Grid generation method, electromagnetic simulation method, device, equipment, medium and product

Abstract

The invention relates to the technical field of electromagnetic field numerical values, and discloses a grid generation method, an electromagnetic simulation method, a device, equipment, a medium and a product, and the method comprises the steps: extracting a plurality of feature points from a metal geometric model, the plurality of feature points being used for representing key points enabling an electromagnetic field to generate singular behaviors in the metal geometric model; determining the maximum grid step length according to the shortest wavelength and the longest side of a bounding box of the metal geometric model; the minimum grid step length, the grid encryption area, the encryption step length and the grid smoothing factor are determined, the encryption step length is the grid step length of the grid encryption area, and the grid smoothing factor is used for representing the change rate between every two adjacent grid step lengths; and according to the plurality of feature points, the maximum grid step length, the minimum grid step length, the grid encryption area, the encryption step length and the grid smoothing factor, generating a plurality of grid points so as to divide the metal geometric model into a plurality of grids. According to the method, the calculation efficiency and the result precision of the FIT algorithm can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic field numerical calculation technology, specifically to a mesh generation method, an electromagnetic simulation method, a device, equipment, medium, and product. Background Technology

[0002] The Finite Integration Technique (FIT) is a numerical analysis method for solving Maxwell's equations, widely used in the simulation and analysis of electromagnetic fields and electromagnetic wave propagation. Traditional FIT methods typically use uniform grids to discretize the computational domain. However, when dealing with complex geometries or multi-scale problems, uniform grids have significant limitations, such as low computational efficiency and excessive memory requirements. To improve computational efficiency and accuracy, non-uniform grid techniques have gained increasing attention.

[0003] Currently, non-uniform mesh generation technology relies on manual adjustment or simple automated rules. When dealing with scenes with complex boundaries or multiple material interfaces, it is difficult to fully consider the coupling relationship between geometric features and electromagnetic properties, which may lead to low simulation accuracy. Summary of the Invention

[0004] In view of this, the present invention provides a mesh generation method, an electromagnetic simulation method, an apparatus, a device, a medium, and a product to solve the problem that non-uniform mesh generation technology relies on manual adjustment or simple automated rules, resulting in low simulation accuracy.

[0005] In a first aspect, the present invention provides a mesh generation method, the method comprising: extracting multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that cause singular behavior of the electromagnetic field; determining a maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometric model; determining a minimum mesh step size, a mesh refinement region, a refinement step size, and a mesh smoothing factor, wherein the refinement step size is the mesh step size of the mesh refinement region, the refinement step size is less than the maximum mesh step size and greater than the minimum mesh step size, and the mesh smoothing factor is used to characterize the rate of change between two adjacent mesh step sizes; and generating multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor to divide the metal geometric model into multiple meshes.

[0006] In this embodiment, extracting multiple feature points from the metal geometric model allows for precise location of areas with drastic field changes. This not only enables targeted mesh refinement, ensuring computational reliability, but also allows the mesh generation algorithm to identify critical geometric feature areas (boundaries, gaps, and holes in the metal geometric model that affect the electromagnetic field propagation path). This allows more mesh lines to actively pass through or conform to these critical areas, avoiding omissions or miscalculations caused by misalignment between the gateway and geometric features. Furthermore, by limiting the maximum and minimum mesh step sizes, mesh refinement areas, and mesh smoothing factors, the quality and efficiency of mesh generation can be effectively improved, making it applicable to various electromagnetic simulation scenarios.

[0007] In one optional implementation, multiple grid points are generated based on multiple feature points, a maximum grid step size, a minimum grid step size, a grid densification region, a densification step size, and a grid smoothing factor. This includes: deleting or merging multiple feature points based on the minimum grid step size to obtain updated feature points; generating multiple grid points under the constraints of the updated feature points, maximum grid step size, minimum grid step size, grid densification region, and densification step size, wherein the multiple grid points are located in multiple intervals, each interval corresponding to a different grid step size; smoothing the grid step sizes corresponding to different intervals based on the grid smoothing factor to obtain smoothed grid step sizes; and inserting new grid points between the multiple grid points according to the smoothed grid step size.

[0008] In one optional implementation, determining the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model includes: determining a first mesh step size based on the shortest wavelength and a first preset factor; determining a second mesh step size based on the longest side of the bounding box of the metal geometry model and a second preset factor; and determining the minimum value between the first mesh step size and the second mesh step size as the maximum mesh step size.

[0009] In this embodiment, the global maximum mesh step size is limited by simultaneously considering the shortest wavelength and geometric features (maximum edge of the bounding box). The upper limit is taken as the smaller value between the "wavelength resolution principle" and the "geometric resolution principle". This ensures that sufficient electromagnetic field resolution is maintained in high-frequency or small electrical size models, and avoids the problem of unreasonable mesh setting (too sparse or too dense) caused by only considering geometry or only considering wavelength.

[0010] In one optional implementation, determining the minimum grid step size, the grid densification region, the densification step size, and the grid smoothing factor includes: determining the minimum grid step size based on the maximum grid step size and a third preset factor; determining the densification step size based on the maximum grid step size and a fourth preset factor, wherein the fourth preset factor is less than the third preset factor; and determining the grid densification region and the grid smoothing factor in response to a user's operation.

