Finite element model boundary transition optimization method, device and readable storage medium

Abstract

The present invention discloses a finite element model boundary transition optimization method, device and readable storage medium, which obtain hexahedral mesh information of a geometric model; use an intra-layer transition algorithm to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain intra-layer transition information; use an inter-layer transition algorithm to perform boundary detection and inter-layer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain inter-layer transition information; according to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, use a finite element reconstruction algorithm based on Python to automatically generate a finite element model after mesh transition, and complete the finite element model boundary transition optimization. The present invention makes the overall geometric boundary surface of the generated finite element model smoother.

Description

Technical Field

[0001] The present invention belongs to the technical field of finite element analysis, and relates to a finite element model boundary transition optimization method, device and readable storage medium. Background Art

[0002] This technology belongs to the pre-processing part of the finite element analysis (FEA) field to generate finite element models. At present, the generation of finite element models is usually achieved by manual interaction of designers, and its quality and results are heavily dependent on the technical level and experience of designers, and the generation efficiency is low. Therefore, the automatic and rapid generation technology of high-precision complex finite element models is one of the key factors to improve the efficiency of engineering design and development.

[0003] At present, there are two main methods for generating finite element models. The first method relies on the built-in meshing methods of traditional finite element software, such as free meshing, mapped meshing, etc. However, traditional generation methods generally have the following disadvantages: a large number of manual interactive operations are required; it is difficult to generate fine finite element models of complex structures, and the generation quality is difficult to guarantee; some methods have a narrow scope of application and poor universality.

[0004] The second is to develop the technology of finite element meshing for specific structures based on the existing platform, such as "A Method for Rapidly Establishing Finite Element Models of Integral Frames" invented by Yang Zhibin, Jiang Junliang and others from the China Aircraft Strength Research Institute (Shaanxi Province: CN105739958B, 2019-02-15). Although this method has the effect of improving efficiency for the structure while ensuring accuracy, it is only applicable to this type of specific structure. It cannot be used or cannot obtain good optimization effects for other structures. Therefore, this method has great limitations and a narrow adaptability.

[0005] In another patent, Zhang Bo, Zhang Yizhe, Sun Dongsheng and others from Chang'an University proposed "A method for quickly generating a fine finite element model of a complex structure" (Shaanxi Province, CN113536617A[P]. 2021-10-22), which is referred to as the comparative case for convenience. This method is to obtain a series of binary images by sectioning the geometric model, and then reconstruct the model on the HYPERMESH platform to finally generate a high-precision hexahedral mesh finite element model. Although the method proposed by Zhang, Sun and others has a wide range of applications and can effectively improve the generation efficiency of finite element models and reduce manual interactive control, the geometric boundaries of non-parallel coordinate planes and non-planar geometric boundaries of parallel coordinate planes in the generated finite element model are relatively rough, which is easy to cause errors in subsequent calculations and analysis, and may cause stress concentration due to discontinuous boundaries. Therefore, there is still a lack of methods for automatically and quickly generating high-precision finite element models with smooth boundaries that are widely applicable and have less manual interaction. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention provides a finite element model boundary transition optimization method, device and readable storage medium, so that the overall geometric boundary surface of the generated finite element model is smoother.

[0007] In order to solve the above technical problems, the present invention is implemented by the following technical solutions:

[0008] A finite element model boundary transition optimization method, comprising:

[0009] Get the hexahedral mesh information of the geometric model;

[0010] Using an intra-layer transition algorithm to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain intra-layer transition information;

[0011] Using an interlayer transition algorithm to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain interlayer transition information;

[0012] According to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, a finite element model after mesh transition is automatically generated by a finite element reconstruction algorithm based on Python, and the boundary transition optimization of the finite element model is completed.

[0013] Furthermore, before obtaining the hexahedral mesh information of the geometric model, the method further includes:

[0014] Get the binary image of the geometric model, including:

[0015] The geometric model is sectioned and preprocessed to obtain a binary image of the geometric model, wherein the binary image of the geometric model includes pixel values ​​and pixel coordinates of pixel points.

