Adaptive grid generation method and device based on strain energy density error estimation

Abstract

The invention relates to the technical field of engineering simulation, and provides a self-adaptive grid generation method and device based on strain energy density error estimation, in the method, error estimation is carried out by utilizing first strain energy density of a model to be analyzed, a first estimation error of the model to be analyzed can be evaluated more accurately, and then grid division is optimized. The to-be-refined region is refined layer by layer, so that the problem of sudden change of the grid can be avoided, the stability and reliability of a simulation result are improved, the region with higher precision requirement in the initial grid can be refined, the unimportant region is kept unchanged, the calculation amount is greatly reduced, and the calculation efficiency is improved while the calculation precision is ensured. The method improves the calculation efficiency, improves the simulation efficiency, reduces the consumption of calculation resources, and achieves the efficient generation and optimization of a target grid.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering simulation, and in particular to a method and device for adaptive grid generation based on strain energy density error estimation. Background Art

[0002] Finite Element Analysis (FEA) is widely used in various engineering simulations, and meshing is a key factor affecting computational accuracy and efficiency. Traditional meshing methods usually use uniform meshing, which cannot be optimized according to the accuracy requirements of different regions, resulting in overly intensive calculations in areas with high accuracy requirements, while wasting a lot of computing resources in unimportant areas. In order to solve this problem, the adaptive meshing method can be used to optimize the mesh according to the local error distribution of the model, thereby improving computational efficiency and accuracy.

[0003] In the prior art, common adaptive mesh methods usually rely on error estimation methods such as stress field, strain energy density or stress gradient, but often ignore the smooth transition between refined and coarsened areas, which easily leads to numerical instability.

[0004] Therefore, how to achieve efficient meshing while ensuring the calculation accuracy and stability of the model is an important challenge in finite element simulation. Summary of the invention

[0005] The present invention provides an adaptive grid generation method and device based on strain energy density error estimation, which are used to solve the defects in the prior art.

[0006] The present invention provides an adaptive grid generation method based on strain energy density error estimation, comprising: Based on the geometric shape of the model to be analyzed, meshing the model to be analyzed to obtain an initial mesh of the model to be analyzed; Based on the initial grid, perform finite element simulation to calculate a first strain energy density of the model to be analyzed, and perform error estimation based on the first strain energy density to obtain a first estimated error; Based on the first estimation error, a subdivided area in the initial grid is determined, and the subdivided area is refined layer by layer to obtain a target grid.

[0007] According to an adaptive grid generation method based on strain energy density error estimation provided by the present invention, the grid is refined layer by layer on the subdivided area to obtain a target grid, including: Refining the subdivided area layer by layer to obtain an initial refined grid; Based on the initial refined grid, perform finite element simulation to calculate a second strain energy density of the model to be analyzed, and calculate a strain energy density change rate based on the first strain energy density and the second strain energy density; Based on the strain energy density change rate, determining whether the initial refined grid is converged; If the initial refined grid converges, the initial refined grid is determined as the target grid; otherwise, the area in the initial refined grid corresponding to the subdivided area continues to be refined layer by layer.

[0008] According to an adaptive grid generation method based on strain energy density error estimation provided by the present invention, the determining of the subdivided area in the initial grid based on the first estimated error includes: Based on the first estimation error, determining a key area in the initial grid, and determining a multi-layer transition area around the key area; Determining the subdivided area based on the key area and the multi-layer transition area; The step of refining the subdivided area layer by layer to obtain a target grid includes: According to the order of the non-subdivided area, the transition areas of each layer arranged in sequence from the non-subdivided area to the key area, and the key area, the element size is reduced layer by layer to obtain the target grid.

[0009] According to an adaptive grid generation method based on strain energy density error estimation provided by the present invention, the initial grid includes a plurality of initial elements, each of which corresponds to a first strain energy density; the error estimation is performed based on the first strain energy density to obtain a first estimated error, including: Based on the first strain energy density corresponding to each initial element, an error estimation is performed on each initial element to obtain a first estimation error corresponding to each initial element.