[0011] In this embodiment, by setting a minimum mesh step size limit, the computational load and memory requirements are prevented from exploding due to excessively fine meshes. Simultaneously, the minimum step size limit can be appropriately relaxed when needed based on finer structures (such as patch details), thus maintaining the resolution of local details while controlling computational resource consumption. By limiting the rate of change of adjacent mesh step sizes, a smooth transition is ensured when the mesh size changes, avoiding numerical dispersion or pseudomorphic phenomena caused by excessive "step skipping." This approach ensures accurate calculation of the refined regions while also considering numerical stability and overall mesh quality.

[0012] In one alternative implementation, the grid smoothing factor ranges from 1.2 to 1.5.

[0013] In one optional implementation, the plurality of feature points include at least one of the following: coordinate points in two directions of the coordinate plane traversed by the edge of the metal geometry model parallel to the coordinate axis; coordinate points in the axial direction perpendicular to the coordinate plane of the surface of the metal geometry model parallel to the coordinate plane; coordinates of the center of the arc edge of the metal geometry model parallel to the coordinate plane and the coordinate points of its bounding box in two directions of the coordinate plane; coordinates of the bounding box of the sphere model in the metal geometry model and the coordinate points of the center of the sphere in three coordinate axis directions; and coordinate points of the cylinder model in the metal geometry model whose height direction is parallel to the coordinate axis and the coordinate points of the center point of the cylinder model in three coordinate axis directions.

[0014] Secondly, the present invention provides an electromagnetic simulation method, comprising: extracting multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause singular behavior of the electromagnetic field; determining a maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometric model; determining a minimum mesh step size, a mesh refinement region, a refinement step size, and a mesh smoothing factor, wherein the refinement step size is the mesh step size of the mesh refinement region, the refinement step size is less than the maximum mesh step size and greater than the minimum mesh step size, and the mesh smoothing factor is used to characterize the rate of change between two adjacent mesh step sizes; generating multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor to divide the metal geometric model into multiple meshes; and inputting the meshed metal geometric model into a finite integral method solver for simulation calculation to obtain the electromagnetic field distribution results of the metal component corresponding to the metal geometric model.

[0015] The electromagnetic simulation method provided in this embodiment uses the mesh generation method provided in the above embodiment to mesh the metal geometric model. Then, the meshed metal geometric model is input into the FIT solver for simulation calculation to obtain the electromagnetic field distribution results of the metal component. This embodiment, by using the mesh generation method provided in the above embodiment, can generate reliable non-uniform FIT mesh lines, thereby effectively improving the computational efficiency and accuracy of the FIT algorithm.

[0016] Thirdly, the present invention provides a mesh generation apparatus, comprising: an extraction module for extracting multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause singular behavior of the electromagnetic field; a first determination module for determining a maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometric model; a second determination module for determining a minimum mesh step size, a mesh refinement region, a refinement step size, and a mesh smoothing factor, wherein the refinement step size is the mesh step size of the mesh refinement region, the refinement step size is less than the maximum mesh step size and greater than the minimum mesh step size, and the mesh smoothing factor is used to characterize the rate of change between two adjacent mesh step sizes; and a mesh division module for generating multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor, so as to divide the metal geometric model into multiple meshes.

[0017] In one optional implementation, the mesh generation module includes: a deletion / merging processing unit, used to delete or merge multiple feature points according to the minimum mesh step size to obtain updated feature points; a generation unit, used to generate multiple mesh points under the constraints of the updated feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, and the refinement step size, wherein the multiple mesh points are located in multiple intervals, and the mesh step size corresponding to each interval is different; a smoothing processing unit, used to smooth the mesh step size corresponding to different intervals according to the mesh smoothing factor to obtain a smoothed mesh step size; and an insertion unit, used to insert new mesh points between the multiple mesh points according to the smoothed mesh step size.

[0018] In one optional implementation, the first determining module includes: a first determining unit, configured to determine a first grid step size based on the shortest wavelength and a first preset factor; a second determining unit, configured to determine a second grid step size based on the longest side of the bounding box of the metal geometric model and a second preset factor; and a third determining unit, configured to determine the minimum value of the first grid step size and the second grid step size as the maximum grid step size.

[0019] In one optional implementation, the second determining module includes: a fourth determining unit, configured to determine a minimum grid step size based on a maximum grid step size and a third preset factor; a fifth determining unit, configured to determine an encryption step size based on a maximum grid step size and a fourth preset factor, wherein the fourth preset factor is less than the third preset factor; and a sixth determining unit, configured to determine a grid encryption region and a grid smoothing factor in response to a user's operation.

[0020] In one alternative implementation, the grid smoothing factor ranges from 1.2 to 1.5.

[0021] In one optional implementation, the plurality of feature points include at least one of the following: coordinate points in two directions of the coordinate plane traversed by the edge of the metal geometry model parallel to the coordinate axis; coordinate points in the axial direction perpendicular to the coordinate plane of the surface of the metal geometry model parallel to the coordinate plane; coordinates of the center of the arc edge of the metal geometry model parallel to the coordinate plane and the coordinate points of its bounding box in two directions of the coordinate plane; coordinates of the bounding box of the sphere model in the metal geometry model and the coordinate points of the center of the sphere in three coordinate axis directions; and coordinate points of the cylinder model in the metal geometry model whose height direction is parallel to the coordinate axis and the coordinate points of the center point of the cylinder model in three coordinate axis directions.

