Three-dimensional entity CAE simulation model conversion method and system based on spatial logic dot matrix

Abstract

The invention relates to the field of computer-aided engineering simulation, in particular to a three-dimensional entity CAE simulation model conversion method and system based on a space logic dot matrix, and the method comprises the steps: building a discretized space orthogonal guide ray based on a structure three-dimensional model; performing envelope cutting on the space orthogonal guide ray based on the surface of the structure three-dimensional model to obtain a line segment set in the surface range of the three-dimensional model; performing intersection calculation on the line segment set in the surface range of the three-dimensional model to obtain an intersection point logic relation dot matrix; traversing a line segment set in the surface range of the three-dimensional model to obtain a line segment endpoint logic relation dot matrix; carrying out vertex enhancement processing on the intersection point logic relation dot matrix and the line segment end point logic relation dot matrix to form a spatial logic relation dot matrix; constructing an entity unit model of CAE simulation calculation by analyzing the spatial logic relation dot matrix and utilizing a reverse hexahedron reconstruction method; the method takes the spatial logic dot matrix as a link, is not limited by an analysis scene, and can quickly adapt to multi-physics field simulation analysis.

Description

Technical Field

[0001] This invention relates to the field of computer-aided engineering simulation, and in particular to a method and system for converting three-dimensional solid CAE simulation models based on spatial logical point lattices. Background Technology

[0002] The core objective of computer-aided engineering (CAE) simulation model conversion is to generate high-quality computational models suitable for finite element analysis through efficient processing of 3D solid models, thus balancing simulation accuracy and computational efficiency. Current mainstream conversion methods mainly include traditional meshing techniques (such as tetrahedral / hexahedral element partitioning), isogeometric analysis (parametric modeling based on non-uniform rational B-splines), and emerging lattice structure simplification techniques. For 3D solids (such as porous structures, irregular curved surfaces, or micro-feature models), existing technologies primarily achieve conversion through adaptive mesh refinement, multi-scale modeling, or dedicated modules in commercial software (such as the lattice generator in ANSYS SpaceClaim and the multiphysics coupling interface in COMSOL). For example, adaptive meshing captures stress concentration regions by locally refining element density, while lattice structure techniques attempt to replace solids with lightweight topological frameworks. However, these methods have serious shortcomings in adaptability to geometric features and versatility in computational scenarios.

[0003] Current methods for converting 3D solid models face multiple technical bottlenecks. When dealing with irregular curved surfaces, porous structures, and other solids, the loss of geometric features and the superposition of physical parameter distortions lead to model conversion failures or huge errors in stress analysis in key areas. In multiphysics coupling analysis, due to the incompatibility of model parameter systems, the same structure needs to be repeatedly constructed with simulation models of different accuracies in scenarios such as fluid-structure interaction, resulting in extremely low simulation efficiency and severely restricting the engineering application value of high-precision CAE simulation. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies in multiphysics coupling analysis, where the model parameter systems are incompatible and the same structure needs to be repeatedly constructed with different precision simulation models in scenarios such as fluid-structure interaction. This invention provides a method and system for converting three-dimensional solid CAE simulation models based on spatial logical point lattices.

[0005] In a first aspect, the present invention provides a method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix, comprising: Discretized spatial orthogonal guiding rays are created based on the three-dimensional structural model; Based on the surface of the structural 3D model, the spatial orthogonal guiding rays are enveloped and clipped to obtain the set of line segments within the surface of the 3D model; Perform intersection calculations on the set of line segments within the surface area of ​​the 3D model to obtain the logical relationship matrix of the intersection points; Traverse the set of line segments within the surface range of the 3D model to obtain the logical relationship matrix of the endpoints of the line segments; Vertex enhancement processing is performed on the intersection logical relationship lattice and the line segment endpoint logical relationship lattice to form a spatial logical relationship lattice; By analyzing the spatial logical relationship lattice, a solid element model for CAE simulation calculation is constructed using the inverse hexahedral reconstruction method.

[0006] Preferably, the process of creating discretized spatial orthogonal guiding rays is as follows: Based on the three-dimensional structural model, spatial orthogonal guiding rays parallel to the X, Y, and Z axes are created sequentially. These spatial orthogonal guiding rays envelop and penetrate the entire model.