[0016] Furthermore, the obtaining of the hexahedral mesh information of the geometric model specifically includes:

[0017] The pixel values ​​of the pixel points in the binary image of the geometric model are sequentially stored in a three-dimensional matrix according to the pixel coordinates to obtain the hexahedral mesh information of the geometric model.

[0018] Furthermore, the intra-layer transition algorithm is used to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain the intra-layer transition information, which specifically includes:

[0019] Using an intra-layer transition algorithm to perform boundary detection processing on the hexahedral mesh information to obtain intra-layer transition mesh coordinates;

[0020] An intra-layer transition algorithm is used to determine the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates to obtain an intra-layer transition grid type value;

[0021] The intra-layer transition grid type value is stored in a three-dimensional matrix according to the intra-layer transition grid coordinates to obtain the intra-layer transition information.

[0022] Further, the intra-layer transition algorithm is used to judge the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates to obtain the intra-layer transition grid type value, specifically including:

[0023] When judging the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates, the grid type around the intra-layer transition grid coordinates is detected, the intra-layer transition grid type is judged, the intra-layer transition grid type is marked, and the intra-layer transition grid type value is obtained.

[0024] Furthermore, the interlayer transition algorithm is used to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain the interlayer transition information, specifically including:

[0025] Using an inter-layer transition algorithm to perform boundary detection processing on the hexahedral mesh information and the intra-layer transition information to obtain inter-layer transition mesh coordinates;

[0026] An interlayer transition algorithm is used to determine the interlayer transition grid type corresponding to the interlayer transition grid coordinates to obtain an interlayer transition grid type value;

[0027] The inter-layer transition grid type value is stored in a three-dimensional matrix according to the inter-layer transition grid coordinates to obtain the inter-layer transition information.

[0028] Further, the inter-layer transition algorithm is used to judge the inter-layer transition grid type corresponding to the inter-layer transition grid coordinates to obtain the inter-layer transition grid type value, specifically including:

[0029] When judging the interlayer transition grid type corresponding to the interlayer transition grid coordinates, the grid type around the interlayer transition grid coordinates is detected, the interlayer transition grid type is judged, the interlayer transition grid type is marked, and the interlayer transition grid type value is obtained.

[0030] Furthermore, the method of automatically generating a finite element model after mesh transition using a finite element reconstruction algorithm based on Python according to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information specifically includes:

[0031] The finite element reconstruction algorithm based on Python first calculates the node number, node coordinates, unit number and unit node relationship based on the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, combined with the input mesh size, section spacing and number of binary images;

[0032] The python-based finite element reconstruction algorithm then automatically generates a finite element model after mesh transition based on the node numbers, node coordinates, unit numbers and unit node relationships, as well as the input material properties.

[0033] A finite element model boundary transition optimization device, comprising:

[0034] An acquisition module, used for acquiring hexahedral mesh information of a geometric model;

[0035] A first processing module is used to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information using an intra-layer transition algorithm to obtain intra-layer transition information;

[0036] The second processing module is used to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information using an interlayer transition algorithm to obtain interlayer transition information;

[0037] The model generation module is used to automatically generate a finite element model after mesh transition based on the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information by using a finite element reconstruction algorithm based on Python, so as to complete the boundary transition optimization of the finite element model.

[0038] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of a finite element model boundary transition optimization method.

[0039] Compared with the prior art, the present invention has at least the following beneficial effects: a finite element model boundary transition optimization method provided by the present invention aims at the problem that the geometric boundaries located on non-parallel coordinate planes and the non-planar geometric boundaries of parallel coordinate planes in the current finite element model are relatively rough. The pixel values ​​of the pixel points in the binary image of the geometric model are stored in a three-dimensional matrix in sequence according to the pixel coordinates to obtain the hexahedral mesh information of the geometric model, and an intra-layer transition algorithm is used to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain the intra-layer transition information. An inter-layer transition algorithm is used to perform boundary detection and inter-layer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain the inter-layer transition information; according to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, a finite element reconstruction algorithm based on python is used to automatically generate a finite element model after mesh transition to complete the boundary transition optimization of the finite element model. Since the present invention obtains hexahedral mesh information through binary images and is relatively accurate for geometric models with various complex structures, the present invention has good universality and a wide range of applications. The present invention adopts an intra-layer transition algorithm and an inter-layer transition algorithm to obtain intra-layer transition information and inter-layer transition information, which solves the problem that the geometric boundaries located on non-parallel coordinate planes and the non-planar geometric boundaries of parallel coordinate planes in the finite element model are relatively rough, making the geometric boundaries of the generated finite element model smoother and improving the quality of the finite element model. The present invention adopts a finite element reconstruction algorithm based on python to automatically generate a finite element model after mesh transition, which significantly improves the efficiency of establishing the finite element model.