[0022] Fourthly, the present invention provides an electromagnetic simulation device, comprising: an extraction module for extracting multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause singular behavior of the electromagnetic field; a first determination module for determining a maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometric model; a second determination module for determining a minimum mesh step size, a mesh refinement region, a refinement step size, and a mesh smoothing factor, wherein the refinement step size is the mesh step size of the mesh refinement region, the refinement step size is less than the maximum mesh step size and greater than the minimum mesh step size, and the mesh smoothing factor is used to characterize the rate of change between two adjacent mesh step sizes; a mesh generation module for generating multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor, so as to divide the metal geometric model into multiple meshes; and an electromagnetic simulation module for inputting the meshed metal geometric model into a finite integral method solver for simulation calculation to obtain the electromagnetic field distribution results of the metal parts corresponding to the metal geometric model.

[0023] Fifthly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the mesh generation method of the first aspect or any corresponding embodiment thereof, or to perform the electromagnetic simulation method of the second aspect or any corresponding embodiment thereof.

[0024] In a sixth aspect, the present invention provides a computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the mesh generation method of the first aspect or any corresponding embodiment thereof, or to execute the electromagnetic simulation method of the second aspect or any corresponding embodiment thereof.

[0025] In a seventh aspect, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the mesh generation method of the first aspect or any corresponding embodiment thereof, or to execute the electromagnetic simulation method of the second aspect or any corresponding embodiment thereof. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating a mesh generation method according to an embodiment of the present invention;

[0028] Figure 2 This is a flowchart illustrating another mesh generation method according to an embodiment of the present invention;

[0029] Figure 3 This is a flowchart illustrating an electromagnetic simulation method according to an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of the geometric model of a patch antenna according to an embodiment of the present invention;

[0031] Figure 5 This is a schematic diagram of the geometric model of a patch antenna with hidden dielectric material according to an embodiment of the present invention;

[0032] Figure 6 This is a flowchart illustrating another electromagnetic simulation method according to an embodiment of the present invention;

[0033] Figure 7 This is a schematic diagram of adding local mesh settings to four radial patches according to an embodiment of the present invention;

[0034] Figure 8 This is a schematic diagram illustrating the addition of a local mesh setting to the intermediate patch according to an embodiment of the present invention;

[0035] Figure 9This is a schematic diagram illustrating the global grid setting and grid data generation according to an embodiment of the present invention;

[0036] Figure 10 This is a schematic diagram of the grid distribution of the YOZ coordinate plane according to an embodiment of the present invention;

[0037] Figure 11 This is a schematic diagram of the grid distribution of the XOZ coordinate plane according to an embodiment of the present invention;

[0038] Figure 12 This is a schematic diagram of the grid distribution in the XOY coordinate plane according to an embodiment of the present invention;

[0039] Figure 13 This is a schematic diagram illustrating the variation of S-parameters with frequency obtained by the FIT solver according to an embodiment of the present invention;

[0040] Figure 14 This is a structural block diagram of a mesh generation device according to an embodiment of the present invention;

[0041] Figure 15 This is a structural block diagram of an electromagnetic simulation device according to an embodiment of the present invention;

[0042] Figure 16 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention.

[0043] Reference numerals: 400, patch antenna; 410, dielectric substrate; 420, radiating patch; 430, intermediate patch; 701, parameter input interface; 1401, extraction module; 1402, first determination module; 1403, second determination module; 1404, mesh generation module; 1501, electromagnetic simulation module; 1610, processor; 1620, memory; 1630, input device; 1640, output device. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0045] The mesh in the mesh generation method provided by this invention refers to a non-uniform FIT mesh. The mesh generation method and electromagnetic simulation method are applied to electromagnetic field simulation software based on the FIT algorithm.

[0046] To facilitate understanding of the present invention, the relevant terms involved in the present invention will be introduced before describing the technical solutions of the present invention.

[0047] (1) FIT

[0048] FIT (Fixed Integral Method) is a numerical computation method for solving physical field problems such as electromagnetic fields by solving Maxwell's equations. Its core idea is based on a discretized integral form of Maxwell's equations. By directly processing the integral relationships of field quantities on a discrete grid, it avoids the accuracy loss that may occur during the discretization process of traditional differential forms. It has advantages such as simplicity, intuitiveness, time-domain solution, and suitability for parallel computation. The FIT algorithm is an important tool in the field of electromagnetic simulation and is suitable for solving complex geometries and high-frequency electromagnetic problems.

[0049] (2) Enclosing box

[0050] Bounding box is an algorithm for finding the optimal bounding space of a discrete point set. The basic idea is to use a geometric object with a slightly larger volume and simpler properties (called a bounding box) to approximate a complex geometric object.

[0051] Common bounding box algorithms include Axis-Aligned Bounding Box (AABB), Sphere Bounding Box, Oriented Bounding Box (OBB), and Fixed-Direction Hull (FDH).

[0052] In electromagnetic field calculations based on the FIT algorithm, using bounding boxes to simplify complex models into simple geometries can significantly reduce the amount of computation.