[0010] According to an adaptive grid generation method based on strain energy density error estimation provided by the present invention, the initial grid includes a plurality of initial elements, each of which corresponds to a first estimation error; and based on the first estimation error, determining the subdivided area in the initial grid includes: For any initial element, comparing a first estimated error corresponding to the initial element with a preset error threshold; If the first estimation error corresponding to any of the initial elements is greater than the preset error threshold, determining that any of the initial elements is an element to be subdivided; The subdivided area is determined based on the element to be subdivided.

[0011] According to an adaptive grid generation method based on strain energy density error estimation provided by the present invention, the model to be analyzed is a geometric model of a zipper tooth chain.

[0012] According to an adaptive mesh generation method based on strain energy density error estimation provided by the present invention, the initial mesh includes a plurality of initial elements, each of which is a tetrahedral unit.

[0013] The present invention also provides an adaptive grid generation device based on strain energy density error estimation, comprising: A meshing module, used for meshing the model to be analyzed based on the geometric shape of the model to be analyzed to obtain an initial mesh of the model to be analyzed; an error estimation module, configured to perform finite element simulation based on the initial mesh, calculate a first strain energy density of the model to be analyzed, and perform error estimation based on the first strain energy density to obtain a first estimated error; A grid refinement module is used to determine the subdivided area in the initial grid based on the first estimation error, and to refine the subdivided area layer by layer to obtain a target grid.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the adaptive grid generation method based on strain energy density error estimation as described in any one of the above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for adaptive grid generation based on strain energy density error estimation as described in any one of the above is implemented.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-described adaptive grid generation methods based on strain energy density error estimation.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides an adaptive grid generation method and device based on strain energy density error estimation. In this method, the first strain energy density of the model to be analyzed is used for error estimation, which can more accurately evaluate the first estimation error of the model to be analyzed, thereby optimizing the grid division. By refining the area to be refined layer by layer, not only can the problem of grid mutation be avoided, the stability and reliability of the simulation results can be improved, but also the area with higher accuracy requirements in the initial grid can be refined, while keeping the unimportant area unchanged, greatly reducing the amount of calculation, while ensuring the calculation accuracy, improving the calculation efficiency, improving the simulation efficiency, reducing the consumption of computing resources, and realizing the efficient generation and optimization of the target grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings in the following description without paying any creative work.

[0019] Figure 1 It is a schematic flow chart of an adaptive grid generation method based on strain energy density error estimation provided by the present invention; Figure 2 It is a structural schematic diagram of an initial network and a target network in the adaptive grid generation method based on strain energy density error estimation provided by the present invention; Figure 3 It is a structural schematic diagram of an adaptive grid generation device based on strain energy density error estimation provided by the present invention; Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. 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.

[0021] Figure 1 FIG. 1 is a flow chart of an adaptive grid generation method based on strain energy density error estimation provided in an embodiment of the present invention, such as Figure 1 As shown, the method includes: S1, based on the geometric shape of the model to be analyzed, meshing the model to be analyzed to obtain an initial mesh of the model to be analyzed; S2, performing finite element simulation based on the initial grid, calculating a first strain energy density of the model to be analyzed, and performing error estimation based on the first strain energy density to obtain a first estimated error; S3, based on the first estimation error, determining the subdivided area in the initial grid, and refining the subdivided area layer by layer to obtain a target grid.

[0022] Specifically, the adaptive mesh generation method based on strain energy density error estimation provided in the embodiment of the present invention is executed by an adaptive mesh generation device based on strain energy density error estimation, and the device can be configured in a computer, which can be a local computer or a cloud computer. The local computer can be a computer, a tablet, etc., which is not specifically limited here.

[0023] First, step S1 is performed. Using the geometric shape of the model to be analyzed, a finite element simulation tool (such as HyperMesh, Abaqus, Ansys, etc.) can be used to mesh the model to be analyzed to obtain the initial mesh of the model to be analyzed. Here, meshing can be achieved by conventional uniform meshing. The initial mesh is a coarse mesh that can cover the entire computational domain of the model to be analyzed, providing a basis for subsequent error estimation and refinement.