[0040] Furthermore, the present invention only needs to input a small number of parameters such as grid size, section spacing and material properties to generate a finite element model after grid transition from a binary image, which greatly reduces manual interaction and is very easy to operate. Moreover, due to less manual intervention, the dependence of the quality and results of the finite element model on the technical level and experience of the designer is greatly reduced.

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the specific implementation modes of the present invention, the drawings required for use in the description of the specific implementation modes will be briefly introduced below. Obviously, the drawings described below are some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 A schematic diagram of a finite element model boundary transition optimization method according to the present invention;

[0044] Figure 2 It is a type I pentahedral mesh diagram;

[0045] Figure 3 It is a type II pentahedral grid diagram;

[0046] Figure 4 is a tetrahedral mesh diagram;

[0047] Figure 5a , 5b This is a comparison diagram of the mesh smoothness before and after the transition between the comparative case and the present invention;

[0048] Figure 6 The finite element model of a gas turbine blade established by the method of the present invention (number of elements: 2.142 million);

[0049] Figure 7 It is a schematic diagram of the grid orientation with grid type values ​​ranging from 1 to 29;

[0050] Figures 8a to 8d Schematic diagram of the transition optimization process based on a hexahedral mesh. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are 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.

[0052] For convenience, the present invention will be described by referring to the following terms:

[0053] Section: Parallel to a certain reference plane, the section image of the existing geometric model is intercepted layer by layer and continuously according to the determined interval Δz.

[0054] Binary image: Each cross-sectional image is cropped, threshold segmented and scaled to obtain a binary image (cropping: crop the black background area around the cross-sectional image as much as possible; threshold segmentation: after completing the cropping of the cross-sectional image, set the grayscale standard, judge the relationship between the pixel value and its size of each cross-sectional image, and set each pixel value to either 0 or 1 to obtain a binary image sequence; scaling: the size of one side of the geometric model is l, and the number of pixels corresponding to it on the cross-sectional image is n l ,make Enlarge the cross-section image p times).

[0055] As a specific embodiment of the present invention, a finite element model boundary transition optimization method specifically includes the following steps:

[0056] S1. Obtain hexahedral mesh information of the geometric model.

[0057] Specifically, before obtaining the hexahedral mesh information of the geometric model, the binary image of the geometric model is first obtained as follows:

[0058] The geometric model is sectioned and preprocessed to obtain a binary image of the geometric model, wherein the binary image of the geometric model includes pixel values ​​and pixel coordinates of pixel points.

[0059] Then, the pixel values ​​of the pixel points in the binary image of the geometric model are sequentially stored in the three-dimensional matrix according to the pixel coordinates to obtain the hexahedral mesh information of the geometric model.

[0060] S2. Use the intra-layer transition algorithm to perform boundary detection and intra-layer transition mesh type judgment on the hexahedral mesh information to obtain intra-layer transition information, as follows:

[0061] S2.1, using the intra-layer transition algorithm to perform boundary detection on the hexahedral mesh information and obtain the intra-layer transition mesh coordinates;

[0062] S2.2, using the intra-layer transition algorithm to determine the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates, and obtaining the intra-layer transition grid type value;

[0063] Preferably, when judging the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates, the grid type around the intra-layer transition grid coordinates is detected, the intra-layer transition grid type is judged, the intra-layer transition grid type is marked, and the intra-layer transition grid type value is obtained;

[0064] S2.3. Store the intra-layer transition grid type value into the three-dimensional matrix according to the intra-layer transition grid coordinates to obtain the intra-layer transition information.