[0053] (3) Non-uniform mesh

[0054] The key to non-uniform meshes lies in rationally adjusting the mesh size and distribution based on the geometric and electromagnetic characteristics of the problem. For example, a denser mesh is used in regions with complex geometry or drastic field changes, while a sparser mesh is used in regions with gradual changes or large feature sizes. Using non-uniform meshes to partition the geometric model not only reduces computational and storage requirements but also adapts to multi-scale characteristics and complex geometries while maintaining accuracy.

[0055] However, as mentioned in the background section, current non-uniform mesh generation techniques rely on manual adjustments or simple automated rules. When dealing with scenes with complex boundaries or multiple material interfaces, the mesh generation is unreasonable, resulting in low simulation accuracy.

[0056] In view of this, the present invention provides a mesh generation method, an electromagnetic simulation method, an apparatus, a device, a medium, and a product. By combining actual electromagnetic field simulation scenarios and employing a mesh generation strategy that utilizes features extracted from metal geometric models, global maximum and minimum mesh constraints, and smooth mesh transitions, reliable non-uniform FIT mesh lines can be automatically generated. This effectively improves the computational efficiency and result accuracy of the FIT algorithm, providing a more reliable solution for numerical simulation of complex electromagnetic environments.

[0057] The mesh generation method and electromagnetic simulation method provided by the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than that shown here.

[0058] This embodiment provides a mesh generation method that can be used in a computer device equipped with electromagnetic field simulation software based on the FIT algorithm. Figure 1 This is a flowchart illustrating a mesh generation method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes the following steps:

[0059] Step S101: Extract multiple feature points from the metal geometric model.

[0060] Among them, multiple feature points are used to characterize the key points in the metal geometric model that cause the electromagnetic field to produce strange behavior (such as discontinuity or abrupt changes in field strength).

[0061] Specifically, in electromagnetic field simulations, the changes in electric and magnetic fields at the tips or acute angles, boundaries, gaps, and holes of a metal geometric model are more drastic compared to other locations. The inventors discovered that by ensuring as many mesh lines as possible pass through these areas of drastic field change during mesh generation, the reliability of the FIT algorithm's calculation results can be improved. Therefore, combining simulation models from most practical electromagnetic engineering projects, a strategy for identifying geometric key points and extracting mesh feature lines was configured in the electromagnetic field simulation software for computer equipment. This allows the software to extract multiple feature points from the metal geometric model. These multiple feature points include feature points of the metal geometric model along the three coordinate axes.

[0062] For example, the feature point extraction rules for metal geometric models can be shown in Table 1:

[0063] Table 1 Feature point extraction rules for geometric models

[0064]

[0065] Based on the extraction rules in Table 1, the multiple feature points extracted by the electromagnetic simulation software from the metal geometric model may include the coordinate points in two directions of the coordinate plane traversed by the edge of the metal geometric model parallel to the coordinate axis, the coordinate points of the surface of the metal geometric model parallel to the coordinate plane in the axis direction perpendicular to the coordinate plane, the coordinates of the center of the arc edge of the metal geometric model parallel to the coordinate plane and the coordinate points of its bounding box in two directions of the coordinate plane, the coordinates of the bounding box of the sphere model in the metal geometric model and the coordinate points of the center of the sphere in three coordinate axis directions, and at least one of the coordinate points of the cylinder model whose height direction is parallel to the coordinate axis and the center point of the cylinder model in three coordinate axis directions.

[0066] Specifically, the metal geometry model can be a model of the metal component to be simulated, created in electromagnetic field simulation software or 3D design software (such as SolidWorks). The metal component can be a patch antenna, a semiconductor chip, or other metal parts that require electromagnetic simulation. When the metal geometry model is a model of the metal component to be simulated created in 3D design software, the metal geometry model needs to be imported into the electromagnetic field simulation software.

[0067] Step S102: Determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model.

[0068] In the FIT algorithm, since an excessively large grid size may make it difficult to accurately simulate the propagation of electromagnetic waves, it is necessary to limit the global maximum grid size.

[0069] The shortest wavelength refers to the smallest wavelength corresponding to the propagation of electromagnetic waves within the frequency range of interest. The shortest wavelength is determined based on the highest frequency within the frequency range of interest and the medium in which the electromagnetic wave is located. The frequency range of interest refers to the range of electromagnetic wave frequencies that the metal component corresponding to the metal geometric model needs to focus on. For example, the frequency range of interest can be the operating frequency range, interference frequency range, or resonant frequency range of the metal geometric model.

[0070] For example, the maximum mesh step size can be determined by the average or minimum value of the mesh step size determined based on the shortest wavelength and the mesh step size determined based on the longest side of the bounding box of the metal geometry model. In other words, the present invention determines the maximum mesh step size based on the shortest wavelength resolution principle and the geometric resolution principle.

[0071] Specifically, when determining the maximum mesh step size, considering the shortest wavelength resolution principle ensures that the mesh can distinguish the details of electromagnetic wave fluctuations, thereby ensuring the accuracy of the simulation results. Considering the geometric resolution principle can avoid the problem of overly coarse meshes that cannot distinguish key geometric details in electrically small (very small electrical dimensions but complex geometry) metal geometric models, where the mesh step size is limited solely based on the shortest wavelength resolution principle.