[0024] The initial grid may include multiple initial elements, each of which is a grid unit of the initial grid. The size of each initial element can be set as needed, for example, it can be set to medium precision with a side length of 0.6-2 mm, which is suitable for most areas.

[0025] Then, step S2 is performed, and the initial grid is used to perform finite element simulation, calculate and analyze the key data such as stress and strain of the model to be analyzed, and obtain the first strain energy density of the model to be analyzed. Here, each initial element of the initial grid corresponds to a first strain energy density. The first strain energy density is a comprehensive indicator that reflects the deformation energy of the solid material corresponding to the model to be analyzed under a specific state, and is closely related to stress and strain, so it can indirectly reflect the first estimation error corresponding to each initial element.

[0026] By using the first strain energy density corresponding to each initial element and performing error estimation on each initial element, the first estimated error corresponding to each initial element can be obtained, thereby being able to more accurately evaluate the error distribution of different initial elements in the model to be analyzed. The first estimated error can be determined by the mapping relationship between strain energy density and estimated error. That is: ; in, The initial element The corresponding first estimation error is, The initial element The corresponding first strain energy density.

[0027] Finally, step S3 is performed to determine the subdivided area in the initial grid using the first estimated error. That is, by analyzing the error distribution, the area where stress is concentrated in the initial grid is selected as the subdivided area. For example, for any initial element, the first estimated error corresponding to any initial element can be compared with the preset error threshold. If the first estimated error corresponding to any initial element is greater than the preset error threshold, the any initial element is determined as an element to be subdivided. Here, the preset error threshold can be set as needed, for example, set to 0.1%-1%.

[0028] After determining whether all the initial elements in the initial grid are elements to be subdivided, the elements to be subdivided in the initial grid can be used to form a subdivided region. It can be seen that a subdivided region can include multiple elements to be subdivided.

[0029] Furthermore, the mesh of the subdivided area can be refined layer by layer. For example, the subdivided area can be directly divided into multiple layers in the order of distance from the non-subdivided area from near to far, and the elements to be subdivided in each layer can be divided into multiple small-sized sub-elements. The sizes of the sub-elements in different layers are different, and the sizes of the sub-elements can be gradually reduced in the order of distance from the non-subdivided area from near to far. The element size in the refined subdivided area can be 0.1-0.3 mm to ensure the accuracy of stress distribution. Here, the mesh control function of the finite element simulation tool can be used to achieve layer-by-layer refinement by setting boundary size gradient control or local mesh control.

[0030] Finally, the target mesh can be obtained. The target mesh is the mesh obtained by subdividing the subdivided areas in the initial mesh and keeping the non-subdivided areas unchanged.

[0031] like Figure 2 As shown, the left side is the initial grid, in which the number of elements is 584886, and the right side is the target grid, in which the number of elements is 409423. From the initial grid to the target grid, the number of elements is reduced by about 30%. By comparing with the traditional method, the adaptive grid generation method based on strain energy density error estimation provided in the embodiment of the present invention has great advantages in computational efficiency and accuracy.

[0032] The adaptive mesh generation method based on strain energy density error estimation provided in the embodiment of the present invention first meshes the model to be analyzed based on the geometric shape of the model to be analyzed to obtain the initial mesh of the model to be analyzed; then, based on the initial mesh, finite element simulation is performed to calculate the first strain energy density of the model to be analyzed, and based on the first strain energy density, error estimation is performed to obtain the first estimated error; finally, based on the first estimated error, the subdivided area in the initial mesh is determined, and the subdivided area is refined layer by layer to obtain the target mesh. In this method, the first strain energy density of the model to be analyzed is used for error estimation, which can more accurately evaluate the first estimated error of the model to be analyzed, and then optimize the mesh division. By refining the refined area layer by layer, not only can the problem of mesh mutation be avoided, the stability and reliability of the simulation results can be improved, but also the area with higher accuracy requirements in the initial mesh can be refined, while keeping the unimportant area unchanged, greatly reducing the amount of calculation, while ensuring the calculation accuracy, improving the calculation efficiency, improving the simulation efficiency, reducing the consumption of computing resources, and realizing the efficient generation and optimization of the target mesh.