[0065] S3, using the inter-layer transition algorithm to perform boundary detection and inter-layer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information, and obtain the inter-layer transition information, as follows:

[0066] S3.1. Use the inter-layer transition algorithm to perform boundary detection on the hexahedral mesh information and the intra-layer transition information to obtain the inter-layer transition mesh coordinates;

[0067] S3.2, using an inter-layer transition algorithm to determine the inter-layer transition grid type corresponding to the inter-layer transition grid coordinates, and obtaining an inter-layer transition grid type value;

[0068] Preferably, when judging the interlayer transition grid type corresponding to the interlayer transition grid coordinates, the grid type around the interlayer transition grid coordinates is detected, the interlayer transition grid type is judged, the interlayer transition grid type is marked, and the interlayer transition grid type value is obtained;

[0069] S3.3. The interlayer transition grid type value is stored in the three-dimensional matrix according to the interlayer transition grid coordinates to obtain the interlayer transition information.

[0070] S4. According to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, a finite element reconstruction algorithm based on Python is used to automatically generate a finite element model after mesh transition, and complete the finite element model boundary transition optimization, as follows:

[0071] S4.1. The finite element reconstruction algorithm based on Python first calculates the node number, node coordinates, unit number and unit-node relationship based on the hexahedral mesh information, intra-layer transition information and inter-layer transition information, combined with the input mesh size, section spacing and number of binary images;

[0072] S4.2. The finite element reconstruction algorithm based on Python automatically generates a finite element model after mesh transition based on the node number, node coordinates, unit number and unit node relationship, as well as the input material properties.

[0073] The present invention improves the establishment method of the finite element model, so that the geometric boundary of the generated finite element model is smoother, and the quality of the finite element model and the establishment efficiency of the finite element model are improved.

[0074] The present invention also provides a finite element model boundary transition optimization device for implementing the optimization method, specifically comprising:

[0075] An acquisition module, used for acquiring hexahedral mesh information of a geometric model;

[0076] The first processing module is used to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information using an intra-layer transition algorithm to obtain intra-layer transition information;

[0077] The second processing module is used to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information using an interlayer transition algorithm to obtain the interlayer transition information;

[0078] The model generation module is used to automatically generate a finite element model with mesh transition based on the hexahedral mesh information, intra-layer transition information and inter-layer transition information, using a finite element reconstruction algorithm based on Python, and complete the boundary transition optimization of the finite element model.

[0079] Example

[0080] Combination Figure 1 As shown in Figure 1, a finite element model boundary transition optimization method is as follows:

[0081] 1. Get the hexahedral mesh information of the geometric model. Set the upper left corner of the first binary image as the coordinate origin, the horizontal direction of the binary image as the X-axis, the vertical direction of the binary image as the Y-axis, and the cross-section direction stacking as the Z-axis. Set the mesh type value to 0 to 29, where 0 means no mesh, 1 means a hexahedral mesh, and 2 to 29 means a transitional mesh. In the transitional mesh, 2 to 13 means type I pentahedral meshes in different orientations, 14 to 21 means type II pentahedral meshes in different orientations, and 22 to 29 means tetrahedral meshes in different orientations (such as Figure 7 ). Read binary images one by one, and store the pixel values ​​0 and 1 as a three-dimensional matrix IM1 containing only grid type values ​​0 and 1 (the matrix dimension is n×w×h, where n is the number of binary images, w is the number of horizontal pixels of the binary image, and h is the number of vertical pixels of the binary image).

[0082] 2. Solve the transition information within the layer (such as Figure 8a to Figure 8b The three-dimensional matrix IM1 is read, and the mesh type and position coordinates of the I-type pentahedral unit are determined according to the intra-layer transition condition, and the mesh type value is stored as a three-dimensional matrix IM2 (the matrix dimension is n×w×h) according to the position coordinates.