[0007] Preferably, after creating the discretized spatial orthogonal guide rays, the guide rays corresponding to each axis are added to the corresponding axis array and numbered.

[0008] Preferably, the intersection logical relationship matrix includes the intersection number, intersection coordinates, the ray number where the intersection is located, and the numbers of adjacent intersections.

[0009] Preferably, the line segment endpoint logical relationship matrix includes the point number, endpoint coordinates, ray number where the endpoint is located, and adjacent intersection point number.

[0010] Preferably, the vertex enhancement process includes: performing vertex enhancement processing on all points of the intersection logical relationship matrix and the line segment endpoint logical relationship matrix to form a spatial logical relationship matrix; The process of vertex enhancement for any point P0 in the intersection logical relationship matrix or the line segment endpoint logical relationship matrix includes: Using P0 as the reference point, obtain the adjacent points P1, P2 and P3 in the X, Y and Z directions of the reference point; Verify the adjacency relationships of adjacent points P1, P2, and P3 respectively, which must satisfy the following conditions: the adjacent point of P1 in the Y direction is the same as the adjacent point of P2 in the X direction, which is the same point P4; the adjacent point of P1 in the Z direction is the same as the adjacent point of P3 in the X direction, which is the same point P5; the adjacent point of P2 in the Z direction is the same as the adjacent point of P3 in the Y direction, which is the same point P6. To verify the diagonal vertices using P4, P5, and P6, the following conditions must be met: the Z-direction adjacent point of P4, the Y-direction adjacent point of P5, and the X-direction adjacent point of P6 are all point P7. Based on the points P0, P1, P2, P3, P4, P5, P6 and P7, a cube is formed, resulting in the final spatial logical data record of the reference point P0: [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7].

[0011] Preferably, if the solid element model of the target CAE simulation calculation is a hexahedron, its reconstruction method is as follows: The spatial logic relation lattice is analyzed, and the final spatial logic data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral element for each final spatial logic data record. The generated hexahedral elements are then spliced ​​together to form the solid element model for the target CAE simulation calculation.

[0012] Preferably, the method for generating hexahedral cells for any final spatial logical data record [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7] is as follows: Based on the coplanar relationship, the points in the final spatial logical data record are classified to obtain bottom surface points and top surface points; By establishing a one-to-one correspondence between the bottom and top points along the Z-axis, the left, right, front, and back faces of the hexahedral element are constructed.

[0013] Preferably, the spatial logical relationship lattice is parsed, and the final spatial logical data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral unit for each final spatial logical data record. The constructed hexahedral elements are decomposed, and tetrahedral elements are constructed using the starting point, two adjacent points, and diagonal vertices of the hexahedral elements. The solid element model for the target CAE simulation calculation is formed by assembling the constructed tetrahedral elements.

[0014] In a second aspect, the present invention provides a three-dimensional solid CAE simulation model conversion system based on a spatial logical dot matrix, for performing the method described in the first aspect, comprising: The Discretized Space Construction Module is used to create orthogonal guiding rays in a discretized space. The envelope clipping module is used to perform envelope clipping on spatial orthogonal guiding rays based on the surface of the structural 3D model to obtain a set of line segments within the surface range of the 3D model. The intersection logical relationship matrix acquisition module is used to perform intersection calculations on the set of line segments within the surface range of the 3D model to obtain the intersection logical relationship matrix; The module for obtaining the logical relationship matrix of line segment endpoints is used to traverse the set of line segments within the surface range of the 3D model and obtain the logical relationship matrix of line segment endpoints. The vertex enhancement module is used to enhance the intersection logical relationship matrix and the line segment endpoint logical relationship matrix to form a spatial logical relationship matrix. The reverse reconstruction module is used to construct solid element models for CAE simulation calculations by analyzing spatial logical relationship lattices and using the reverse hexahedral reconstruction method.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: Based on a spatial orthogonal coordinate system, this invention discretizes and reconstructs the shape rules of model units, quickly and accurately discretizes a three-dimensional model into a spatial lattice and simultaneously creates spatial logical relationships between each point. This allows the invention to use the spatial logical lattice as a link, without being limited by the shape of the three-dimensional model, and to quickly discretize entity models of arbitrary shapes. Attached Figure Description