[0033] On the basis of the above embodiment, the subdivided area is refined layer by layer to obtain a target grid, including: Refining the subdivided area layer by layer to obtain an initial refined grid; Based on the initial refined grid, perform finite element simulation to calculate a second strain energy density of the model to be analyzed, and calculate a strain energy density change rate based on the first strain energy density and the second strain energy density; Based on the strain energy density change rate, determining whether the initial refined grid is converged; If the initial refined grid converges, the initial refined grid is determined as the target grid; otherwise, the region in the initial refined grid corresponding to the subdivided region continues to be refined layer by layer.

[0034] Specifically, when the subdivided area is refined layer by layer, the subdivided area can be refined layer by layer to obtain an initial refined mesh. Then, it can be checked whether the initial refined mesh transition is smooth, especially the connection between the subdivided area and the non-subdivided area, to ensure that there is no excessive mesh mismatch, such as too large mesh aspect ratio.

[0035] Using the initial refined grid, finite element simulation is performed to calculate and analyze key data such as stress and strain of the model to be analyzed, and the second strain energy density of the model to be analyzed is obtained.

[0036] Thereafter, the strain energy density change rate may be calculated using the first strain energy density and the second strain energy density of the same initial element. The strain energy density change rate may be the ratio of the difference between the second strain energy density and the first strain energy density to the first strain energy density.

[0037] The strain energy density change rate can be used to determine whether the initial refined mesh has converged. If the strain energy density change rate is greater than the change rate threshold, it can be determined that the initial refined mesh has converged, otherwise it is determined that the initial refined mesh has not converged. Here, the change rate threshold can be set as needed, for example, it can be set to less than 0.1%, or it can be set to other thresholds, which are not specifically limited here.

[0038] If the initial refined mesh converges, it means that the division of the initial refined mesh reaches the required accuracy, and the initial refined mesh can be determined as the target mesh. Otherwise, the area corresponding to the subdivision area in the initial refined mesh is continuously refined layer by layer until the initial refined mesh converges, and the initial refined mesh is determined as the target mesh.

[0039] Based on the above embodiment, determining the subdivided area in the initial grid based on the first estimation error includes: Based on the first estimation error, determining a key area in the initial grid, and determining a multi-layer transition area around the key area; Determining the subdivided area based on the key area and the multi-layer transition area; The step of refining the subdivided area layer by layer to obtain a target grid includes: According to the order of the non-subdivided area, the transition areas of each layer arranged in sequence from the non-subdivided area to the key area, and the key area, the element size is reduced layer by layer to obtain the target grid.

[0040] Specifically, when determining the subdivided area in the initial grid, the first estimation error can be used to first determine the key area in the initial grid, that is, the area composed of the elements to be subdivided in the initial grid is taken as the key area, and then the multi-layer transition area around the key area is determined, and the key area and the multi-layer transition area are jointly determined as the subdivided area. Here, the transition area can include three layers or other numbers of layers. The gradient rate of the transition area can be 1.3.

[0041] Furthermore, when the subdivided area is meshed layer by layer, the element size can be reduced layer by layer in the order of the non-subdivided area, the transition areas of each layer arranged from the non-subdivided area to the key area, and the key area to obtain the target mesh. That is, the element size in the non-subdivided area, the transition areas of each layer arranged from the non-subdivided area to the key area, and the key area is reduced layer by layer.

[0042] In the embodiment of the present invention, the introduction of the transition area can further ensure smooth transition of each element in the target grid, avoid instability of the simulation result caused by sudden change of element size, and improve the stability and reliability of the simulation result.

[0043] Based on the above embodiment, the model to be analyzed is a geometric model of a zipper chain.

[0044] Specifically, the adaptive mesh generation method based on strain energy density error estimation provided in the embodiment of the present invention can be applied to the geometric model of the zipper tooth chain.

[0045] Furthermore, through calculation, it can be determined that the key area is the tooth head area, sharp corner area, hole area and surrounding area of ​​the zipper tooth chain, and the transition area is determined as the surrounding area of ​​the key area, such as the tooth root area and the contact area between the slider and the tooth chain. The element size in the key area can be 0.1-0.3mm, the element size in the transition area can be 1.5-2 times the element size in the key area, for example, it can be 0.3-0.6mm, and the element size in the non-subdivided area can be 2-3 times the element size in the transition area, for example, it can be 0.6-1mm.