[0083] 2.1 Perform intra-layer transition along the Z-axis direction and determine transition mesh types 2 to 5.

[0084] 2.1.1 Get the row and column grid type value matrix. Read the three-dimensional matrix IM1 and store each two-dimensional matrix as A1, A2, ···, A along the Z axis. i ,···,A n (The matrix dimension is w×h), where n is the dimension of the three-dimensional matrix in the Z axis direction. i For example, take A i The first h-1 behavior matrix A it (the matrix dimension is w×(h-1)), the last h-1 rows are the matrix Aib (the matrix dimension is w×(h-1)), the first w-1 columns are matrix A il (The matrix dimension is (w-1)×h), and the last w-1 columns are the matrix A ir (The matrix dimension is (w-1)×h).

[0085] 2.1.2 Get the row and column grid boundary matrix. Let A h =A it -A ib (the matrix dimension is w×(h-1)), where the position with a value of positive or negative 1 is the position of the horizontal boundary, let A v =A il -A ir (The matrix dimension is (w-1)×h), where the position with a value of positive or negative 1 is the position of the vertical boundary.

[0086] 2.1.3 Get the transition grid coordinates (x b ,y b ), if A h (x1,y1)=1, then x b =x1,y b =y1+1; if A h (x2,y2)=-1, then x b =x2,y b =y2; if A v (x3,y3)=1, then x b =x3+1,y b =y3; if A v (x4,y4)=-1, then x b =x3,y b =y3.

[0087] 2.1.4 Deduplication. Delete (x b ,y b ) in the duplicate position coordinates.

[0088] 2.1.5 Determine the transition grid type in the layer one by one. Let the grid type value to be transitioned be e o , the coordinates are (x b ,y b ), the top, bottom, left, and right grid coordinates are (x n ,y n ),(x s ,y s ),(x e ,y e ),(x w ,y w ), where x n =x b ,yn =y b -1,x s =x b ,y s =y b -1,x e =x b -1,y e =y b ,x w =x b +1, y w =y b , read A respectively i The corresponding coordinates (x n ,y n ),(x s ,y s ),(x e ,y e ),(x w ,y w )'s grid value e n , e s , e e , e w If e s +e e =2,e o =2; if e s +e w =2, then set the grid type value e o is 3; if e n +e w =2, then set the grid type value e o is 4; if e n +e e =2, then set the grid type value e o is 5; if e n +e s +e w +e e ≥3, then set the grid type value to e o is 1.

[0089] 2.1.6 Store the transition grid type values ​​into the three-dimensional matrix IM2 according to the corresponding coordinates, that is, IM2(x b ,y b ,z i )=e o .

[0090] 2.2 Perform intra-layer transition along the X-axis direction, determine transition grid types 6 to 9, and store the transition grid type values ​​into IM2 according to the corresponding coordinates, that is, IM2(x i ,y b ,z b )=eo .

[0091] 2.3 Perform intra-layer transition along the Y-axis direction, determine the transition grid types 10 to 13, and store the transition grid type values ​​into IM2 according to the corresponding coordinates, that is, IM2(x b ,y i ,z b )=e o .

[0092] 3. Solve the inter-layer transition information (such as Figure 8b to Figure 8d The three-dimensional matrix IM2 is read, and the mesh type and position coordinates of the tetrahedral mesh and the type II pentahedral mesh are determined according to the interlayer transition condition, and the mesh type value is stored as a three-dimensional matrix IM3 (the matrix dimension is n×w×h) according to the position coordinates.

[0093] 3.1 Determine transitional grid types 14 to 21 (such as Figure 8b to Figure 8c The three-dimensional matrix IM2 is read to obtain the coordinates of the grids with grid type values ​​2 to 5 in the matrix (x2, y2, z2), (x3, y3, z3), (x4, y4, z4), (x5, y5, z5),

[0094] If IM2(x2,y2,z2+1)=1, then set the grid type value to e o is 14;

[0095] If IM2(x2,y2,z2-1)=1, then set the grid type value e o is 18;

[0096] If IM2(x3,y3,z3+1)=1, then set the grid type value to e o is 15;

[0097] If IM2(x3,y3,z3-1)=1, then set the grid type value e o is 19;

[0098] If IM2(x4,y4,z4+1)=1, then set the grid type value to e o is 16;

[0099] If IM2(x4,y4,z4-1)=1, then set the grid type value to e o is 20;

[0100] If IM2(x5,y5,z5+1)=1, then set the grid type value to e o is 17;

[0101] If IM2(x5,y5,z5-1)=1, then set the grid type value to e o is 21.