[0072] Step S103: Determine the minimum grid step size, grid refinement area, refinement step size, and grid smoothing factor.

[0073] The encryption step size is the grid step size of the encrypted area. The encryption step size is less than the maximum grid step size and greater than the minimum grid step size. The grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes.

[0074] Specifically, in FIT simulation, in addition to meeting the maximum mesh size limit, it is also necessary to limit the minimum mesh size. By limiting the minimum mesh size, numerical and engineering problems caused by excessively fine meshes can be avoided.

[0075] It should be understood that the finer the mesh, the more meshes there are in the entire computational domain, and the amount of field storage and updates required by the FIT algorithm will increase cubically. The time step, according to the Courant condition, will further decrease as the mesh becomes finer, meaning that more time steps are needed to achieve the same simulation duration. Therefore, to avoid the surge in memory and computational costs caused by small mesh sizes, this invention imposes certain limitations on the minimum mesh size.

[0076] The Courant condition is a key criterion for ensuring the stability of numerical calculations. Essentially, it restricts the ratio between the time step and the spatial grid size in numerical simulations, ensuring that the propagation distance of physical quantities within a time step does not exceed the size of a spatial grid.

[0077] For example, electromagnetic simulation software can determine the minimum grid step size based on user input, or it can divide the maximum grid step size by a specific factor to obtain the minimum grid step size.

[0078] Mesh refinement can be applied to areas of a metal geometry model where the electromagnetic field is locally enhanced or suddenly abruptly changed, such as edges, boundaries, sharp points or acute angles, gaps, and holes. Refining these areas can reduce numerical errors, dispersion, and prevent the omission of key physical effects, thereby improving the accuracy of simulation results.

[0079] For example, electromagnetic simulation software can determine the mesh refinement area and refinement step size based on user input, or it can determine the location of multiple feature points as the mesh refinement area and determine the refinement step size based on the maximum and minimum mesh step sizes. For example, the average of the maximum and minimum mesh step sizes can be determined as the refinement step size.

[0080] This embodiment can fully combine the geometric features and electromagnetic properties of the electromagnetic simulation model. By extracting information such as geometric feature points and feature lines of the model, and combining it with areas where the electromagnetic field is prone to drastic changes (such as acute angles, metal edges, gaps and holes), it can achieve non-uniform mesh division with local densification at key locations.

[0081] Specifically, the grid smoothing factor SmoothRatio can be defined as shown in Equation (1):

[0082]

[0083] In formula (1), Δ0 and Δ1 represent the step size of two adjacent grids.

[0084] For example, electromagnetic simulation software can limit the rate of change between two adjacent grid steps by using a grid smoothing factor, which can keep the grid step size changing smoothly in space and reduce the discontinuity of local field quantities.

[0085] In FIT mesh generation, the scale variation between adjacent meshes cannot be too drastic, because when the size difference between adjacent meshes is too large, the FIT update equation may produce numerical dispersion, pseudo-mode, or local numerical instability at the mesh boundary.

[0086] Step S104: Generate multiple mesh points based on multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size, and mesh smoothing factor to divide the metal geometry model into multiple meshes.

[0087] Specifically, after determining multiple feature points, maximum grid step size, minimum grid step size, grid refinement region, refinement step size, and grid smoothing factor, the mesh generation algorithm in the electromagnetic simulation software generates multiple grid points under the constraints of these parameters, dividing the metal geometric model into multiple grids.

[0088] The mesh generation method provided in this embodiment extracts multiple feature points from the metal geometric model after loading it onto the metal geometric model. At the same time, it determines the maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size, and mesh smoothing factor based on the shortest wavelength and the longest side of the bounding box of the metal geometric model. Then, based on the multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size, and mesh smoothing factor, it generates multiple mesh points, dividing the metal geometric model into multiple meshes.

[0089] In this embodiment, extracting multiple feature points from the metal geometric model allows for precise location of areas with drastic field changes. This not only enables targeted mesh refinement, ensuring computational reliability, but also allows the mesh generation algorithm to identify critical geometric feature areas (boundaries, gaps, and holes in the metal geometric model that affect the electromagnetic field propagation path). This allows more mesh lines to actively pass through or conform to these critical areas, avoiding omissions or miscalculations caused by misalignment between the gateway and geometric features. Furthermore, by limiting the maximum and minimum mesh step sizes, mesh refinement areas, and mesh smoothing factors, the quality and efficiency of mesh generation can be effectively improved, making it applicable to various electromagnetic simulation scenarios.

[0090] This embodiment also provides another mesh generation method, which can be used in a computer device equipped with electromagnetic field simulation software based on the FIT algorithm. Figure 2 This is a flowchart illustrating another mesh generation method according to an embodiment of the present invention, such as... Figure 2 As shown, the method includes the following steps:

[0091] Step S201: Extract multiple feature points from the metal geometric model.

[0092] Please see details Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0093] Step S202: Determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model.

[0094] Specifically, step S202 includes:

[0095] Step S2021: Determine the first grid step size based on the shortest wavelength and the first preset factor.

[0096] The first preset factor can be a default value configured in the electromagnetic simulation software, or it can be input by the user into the electromagnetic simulation software. The first preset factor can be any value within the range of 10 to 20. For example, the first preset factor can be 10, 12, 15, 17, 19 or 20, etc.