[0016] Figure 1 This is a flowchart of a three-dimensional solid CAE simulation model conversion method based on spatial logic dot matrix in one embodiment of the present invention; Figure 2 This is a schematic diagram of the graph model conversion process in one embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the creation and trimming of discretized spatial orthogonal guide rays in one embodiment of the present invention; Figure 4 This is a schematic diagram of constructing a spatial logical relationship matrix record in one embodiment of the present invention; Figure 5 This is a schematic diagram of reverse construction of CAE simulation hexahedral reconstruction and tetrahedral reconstruction in one embodiment of the present invention. Detailed Implementation

[0017] The present invention will now be described in further detail with reference to specific embodiments. However, this should not be construed as limiting the scope of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0018] In the description of the embodiments of this application, "adjacent point" refers to one or more points that have a direct connection relationship with a given reference point or meet preset proximity conditions in a specific data structure or spatial configuration.

[0019] Example 1 Please refer to Figure 1 This embodiment provides a method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix, including: Discretized spatial orthogonal guiding rays are created based on the three-dimensional structural model; Based on the surface of the structural 3D model, the spatial orthogonal guiding rays are enveloped and clipped to obtain the set of line segments within the surface of the 3D model; Perform intersection calculations on the set of line segments within the surface area of ​​the 3D model to obtain the logical relationship matrix of the intersection points; Traverse the set of line segments within the surface range of the 3D model to obtain the logical relationship matrix of the endpoints of the line segments; Vertex enhancement processing is performed on the intersection logical relationship lattice and the line segment endpoint logical relationship lattice to form a spatial logical relationship lattice; By analyzing the spatial logical relationship lattice, a solid element model for CAE simulation calculation is constructed using the inverse hexahedral reconstruction method.

[0020] Please refer to Figure 2 In some possible implementations, the process of creating a discretized spatial orthogonal guiding ray is as follows: Based on the three-dimensional structural model, spatial orthogonal guiding rays parallel to the X, Y, and Z axes are created sequentially. These spatial orthogonal guiding rays envelop and penetrate the entire model.

[0021] Preferably, please refer to Figure 3 After creating discretized spatial orthogonal guide rays, add the guide rays corresponding to each axis to the corresponding axis array and number them. For example, add the guide rays to the arrays L_Xid (numbered sequentially from negative Y to positive Y, negative Z to positive Z), L_Yid (numbered sequentially from negative X to positive X, negative Z to positive Z), and L_Zid (numbered sequentially from negative X to positive X, negative Y to positive Y), and number the rays in them.

[0022] To ensure that the array numbering remains unchanged, in the numbered ray array, each ray is intersected with the outer surface of the 3D model and trimmed into line segments. After removing the line segments outside the model and obtaining the set of line segments within the surface range of the 3D model, the position of the ray in the array is not changed.

[0023] To enable those skilled in the art to more easily understand the scheme for obtaining the intersection logical relationship matrix and the line segment endpoint logical relationship matrix in this embodiment, please refer to... Figure 4 .

[0024] As one possible implementation, take line segments L_Xid[0], L_Yid[0], and L_Zid[0] and find their intersection to obtain the intersection point P0, whose coordinates are (x, y, z). Then, take L_Xid[0], L_Yid[1], and L_Zid[1] and find their intersection to obtain the collinear adjacent points P1 of P0 in the positive X direction. Then, take L_Xid[1], L_Yid[0], and L_Zid[1] and find their intersection to obtain the collinear points P0 in the positive Y direction. Intersections of adjacent points P2, L_Xid[1], L_Yid[1], and L_Zid[0] are obtained to find the collinear adjacent point P3 of P0 in the positive Z direction, forming a preliminary record of the spatial logical relationship data of point P0: P0, x, y, z, P1, P2, P3. Then, all line segments are traversed to find intersections, forming a spatial logical point matrix of all intersection points. The logical relationship point matrix of intersection points includes the intersection point number, the intersection point coordinates, the ray number where the intersection point is located, and the adjacent intersection point number.