[0102] 3.2 Determine transitional grid types 22 to 29 (such as Figure 8c to Figure 8d Taking the determination of transitional grid type 22 as an example, the three-dimensional matrix IM2 is read to obtain the grid coordinates (x9, y9, z9) and (x 12 ,y 12 ,z 12 ), if IM2(x9,y9,z9)=0 and IM2(x9+1,y9,z9+1)=1 or 2 or 14, then set the grid type value e o is 22;

[0103] If IM2(x 12 ,y 12 -1,z 12 )=0 and IM2(x 12 ,y 12 -1,z 12 +1)=1 or 2 or 14, then set the grid type value e o is 22.

[0104] 3.3 Store the inter-layer transition grid type value into IM3 according to the corresponding coordinates.

[0105] 4. Generate a finite element model after mesh transition. Integrate the information of the three-dimensional matrices IM1, IM2, and IM3, automatically establish a finite element model without relying on other finite element platforms by combining the mesh type and position coordinates with the mesh size, the number of images, and the spacing between adjacent images to obtain a finite element model after mesh transition.

[0106] This method not only inherits the advantages of previous methods such as wide adaptability, high efficiency, low manual interaction, and high precision, but also uses I-type pentahedral meshes (such as Figure 2 ), Type II pentahedral mesh (such as Figure 3 ), tetrahedral mesh (such as Figure 4 ) The transition optimizes the types and distribution rules of the surface grids of the geometric boundaries located on non-parallel coordinate planes and non-planar geometric boundaries of parallel coordinate planes in the finite element model, making the overall geometric boundary surface of the generated finite element model smoother (such as Figure 5a , 5b ), further improving the quality of the finite element model (as shown in Table 1, which is a quality comparison chart of the spherical finite element model with a radius of 20 generated by traditional manual division, comparison case and the present invention).

[0107] Table 1

[0108]

[0109]

[0110] The geometric boundary of the finite element model in the existing methods is not smooth, resulting in a decrease in the quality of the finite element model and a decrease in the solution accuracy. The present invention proposes a finite element model boundary transition optimization method that not only utilizes the I-type pentahedral grid (such as Figure 2 ), Type II pentahedral mesh (such as Figure 3 ), tetrahedral mesh (such as Figure 4 ) Transition grids 2 to 29 in different orientations (e.g. Figure 7 )according to Figures 8a to 8d The method shown performs transition optimization on the finite element model, improves the quality of the finite element model, and also improves the efficiency of establishing the finite element model through the improved method of establishing the finite element model (as shown in Table 2, which is a comparison chart of the efficiency of establishing the finite element model of a gas turbine blade by traditional manual division, comparison case and the present invention under the same conditions).

[0111] Table 2

[0112]

[0113] In one embodiment of the present invention, a computer device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of a finite element model boundary transition optimization method.

[0114] In one embodiment of the present invention, a finite element model boundary transition optimization method can be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as an independent product. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by a processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data.

[0115] The computer storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO)), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drives (SSDs)), etc.

[0116] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0117] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0120] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, those of ordinary skill in the art should understand that any person familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A finite element model boundary transition optimization method, characterized in that: include: Get the hexahedral mesh information of the geometric model; Using an intra-layer transition algorithm to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain intra-layer transition information; Using an interlayer transition algorithm to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain interlayer transition information; According to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, a finite element model after mesh transition is automatically generated by a finite element reconstruction algorithm based on Python, and the boundary transition optimization of the finite element model is completed.