[0097] Specifically, after determining the shortest wavelength and the first preset factor, the first grid step size can be determined using the following formula (2):

[0098]

[0099] In formula (2), λ represents the first grid step size. min N represents the shortest wavelength, and N1 represents the first preset factor.

[0100] In this embodiment, a shortest wavelength is divided into 10 to 20 units, which can achieve a relatively balanced accuracy and computational cost in most simulations.

[0101] Step S2022: Determine the second mesh step size based on the longest side of the bounding box of the metal geometry model and the second preset factor.

[0102] The second preset factor can be a resolution factor specified by the user. For example, the second preset factor can be any value between 10 and 20, such as 10, 14, 15, 16, 18, or 20. The second preset factor and the first preset factor can be the same or different. When they are different, the second preset factor can be greater than or less than the first preset factor.

[0103] Specifically, after determining the longest side of the bounding box of the metal geometry model and the second preset factor, the second mesh step size can be determined by the following formula (3):

[0104]

[0105] In formula (3), L represents the second grid step size. max N represents the longest side of the bounding box of the metal geometry model. geom This represents the second preset factor.

[0106] In this embodiment, the ratio of the longest side of the bounding box of the metal geometry model to the second preset factor is determined as the second mesh step size. This ensures that even when the electrical size of the metal geometry model is very small, there is still a certain number of mesh divisions in the geometry, so that the mesh is spatially sufficient to capture the key details of the structure.

[0107] Step S2023: Determine the minimum value between the first grid step size and the second grid step size as the maximum grid step size.

[0108] Specifically, after determining the first and second grid step sizes, the maximum grid step size can be determined using the following formula (4):

[0109]

[0110] In formula (4), gMaxStepLimit represents the maximum grid step size. That is, when the first grid step size is less than or equal to the second grid step size, the first grid step size is determined as the maximum grid step size; when the first grid step size is greater than the second grid step size, the second grid step size is determined as the maximum grid step size.

[0111] In summary, this embodiment considers both wavelength resolution and geometric feature resolution in the actual simulation analysis of the FIT algorithm, and takes the smaller of the two as the maximum grid step size (the upper limit of the global grid step size).

[0112] In this embodiment, the global maximum mesh step size is limited by simultaneously considering the shortest wavelength and geometric features (maximum edge of the bounding box). The upper limit is taken as the smaller value between the "wavelength resolution principle" and the "geometric resolution principle". This ensures that sufficient electromagnetic field resolution is maintained in high-frequency or small electrical size models, and avoids the problem of unreasonable mesh setting (too sparse or too dense) caused by only considering geometry or only considering wavelength.

[0113] Step S203: Determine the minimum grid step size, grid refinement area, refinement step size, and grid smoothing factor.

[0114] For example, step S203 above may include steps a1 to a3:

[0115] Step a1: Determine the minimum grid step size based on the maximum grid step size and the third preset factor.

[0116] The third preset factor can be the default value configured in the electromagnetic simulation software, or it can be input by the user into the electromagnetic simulation software. The third preset factor can be any value within the range of 15 to 20. For example, the third preset factor can be 15, 16, 17, 18 or 20, etc.

[0117] Specifically, after determining the maximum grid step size and the third preset factor, the minimum grid step size can be determined using the following formula (5):

[0118]

[0119] In formula (5), gMinStepLimit represents the minimum grid step size, and N3 represents the third preset factor.

[0120] It should be noted that for simple metal geometric models that do not have key fine structures, the value of the third preset factor is within 15 to 20. However, for some more complex models that have key fine structures, it is necessary to further increase the third preset factor to reduce the minimum mesh step size (lower limit of global mesh step size).

[0121] In other implementations, the minimum grid step size can also be manually specified by the user.

[0122] Specifically, setting a minimum mesh step size limit can prevent excessive computational and storage pressure. By setting a minimum mesh step size limit, it prevents the computational load and memory requirements from exploding due to excessively fine meshes, while allowing the minimum step size limit to be appropriately relaxed when needed based on fine structures (such as patch details). This allows for control of computational resource consumption while maintaining the resolution of local details.

[0123] Step a2: Determine the encryption step size based on the maximum grid step size and the fourth preset factor.

[0124] The fourth preset factor is less than the third preset factor. The fourth preset factor can be the default value configured in the electromagnetic simulation software, or it can be input by the user into the electromagnetic simulation software. The fourth preset factor can be any value between 2 and 5. For example, the fourth preset factor can be 2, 3, 4 or 5, etc.

[0125] Specifically, after determining the maximum grid step size and the fourth preset factor, the refinement step size can be determined using the following formula (6):

[0126]

[0127] In formula (6), RefinementStep represents the encryption step size, and N4 represents the fourth preset factor.

[0128] Step a3: In response to the user's action, determine the mesh encryption area and the mesh smoothing factor.

[0129] Specifically, the area selected by the user through the display interface can be designated as the grid refinement area, or the grid smoothing factor can be determined based on the user's input. For example, the value range of the grid smoothing factor can be 1.2 to 1.5, such as 1.2, 1.3, or 1.5.