[0025] Traverse the clipped spatial line segments to obtain the endpoints of all line segments. For example, take the endpoint P100 of line segment L_Xid[0], whose coordinates are (x, y, z). The adjacent intersection point P101 in the collinear positive X direction is taken as its adjacent point in the positive X axis. The endpoint P102 of the adjacent line segment in the positive Y direction at the same end is taken as its adjacent point in the positive Y axis. The endpoint P103 of the adjacent line segment in the positive Z direction at the same end is taken as its adjacent point in the positive Z axis. The preliminary data record of the spatial logical relationship of point P100 is formed: P100, x, y, z, P101, P102, P103. The point matrix of the line segment endpoint logical relationship includes the point number, endpoint coordinates, ray number where the endpoint is located, and adjacent intersection number.

[0026] By combining the intersection logic relation matrix and the line segment endpoint logic relation matrix, a complete preliminary data file of spatial matrix logic can be formed.

[0027] To obtain a directly constructible spatial logical relationship matrix from the preliminary spatial matrix logical data file, this embodiment provides a specific scheme for vertex enhancement processing in some possible implementations. For example, vertex enhancement processing is performed on all points of the intersection logical relationship matrix and the line segment endpoint logical relationship matrix to form a spatial logical relationship matrix. The process of vertex enhancement for any point P0 in the intersection logical relationship matrix or the line segment endpoint logical relationship matrix includes: Using P0 as the reference point, obtain the adjacent points P1, P2 and P3 in the X, Y and Z directions of the reference point; Verify the adjacency relationships of adjacent vertices P1, P2, and P3 respectively, which must satisfy: The adjacent point of P1 in the Y direction is the same as the adjacent point of P2 in the X direction, which is the same point P4. The Z-direction adjacent point of P1 is the same as the X-direction adjacent point of P3, which is the same point P5. The Z-direction adjacent point of P2 is the same as the Y-direction adjacent point of P3, which is the same point P6. To verify the diagonal vertices using P4, P5, and P6, the following conditions must be met: the Z-direction adjacent point of P4, the Y-direction adjacent point of P5, and the X-direction adjacent point of P6 are all point P7. Based on the points P0, P1, P2, P3, P4, P5, P6 and P7, a cube is formed, resulting in the final spatial logical data record of the reference point P0: [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7].

[0028] This embodiment illustrates a method and process for rapidly and accurately discretizing a 3D model into a spatial lattice and simultaneously creating the spatial logical relationships between the points using spatial orthogonal rays and the surface contour of the 3D model. It also proposes a data storage format for expressing spatial logical relationships and provides a fast and efficient method for discretizing a 3D model into a CAE simulation analysis model.

[0029] Example 2 Please refer to Figure 5 This embodiment provides a process for reconstructing hexahedral and tetrahedral elements based on the method described in Embodiment 1. It is used to illustrate that the method provided by the present invention is not limited by the shape of the three-dimensional model, can quickly discretize solid models of arbitrary shapes, is not limited by the analysis scene, and can quickly adapt to multiphysics simulation analysis. It should be understood that this embodiment is only an example implementation scheme of the present invention and is not intended to limit the present invention to only reconstructing hexahedral or tetrahedral elements.

[0030] If the solid element model of the target CAE simulation is a hexahedron, its reconstruction method is as follows: The spatial logic relation lattice is analyzed, and the final spatial logic data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral element for each final spatial logic data record. The generated hexahedral elements are then spliced ​​together to form the solid element model for the target CAE simulation calculation.

[0031] The method for generating hexahedral cells for any final spatial logical data record [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7] is as follows: Based on the coplanar relationship, the points in the final spatial logical data record are classified to obtain bottom surface points and top surface points; By establishing a one-to-one correspondence between the bottom and top points along the Z-axis, the left, right, front, and back faces of the hexahedral element are constructed.

[0032] For example, such as Figure 5 As shown in the diagram, P0, P1, P4, and P2 are four coplanar vertices, and P3, P5, P7, and P6 are four coplanar vertices, each corresponding one-to-one with the positive Z-axis direction of P0, P1, P4, and P2. The vertex combinations of the faces of the resulting hexahedron are as follows: Bottom surfaces: P0, P1, P4, P2; Above: P3, P5, P7, P6; Left side: P0, P2, P6, P3; Right side: P1, P4, P7, P5; Previous: P0, P1, P5, P3; The following are P2, P4, P7, and P6.

[0033] The logic dot matrix data file is traversed, each record is generated into a hexahedron, and finally assembled into a complete three-dimensional discrete model.