2. A finite element model boundary transition optimization method according to claim 1, characterized in that: Before obtaining the hexahedral mesh information of the geometric model, the method further includes: Get the binary image of the geometric model, including: The geometric model is sectioned and preprocessed to obtain a binary image of the geometric model, wherein the binary image of the geometric model includes pixel values ​​and pixel coordinates of pixel points.

3. A finite element model boundary transition optimization method according to claim 2, characterized in that: The obtaining of the hexahedral mesh information of the geometric model specifically includes: The pixel values ​​of the pixel points in the binary image of the geometric model are sequentially stored in a three-dimensional matrix according to the pixel coordinates to obtain the hexahedral mesh information of the geometric model.

4. The finite element model boundary transition optimization method according to claim 1, characterized in that: The adopting of the intra-layer transition algorithm to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information to obtain the intra-layer transition information specifically includes: Using an intra-layer transition algorithm to perform boundary detection processing on the hexahedral mesh information to obtain intra-layer transition mesh coordinates; An intra-layer transition algorithm is used to determine the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates to obtain an intra-layer transition grid type value; The intra-layer transition grid type value is stored in a three-dimensional matrix according to the intra-layer transition grid coordinates to obtain the intra-layer transition information.

5. A finite element model boundary transition optimization method according to claim 4, characterized in that: The intra-layer transition algorithm is used to judge the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates to obtain the intra-layer transition grid type value, specifically including: When judging the intra-layer transition grid type corresponding to the intra-layer transition grid coordinates, the grid type around the intra-layer transition grid coordinates is detected, the intra-layer transition grid type is judged, the intra-layer transition grid type is marked, and the intra-layer transition grid type value is obtained.

6. The finite element model boundary transition optimization method according to claim 1, characterized in that: The adopting of the inter-layer transition algorithm to perform boundary detection and inter-layer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information to obtain the inter-layer transition information specifically includes: Using an inter-layer transition algorithm to perform boundary detection processing on the hexahedral mesh information and the intra-layer transition information to obtain inter-layer transition mesh coordinates; An interlayer transition algorithm is used to determine the interlayer transition grid type corresponding to the interlayer transition grid coordinates to obtain an interlayer transition grid type value; The inter-layer transition grid type value is stored in a three-dimensional matrix according to the inter-layer transition grid coordinates to obtain the inter-layer transition information.

7. A finite element model boundary transition optimization method according to claim 6, characterized in that: The interlayer transition algorithm is used to judge the interlayer transition grid type corresponding to the interlayer transition grid coordinates to obtain the interlayer transition grid type value, specifically including: When judging the interlayer transition grid type corresponding to the interlayer transition grid coordinates, the grid type around the interlayer transition grid coordinates is detected, the interlayer transition grid type is judged, the interlayer transition grid type is marked, and the interlayer transition grid type value is obtained.

8. The finite element model boundary transition optimization method according to claim 1, characterized in that: The method of automatically generating a finite element model after mesh transition by using a finite element reconstruction algorithm based on Python according to the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information specifically includes: The finite element reconstruction algorithm based on Python first calculates the node number, node coordinates, unit number and unit node relationship from the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information, combined with the input mesh size, section spacing and number of binary images; The python-based finite element reconstruction algorithm then automatically generates a finite element model after mesh transition based on the node numbers, node coordinates, unit numbers and unit node relationships, as well as the input material properties.

9. A finite element model boundary transition optimization device, characterized in that: include: An acquisition module, used for acquiring hexahedral mesh information of a geometric model; A first processing module is used to perform boundary detection and intra-layer transition mesh type judgment processing on the hexahedral mesh information using an intra-layer transition algorithm to obtain intra-layer transition information; The second processing module is used to perform boundary detection and interlayer transition mesh type judgment processing on the hexahedral mesh information and the intra-layer transition information using an interlayer transition algorithm to obtain interlayer transition information; The model generation module is used to automatically generate a finite element model after mesh transition based on the hexahedral mesh information, the intra-layer transition information and the inter-layer transition information by using a finite element reconstruction algorithm based on Python, so as to complete the boundary transition optimization of the finite element model.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a finite element model boundary transition optimization method according to any one of claims 1 to 8 are implemented.

Images