[0046] Based on the above embodiment, the initial grid includes a plurality of initial elements, each of which is a tetrahedral unit.

[0047] Specifically, in the embodiment of the present invention, tetrahedral units are selected as the shape of the initial elements for meshing, which can better adapt to complex geometric shapes, especially when processing curved surfaces or irregular shapes, and can provide accurate mesh representation.

[0048] like Figure 3 As shown, based on the above embodiment, an adaptive grid generation device based on strain energy density error estimation is provided in an embodiment of the present invention, comprising: A meshing module 31 is used to mesh the model to be analyzed based on the geometric shape of the model to be analyzed to obtain an initial mesh of the model to be analyzed; An error estimation module 32 is used to perform finite element simulation based on the initial grid, calculate a first strain energy density of the model to be analyzed, and perform error estimation based on the first strain energy density to obtain a first estimated error; The grid refinement module 33 is used to determine the subdivided area in the initial grid based on the first estimation error, and perform grid refinement on the subdivided area layer by layer to obtain a target grid.

[0049] On the basis of the above-mentioned embodiment, in the adaptive grid generation device based on strain energy density error estimation provided in the embodiment of the present invention, the grid refinement module is specifically used for: Refining the subdivided area layer by layer to obtain an initial refined grid; Based on the initial refined grid, perform finite element simulation to calculate a second strain energy density of the model to be analyzed, and calculate a strain energy density change rate based on the first strain energy density and the second strain energy density; Based on the strain energy density change rate, determining whether the initial refined grid is converged; If the initial refined grid converges, the initial refined grid is determined as the target grid; otherwise, the area in the initial refined grid corresponding to the subdivided area continues to be refined layer by layer.

[0050] On the basis of the above-mentioned embodiment, in the adaptive grid generation device based on strain energy density error estimation provided in the embodiment of the present invention, the grid refinement module is specifically used for: Based on the first estimation error, determining a key area in the initial grid, and determining a multi-layer transition area around the key area; Determining the subdivided area based on the key area and the multi-layer transition area; The step of refining the subdivided area layer by layer to obtain a target grid includes: According to the order of the non-subdivided area, the transition areas of each layer arranged in sequence from the non-subdivided area to the key area, and the key area, the element size is reduced layer by layer to obtain the target grid.

[0051] On the basis of the above-mentioned embodiment, in the adaptive grid generation device based on strain energy density error estimation provided in the embodiment of the present invention, the error estimation module is specifically used for: Based on the first strain energy density corresponding to each initial element, an error estimation is performed on each initial element to obtain a first estimation error corresponding to each initial element.

[0052] On the basis of the above-mentioned embodiment, in the adaptive grid generation device based on strain energy density error estimation provided in the embodiment of the present invention, the initial grid includes a plurality of initial elements, each of which corresponds to a first estimation error; The grid refinement module is specifically used for: For any initial element, comparing a first estimated error corresponding to the initial element with a preset error threshold; If the first estimation error corresponding to any of the initial elements is greater than the preset error threshold, determining that any of the initial elements is an element to be subdivided; The subdivided area is determined based on the element to be subdivided.

[0053] On the basis of the above-mentioned embodiment, in the adaptive mesh generation device based on strain energy density error estimation provided in the embodiment of the present invention, the model to be analyzed is a geometric model of a zipper tooth chain.

[0054] On the basis of the above-mentioned embodiment, in the adaptive mesh generation device based on strain energy density error estimation provided in the embodiment of the present invention, the initial mesh includes a plurality of initial elements, and each initial element is a tetrahedral unit.

[0055] Specifically, the functions of each module in the adaptive grid generation device based on strain energy density error estimation provided in the embodiment of the present invention correspond one-to-one to the operation flow of each step in the above-mentioned method embodiment, and the effects achieved are also consistent. Please refer to the above-mentioned embodiment for details, which will not be repeated in the embodiment of the present invention.

