re-partitioned; after partitioning, if calling the first mesh division computer program to perform hexahedral mesh division on the important area still fails, calling the third mesh division computer program to perform hybrid mesh division on the important area.

[0085] In other words, when manually or by creating a partitioning model to partition the key feature area, multiple partitioning schemes may be obtained. Therefore, the first meshing computer program can be used to perform hexahedral partitioning for each partitioning scheme. If all partitioning schemes cannot produce a satisfactory hexahedral mesh, the third meshing computer program can be used to perform mixed meshing of the important area. Among them, the scheme with the highest proportion of hexahedral partitioning is selected as the final partitioning scheme.

[0086] S4. In step 3, if the hybrid meshing is successful, the second meshing computer program is called to perform tetrahedral meshing on the non-important area, and then the hybrid mesh and tetrahedral mesh file are output; if the hybrid meshing fails, the third meshing computer program is called to perform tetrahedral meshing on the important area and the non-important area, and then the tetrahedral mesh file is output.

[0087] As mentioned above, the first meshing computer program may be: ICEM or HyperMesh or a self-developed and trained hexahedral meshing program; the second meshing computer program may be: ANSYS Meshing, MeshGems or a self-developed hybrid meshing automatic partitioning program; the third meshing computer program may be: Tgrid or Gmsh- and other tetrahedral meshing automatic partitioning programs; the above computer programs are selected from existing computer programs, and the specific types are only given as examples and are not limited.

[0088] The target geometric model partitioning process is described as follows:

[0089] The first step is to select the key features of the target geometric model. Then, a meshing computer program is called to perform hexahedral meshing of the key feature areas. If the meshing is successful, the hexahedral mesh file can be output after adjusting the mesh quality.

[0090] In the second step, when the hexahedral mesh division fails in the first step, the key adjustment area is partitioned and important areas and non-important areas are selected.

[0091] The important areas call the first meshing computer program to perform hexahedral meshing, and the non-important areas can select hexahedral meshing, hybrid meshing and tetrahedral meshing in turn; or the non-important areas can be directly subjected to tetrahedral meshing. The specific method can be adjusted according to actual needs. If a mesh file with a high proportion of hexahedral meshes is required, it is preferred to first select hexahedral meshing, hybrid meshing and tetrahedral meshing. If the meshing efficiency needs to be improved, the non-important areas can be directly subjected to tetrahedral meshing.

[0092] If the hexahedral meshing of the important area fails, the third meshing computer program may be called to perform hybrid meshing on the important area.

[0093] If the hybrid meshing is successful, the hybrid mesh and tetrahedral mesh files are output; if the hybrid meshing fails, the second meshing computer program is called to directly perform tetrahedral meshing on the important and non-important areas and output the tetrahedral mesh files. Figure 5 , Figure 5 A meshing diagram generated by directly calling the second meshing computer program.

[0094] The automated finite element meshing method described above significantly reduces the manual time required for meshing, while also increasing the success rate and percentage of hexahedral meshes. Automatically generating hexahedral meshes at large scales improves the accuracy and speed of finite element analysis, reducing the manual effort required for finite element analysis.

[0095] The present invention further provides a finite element mesh automatic division system, characterized in that the finite element mesh automatic division method described above is adopted, and the division system includes:

[0096] Complexity analysis module, hexahedral mesh automatic generation module, hybrid mesh automatic generation module, partitioning module, tetrahedral mesh automatic generation module and mesh quality inspection module; among them,

[0097] The complexity analysis module is used to analyze the complexity of the target geometric model; the hexahedral mesh automatic generation module is used to call the first mesh division computer program to perform hexahedral mesh division on the target area; the hybrid mesh automatic generation module is used to call the third mesh division computer program to perform hybrid mesh division on the target area; the partitioning module is used to partition the target area of the target geometric model; the tetrahedral mesh automatic generation module is used to call the second mesh division computer program to perform tetrahedral mesh division on the target area, and the mesh quality inspection module is used to perform quality inspection on the generated mesh.

[0098] refer to Figure 6 As shown, the present application also provides a partitioning system 1000, including a memory 1001 and a processor 1002, wherein the memory can store instructions that can be executed by the processor 1002; the processor 1002 can execute instructions to implement the steps performed by the computer in the finite element mesh automatic partitioning method introduced in the above embodiment.

[0099] It is understood that it is important to note that the aforementioned memory and processor are not limited to a specific memory or processor. Furthermore, in embodiments employing a distributed structure, the specific execution terminal of each step can be adjusted according to actual circumstances, and the specific implementation of each step on a specific terminal should not limit the scope of protection of this application.

[0100] According to another aspect of the present application, the present application also provides a computer-readable medium.

[0101] The computer-readable medium provided in this application has computer instructions thereon. When the computer instructions are executed by a processor, the program can be executed by the processor to implement the steps performed by the program in the method described in the above embodiment.