[0130] Specifically, setting a mesh smoothing factor can ensure mesh quality and numerical stability. By limiting the rate of change of adjacent mesh step sizes (SmoothRatio), a smooth transition is ensured when the mesh size changes, avoiding numerical dispersion or pseudomorphisms caused by excessive "step skipping". This approach ensures accurate calculation in the refined region while also taking into account numerical stability and overall mesh quality.

[0131] In other embodiments, the mesh smoothing factor can be pre-configured in the electromagnetic simulation software, and the mesh refinement area can also be determined based on the rules of the pre-configured local mesh refinement range.

[0132] For example, the local mesh encryption range can follow the following rules:

[0133] a. If the metal edge of the metal geometry model is a straight line and parallel to the coordinate axis, then apply RefinementStep as the upper limit of the mesh step size in that region within a certain range around the coordinate points of the coordinate plane through which the metal edge passes (denoted as the local maximum mesh step size).

[0134] For example, if the metal edge is a straight line parallel to the Z-axis, and its coordinate point in the XOY coordinate plane is (x0, y0), then the local maximum mesh step size is limited to RefinementStep within the range [x0-Δx, x0+Δx]; and the local maximum mesh step size is also limited to RefinementStep within the range [y0-Δy, y0+Δy]. Δx represents the preset mesh step size in the x-axis direction, and Δy represents the preset mesh step size in the y-axis direction.

[0135] b. If the metal edge is not parallel to the coordinate axis, then extend the bounding box formed by the metal edge outward by a certain distance and apply RefinementStep as the upper limit of the mesh step size for that region.

[0136] For example, if the bounding box of the metal edge is [x0, y0, z0] to [x1, y1, z1], then the local maximum mesh step size is restricted to RefinementStep within the range of [x0-Δx, x1+Δx]; the local maximum mesh step size is restricted to RefinementStep within the range of [y0-Δy, y1+Δy]; and the local maximum mesh step size is restricted to RefinementStep within the range of [z0-Δz, z1+Δz]. Here, Δz represents the preset mesh step size in the z-axis direction.

[0137] Step S204: Based on multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size, and mesh smoothing factor, generate multiple mesh points to divide the metal geometry model into multiple meshes.

[0138] Specifically, step S204 includes:

[0139] Step S2041: Delete or merge multiple feature points according to the minimum grid step size to obtain updated feature points.

[0140] Specifically, after obtaining multiple feature points, if the feature points in some areas are relatively dense (the distance between two adjacent feature points is less than the minimum grid step size), then the feature points in that area can be deleted or merged using the global minimum grid size constraint to obtain multiple updated feature points.

[0141] Step S2042: Under the constraints of the updated multiple feature points, maximum grid step size, minimum grid step size, grid refinement area, and refinement step size, generate multiple grid points.

[0142] In this model, multiple grid points are located in multiple intervals, each with a different grid step size. Specifically, the metal geometry model can be divided into dense grid regions and sparse grid regions. Dense grid regions include grid-refined regions, with the refinement step size serving as the upper limit for the grid step size in dense grid regions, while sparse grid regions use the maximum grid step size as the upper limit for the grid step size.

[0143] Step S2043: Based on the grid smoothing factor, smooth the grid step size corresponding to different intervals to obtain the smoothed grid step size.

[0144] Specifically, the grid step size at the boundary between dense and sparse grid regions is smoothed by a grid smoothing factor to avoid an excessively large ratio between two adjacent grid step sizes.

[0145] If dense and sparse mesh regions are directly and abruptly cut (e.g., the step size changes abruptly from 0.1 to 1), simulation errors will occur. To avoid this, the mesh step size at the boundary between different regions is smoothed. For example, the mesh step size before smoothing is 0.1 and 1, and the smoothed mesh step size gradually changes from 0.1→0.2→0.3…→1, making the mesh transition more natural.

[0146] Step S2044: Insert new grid points between multiple grid points according to the smoothed grid step size.

[0147] Specifically, new grid points are inserted at the grid points at the boundaries of different intervals according to the smoothed grid step size, resulting in the grid point distribution in the three coordinate axes. Based on the grid point distribution, the metal geometry model can be divided into multiple grids.

[0148] The mesh generation method provided in this embodiment fully combines the geometric features and electromagnetic properties of the electromagnetic simulation model. By extracting information such as geometric feature points and feature lines of the model, and combining it with areas where the electromagnetic field is prone to drastic changes (such as acute angles, metal edges, gaps and holes), it achieves non-uniform mesh generation with local densification at key locations. It can effectively control the computational cost while ensuring simulation accuracy, taking into account the needs of complex geometric features and electromagnetic properties. Furthermore, through a series of smoothing, densification and restriction strategies, it effectively improves the quality and efficiency of mesh generation, and is applicable to a variety of electromagnetic simulation scenarios.

[0149] This embodiment also provides an electromagnetic simulation method that can be used in a computer device equipped with electromagnetic field simulation software based on the FIT algorithm. Figure 3 This is a flowchart illustrating an electromagnetic simulation method according to an embodiment of the present invention, as shown below. Figure 3 As shown, the method includes the following steps:

[0150] Step S301: Extract multiple feature points from the metal geometric model.

[0151] Please see details Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0152] Step S302: Determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model.

[0153] Please see details Figure 1 Step S102 of the illustrated embodiment or Figure 2 Step 202 of the illustrated embodiment will not be repeated here.