[0056] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor (Processor) 410, a communication interface (Communications Interface) 420, a memory (Memory) 430 and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the adaptive grid generation method based on strain energy density error estimation provided in the above embodiments.

[0057] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0058] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the adaptive grid generation method based on strain energy density error estimation provided in the above embodiments.

[0059] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the adaptive grid generation method based on strain energy density error estimation provided in the above embodiments.

[0060] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0061] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive grid generation method based on strain energy density error estimation, characterized in that: include: Based on the geometric shape of the model to be analyzed, meshing the model to be analyzed to obtain an initial mesh of the model to be analyzed; Based on the initial grid, perform finite element simulation to calculate a first strain energy density of the model to be analyzed, and perform error estimation based on the first strain energy density to obtain a first estimated error; Based on the first estimation error, a subdivided area in the initial grid is determined, and the subdivided area is refined layer by layer to obtain a target grid.

2. The adaptive grid generation method based on strain energy density error estimation according to claim 1, characterized in that: The step of refining the subdivided area layer by layer to obtain a target grid includes: Refining the subdivided area layer by layer to obtain an initial refined grid; Based on the initial refined grid, perform finite element simulation to calculate a second strain energy density of the model to be analyzed, and calculate a strain energy density change rate based on the first strain energy density and the second strain energy density; Based on the strain energy density change rate, determining whether the initial refined grid is converged; If the initial refined grid converges, the initial refined grid is determined as the target grid; otherwise, the area in the initial refined grid corresponding to the subdivided area continues to be refined layer by layer.

3. The adaptive grid generation method based on strain energy density error estimation according to claim 1, characterized in that: The determining, based on the first estimation error, a subdivided area in the initial grid comprises: Based on the first estimation error, determining a key area in the initial grid, and determining a multi-layer transition area around the key area; Determining the subdivided area based on the key area and the multi-layer transition area; The step of refining the subdivided area layer by layer to obtain a target grid includes: According to the order of the non-subdivided area, the transition areas of each layer arranged in sequence from the non-subdivided area to the key area, and the key area, the element size is reduced layer by layer to obtain the target grid.

4. The adaptive grid generation method based on strain energy density error estimation according to claim 1, characterized in that: The initial grid includes a plurality of initial elements, each of which corresponds to a first strain energy density; The performing error estimation based on the first strain energy density to obtain a first estimated error includes: Based on the first strain energy density corresponding to each initial element, an error estimation is performed on each initial element to obtain a first estimation error corresponding to each initial element.

5. The adaptive grid generation method based on strain energy density error estimation according to any one of claims 1 to 4, characterized in that: The initial grid includes a plurality of initial elements, each of which corresponds to a first estimation error; The determining, based on the first estimation error, a subdivided area in the initial grid comprises: For any initial element, comparing a first estimated error corresponding to the initial element with a preset error threshold; If the first estimation error corresponding to any of the initial elements is greater than the preset error threshold, determining that any of the initial elements is an element to be subdivided; The subdivided area is determined based on the element to be subdivided.

6. The adaptive grid generation method based on strain energy density error estimation according to any one of claims 1 to 4, characterized in that: The model to be analyzed is a geometric model of a zipper tooth chain.

7. The adaptive grid generation method based on strain energy density error estimation according to any one of claims 1 to 4, characterized in that: The initial grid includes a plurality of initial elements, each of which is a tetrahedral unit.

8. An adaptive grid generation device based on strain energy density error estimation, characterized in that: include: A meshing module, used for meshing the model to be analyzed based on the geometric shape of the model to be analyzed to obtain an initial mesh of the model to be analyzed; an error estimation module, configured to perform finite element simulation based on the initial mesh, calculate a first strain energy density of the model to be analyzed, and perform error estimation based on the first strain energy density to obtain a first estimated error; A grid refinement module is used to determine the subdivided area in the initial grid based on the first estimation error, and to refine the subdivided area layer by layer to obtain a target grid.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the adaptive grid generation method based on strain energy density error estimation according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the adaptive grid generation method based on strain energy density error estimation according to any one of claims 1 to 7 is implemented.

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