[0102] According to yet another aspect of the present application, the present application also provides a computer program product.

[0103] The computer-readable medium provided in the present application includes a computer program. When the computer program is executed by a processor, the program can implement the steps executed by the program in the method described in the above embodiment.

[0104] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or performed using 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 device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0105] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read and write information from / to the storage medium. In an alternative embodiment, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative embodiment, the processor and storage medium may reside in a user terminal as discrete components.

[0106] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any media that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium that can be accessed by a computer. By way of example and not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks typically reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0107] Although the present application is disclosed above with reference to preferred embodiments, this is not intended to limit the present application. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, any modifications, equivalent variations, and modifications made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application shall fall within the scope of protection defined by the claims of the present application.

Claims

1. A finite element mesh automatic division method, characterized in that: include: Step 1: Extract key features of the target geometric model; Step 2: Calling a first meshing computer program to perform hexahedral meshing on the key feature area; If the hexahedral mesh is successfully divided, the hexahedral mesh file will be output; If the hexahedral meshing fails, partition the key feature area and select important areas and non-important areas; Step 3: calling the first meshing computer program to perform hexahedral meshing on the important area; if the hexahedral meshing is successful, calling the second meshing computer program to perform tetrahedral meshing on the non-important area, and then outputting hexahedral and tetrahedral mesh files; If the hexahedral meshing fails, calling a third meshing computer program to perform hybrid meshing on the important area; Step 4. In step 3, if the hybrid mesh division is successful, the second mesh division computer program is called to perform tetrahedral mesh division on the non-important area, and then the hybrid mesh and the tetrahedral mesh file are output; if the hybrid mesh division fails, the third mesh division computer program is called to perform tetrahedral mesh division on the important area and the non-important area, and then the tetrahedral mesh file is output.

2. The finite element mesh automatic division method according to claim 1, characterized in that: In the step 1, the key features of the target geometric model are extracted by automatically analyzing the complexity of the target geometric model; wherein the complexity is evaluated based on one or more of the number of geometric features, topological structure and surface complexity.

3. The finite element mesh automatic division method according to claim 1, characterized in that: After the hexahedral mesh is successfully divided in step 2, a quality analysis is performed on the hexahedral mesh; if the quality analysis is qualified, a hexahedral mesh file is output; if the quality analysis is unqualified, the mesh mapping is adjusted to generate a hexahedral mesh file that meets the requirements.

4. The finite element mesh automatic division method according to claim 1, characterized in that: After the hexahedral mesh division fails in step 2, the key feature area is partitioned manually and / or by establishing a partition model.

5. The finite element mesh automatic division method according to claim 4, characterized in that: When partitioning the key feature area by establishing a partition model, the steps of establishing the partition model are as follows: Step 21: Collect geometric models of various types and complexities to form a database; Step 22: manually partition each geometric model and record partition information; wherein the partition information includes the boundaries and geometric elements of the regions; Step 23: extracting geometric features of the geometric model; wherein the geometric features include shape features, topological features, and curvature features; Step 24: Select a prediction model to train the data set, and adjust the model parameters so that the partition scheme predicted by the model is close to the partition information of the manual partition, thereby obtaining a partition model.

6. The finite element mesh automatic division method according to claim 1, characterized in that: In step 3, if the hexahedral mesh division fails, the key feature area is first re-partitioned; after partitioning, if calling the first mesh division computer program to perform hexahedral mesh division on the important area still fails, calling the third mesh division computer program to perform hybrid mesh division on the important area.

7. A finite element mesh automatic division system, characterized in that: The automatic finite element mesh partitioning method according to any one of claims 1 to 6 is adopted, wherein the partitioning system comprises: Complexity analysis module, hexahedral mesh automatic generation module, hybrid mesh automatic generation module, partitioning module, tetrahedral mesh automatic generation module and mesh quality inspection module; among them, The complexity analysis module is used to analyze the complexity of the target geometric model; the hexahedral mesh automatic generation module is used to call the first mesh division computer program to perform hexahedral mesh division on the target area; the hybrid mesh automatic generation module is used to call the third mesh division computer program to perform hybrid mesh division on the target area; the partitioning module is used to partition the target area of the target geometric model; the tetrahedral mesh automatic generation module is used to call the second mesh division computer program to perform tetrahedral mesh division on the target area, and the mesh quality inspection module is used to perform quality inspection on the generated mesh.

8. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, implements the steps performed by a computer in the method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The invention provides a computer program, which, when executed by a processor, implements the steps executed by a computer in the method according to any one of claims 1 to 7.

10. A partitioning system, characterized in that: include: a memory capable of storing instructions executable by a processor; A processor capable of executing the instructions to implement the steps performed by a computer in the method according to any one of claims 1 to 7.

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