[0034] If the solid element model of the target CAE simulation is a tetrahedron, its reconstruction method is as follows: The spatial logical relationship lattice is analyzed, and the final spatial logical data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral unit for each final spatial logical data record. The constructed hexahedral elements are decomposed, and tetrahedral elements are constructed using the starting point, two adjacent points, and diagonal vertices of the hexahedral elements. The solid element model for the target CAE simulation calculation is formed by assembling the constructed tetrahedral elements.

[0035] For example, such as Figure 5 As shown, for the vertices P0, P1, P2, P4, P3, P5, P6, and P7 of the tetrahedron, it is decomposed into the following 6 tetrahedrons (the vertex numbers of each tetrahedron are arranged in ascending order to ensure uniqueness): Tetrahedron 1: P0, P1, P4, P7; Tetrahedron 2: P0, P4, P2, P7; Tetrahedron 3: P0, P2, P6, P7; Tetrahedron 4: P0, P6, P3, P7; Tetrahedron 5: P0, P3, P5, P7; Tetrahedron 6: P0, P5, P1, P7.

[0036] The logic dot matrix data file is traversed, and each record is used to generate 6 tetrahedrons, which are then pieced together to form a complete 3D discrete model.

[0037] Example 3 To implement the method in Embodiment 1 or Embodiment 2, in some possible implementations, the present invention also provides a three-dimensional solid CAE simulation model conversion system based on spatial logical point lattices, comprising: The Discretized Space Construction Module is used to create orthogonal guiding rays in a discretized space. The envelope clipping module is used to perform envelope clipping on spatial orthogonal guiding rays based on the surface of the structural 3D model to obtain a set of line segments within the surface range of the 3D model. The intersection logical relationship matrix acquisition module is used to perform intersection calculations on the set of line segments within the surface range of the 3D model to obtain the intersection logical relationship matrix; The module for obtaining the logical relationship matrix of line segment endpoints is used to traverse the set of line segments within the surface range of the 3D model and obtain the logical relationship matrix of line segment endpoints. The vertex enhancement module is used to enhance the intersection logical relationship matrix and the line segment endpoint logical relationship matrix to form a spatial logical relationship matrix. The reverse reconstruction module is used to construct solid element models for CAE simulation calculations by analyzing spatial logical relationship lattices and using the reverse hexahedral reconstruction method.

[0038] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0039] This invention describes a method for converting 3D solid CAE simulation models based on spatial logical point lattices. Through innovative 3D model discretization and reconstruction methods, it significantly improves the efficiency and accuracy of CAE simulation analysis. First, based on dynamic matching technology between spatial orthogonal rays and model surface contours, it achieves efficient discretization of irregular solid models, rapidly converting arbitrary curved surfaces into regular spatial point lattices with spatial logical relationships, breaking through the dependence of traditional mesh generation on model geometric features. Second, the proposed logical point lattice data format and reverse reconstruction algorithm support the dynamic generation of hexahedral / tetrahedral elements, with regular and uniform element shapes, effectively reducing numerical distortion errors and improving computational accuracy. Furthermore, this method uses spatial logical point lattices as a conversion link to decouple the geometric model from the physical field, seamlessly connecting to multi-physics simulation needs such as structural, fluid, and thermodynamic simulations, improving model reusability. This technology will provide core support for refined CAE simulation of equipment and engineering structures, possessing significant engineering application value.

Claims

1. A method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix, characterized in that, include: Discretized spatial orthogonal guiding rays are created based on the three-dimensional structural model; Based on the surface of the structural 3D model, the spatial orthogonal guiding rays are enveloped and clipped to obtain the set of line segments within the surface of the 3D model; Perform intersection calculations on the set of line segments within the surface area of ​​the 3D model to obtain the logical relationship matrix of the intersection points; Traverse the set of line segments within the surface range of the 3D model to obtain the logical relationship matrix of the endpoints of the line segments; Vertex enhancement processing is performed on the intersection logical relationship lattice and the line segment endpoint logical relationship lattice to form a spatial logical relationship lattice; By analyzing the spatial logical relationship lattice, a solid element model for CAE simulation calculation is constructed using the inverse hexahedral reconstruction method.

2. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 1, characterized in that, The process of creating a discretized spatial orthogonal guiding ray is as follows: Based on the three-dimensional structural model, spatial orthogonal guiding rays parallel to the X, Y, and Z axes are created sequentially. These spatial orthogonal guiding rays envelop and penetrate the entire model.

3. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 2, characterized in that, After creating discretized spatial orthogonal guide rays, add the guide rays corresponding to each axis to the corresponding axis array and number them.

4. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 1, characterized in that, The intersection logical relationship matrix includes the intersection number, intersection coordinates, the ray number where the intersection is located, and the numbers of adjacent intersections.

5. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 1, characterized in that, The logical relationship matrix of line segment endpoints includes the point number, endpoint coordinates, ray number where the endpoint is located, and adjacent intersection point numbers.

6. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 1, characterized in that, The vertex enhancement process includes: performing vertex enhancement on all points of the intersection logical relationship lattice and the line segment endpoint logical relationship lattice to form a spatial logical relationship lattice; The process of vertex enhancement for any point P0 in the intersection logical relationship matrix or the line segment endpoint logical relationship matrix includes: Using P0 as the reference point, obtain the adjacent points P1, P2 and P3 in the X, Y and Z directions of the reference point; Verify the adjacency relationships of adjacent points P1, P2, and P3 respectively, which must satisfy the following conditions: the adjacent point of P1 in the Y direction is the same as the adjacent point of P2 in the X direction, which is the same point P4; the adjacent point of P1 in the Z direction is the same as the adjacent point of P3 in the X direction, which is the same point P5; the adjacent point of P2 in the Z direction is the same as the adjacent point of P3 in the Y direction, which is the same point P6. To verify the diagonal vertices using P4, P5, and P6, the following conditions must be met: the Z-direction adjacent point of P4, the Y-direction adjacent point of P5, and the X-direction adjacent point of P6 are all point P7. Based on the points P0, P1, P2, P3, P4, P5, P6 and P7, a cube is formed, resulting in the final spatial logical data record of the reference point P0: [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7].

7. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 6, characterized in that, If the solid element model of the target CAE simulation is a hexahedron, its reconstruction method is as follows: The spatial logic relation lattice is analyzed, and the final spatial logic data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral element for each final spatial logic data record. The generated hexahedral elements are then spliced ​​together to form the solid element model for the target CAE simulation calculation.

8. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 7, characterized in that, The method for generating hexahedral cells for any final spatial logical data record [P0, x, y, z, P1, P2, P3, P4, P5, P6, P7] is as follows: Based on the coplanar relationship, the points in the final spatial logical data record are classified to obtain bottom surface points and top surface points; By establishing a one-to-one correspondence between the bottom and top points along the Z-axis, the left, right, front, and back faces of the hexahedral element are constructed.

9. The method for converting a three-dimensional solid CAE simulation model based on a spatial logical dot matrix according to claim 6, characterized in that, If the solid element model of the target CAE simulation is a tetrahedron, its reconstruction method is as follows: The spatial logical relationship lattice is analyzed, and the final spatial logical data record is read point by point. The hexahedral reconstruction method is used to generate a hexahedral unit for each final spatial logical data record. The constructed hexahedral elements are decomposed, and tetrahedral elements are constructed using the starting point, two adjacent points, and diagonal vertices of the hexahedral elements. The solid element model for the target CAE simulation calculation is formed by assembling the constructed tetrahedral elements.

10. A three-dimensional solid CAE simulation model conversion system based on spatial logical dot lattice, characterized in that, For performing the method according to any one of claims 1-9, comprising: The Discretized Space Construction Module is used to create orthogonal guiding rays in a discretized space. The envelope clipping module is used to perform envelope clipping on spatial orthogonal guiding rays based on the surface of the structural 3D model to obtain a set of line segments within the surface range of the 3D model. The intersection logical relationship matrix acquisition module is used to perform intersection calculations on the set of line segments within the surface range of the 3D model to obtain the intersection logical relationship matrix; The module for obtaining the logical relationship matrix of line segment endpoints is used to traverse the set of line segments within the surface range of the 3D model and obtain the logical relationship matrix of line segment endpoints. The vertex enhancement module is used to enhance the intersection logical relationship matrix and the line segment endpoint logical relationship matrix to form a spatial logical relationship matrix. The reverse reconstruction module is used to construct solid element models for CAE simulation calculations by analyzing spatial logical relationship lattices and using the reverse hexahedral reconstruction method.

Images