[0154] Step S303: Determine the minimum grid step size, grid refinement area, refinement step size, and grid smoothing factor.

[0155] Please see details Figure 1 Step S103 of the illustrated embodiment or Figure 2 Step 203 of the illustrated embodiment will not be described again here.

[0156] Step S304: Generate multiple mesh points based on multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size, and mesh smoothing factor to divide the metal geometry model into multiple meshes.

[0157] Please see details Figure 2 Step S204 of the illustrated embodiment will not be described again here.

[0158] Step S305: Input the meshed metal geometric model into the finite integral method solver for simulation calculation to obtain the electromagnetic field distribution results of the metal parts corresponding to the metal geometric model.

[0159] Specifically, the electromagnetic simulation software includes a FIT solver. After meshing the metal geometric model, the meshed metal geometric model can be input into the FIT solver. The FIT solver solves for the unknowns of the electric and magnetic fields to obtain the electromagnetic field distribution results of the metal parts.

[0160] For example, after determining the electromagnetic field distribution, the results can be visualized (e.g., plotting the distribution of electric and magnetic fields). Visualization allows for an intuitive observation of the electromagnetic field distribution around the metal component, assessing the impact of the metal component on the electromagnetic field, and providing a basis for further design and optimization.

[0161] The electromagnetic simulation method provided in this embodiment uses the mesh generation method provided in the above embodiment to mesh the metal geometric model. Then, the meshed metal geometric model is input into the FIT solver for simulation calculation to obtain the electromagnetic field distribution results of the metal component. This embodiment, by using the mesh generation method provided in the above embodiment, can generate reliable non-uniform FIT mesh lines, thereby effectively improving the computational efficiency and accuracy of the FIT algorithm.

[0162] The electromagnetic simulation method provided by this invention will be described in detail below, taking a metal component as an example of a patch antenna, with reference to the accompanying drawings, to verify the correctness of the mesh partitioning algorithm proposed in this invention.

[0163] Specifically, the geometric model of the patch antenna can be as follows: Figure 4 and Figure 5 As shown, the patch antenna 400 includes a dielectric substrate 410, a radiating patch 420, and an intermediate patch 430. The metal material in the patch antenna is copper, for example. The relative permittivity of the metal material is 4.4, and the relative dielectric constant of the dielectric substrate material is 3.2. The bounding box size of the patch antenna's geometric model is [-2.5mm, -2.5mm, 0] to [2.5mm, 2.5mm, 0]. The frequency range of interest is 20GHz to 45GHz. The boundary condition is set as a perfectly matched layer (PML), and the distance is 1 / 4 of the wavelength corresponding to the center frequency extended outward from the boundary of the patch antenna's geometric model.

[0164] For example, the specific process of the electromagnetic simulation method can be as follows: Figure 6 As shown, in the case of Figure 4 After importing the metal geometry model shown into the electromagnetic simulation software, or creating a model like this in the electromagnetic simulation software... Figure 4 After the metal geometry model is shown, the feature points CriticalNodes[X / Y / Z] of the metal geometry model are first extracted in the three coordinate axes according to the set rules; then the global maximum mesh size limit gMaxStepLimit is calculated according to the minimum wavelength resolution rule and the geometric resolution rule; the global minimum mesh size limit gMinStepLimit is calculated according to the absolute value or the maximum mesh size fraction manually input by the user.

[0165] After obtaining the global minimum mesh size limit gMinStepLimit, the extracted feature points are deleted or merged using the global minimum mesh size limit to obtain merged feature points MergedNodes[X / Y / Z]. Then, based on the metal edge encryption factor Fraction set by the user, the encryption step size RefinementStep = gMaxStepLimit / Fraction of the metal geometry model edge is calculated, and the encryption step size limit is applied around the metal edge according to the rules. Then, considering the local mesh step size limit (encryption step size) added by the user and the metal edge encryption strategy, the step size limit and encryption strategy of the local mesh are applied to the global mesh generation strategy.

[0166] For example, such as Figure 7 As shown, the user adds local mesh settings to the four radiation patches through the parameter input interface 701 of the electromagnetic simulation software, such as... Figure 8 As shown, the user adds local mesh settings to the middle patch through the parameter input interface 701. The specific setting parameters are determined by the user and will not be explained in detail here.

[0167] Then, the step size constraints of different global intervals are smoothed using the grid smoothing factor SmoothRatio. New grid points are inserted between the merged feature points MergedNodes[X / Y / Z] according to the smoothed step size constraints to obtain the final grid point distribution in the three coordinate axes.

[0168] For example, the mesh generation result can be as follows Figure 9 As shown, the number of grids in the X / Y / Z directions are 192 / 109 / 46 respectively, and the grid line distribution is as follows. Figure 10 , Figure 11 and Figure 12 As shown, where, Figure 10 This shows the grid line distribution in the YOZ coordinate plane. Figure 11 This shows the grid line distribution in the XOZ coordinate plane. Figure 12 This shows the grid line distribution in the XOY coordinate plane.

[0169] After obtaining the grid point distribution, the grid line data is transmitted to the FIT solver based on non-uniform grids for simulation calculation. After the solution is completed, the final electromagnetic field distribution result is obtained.

[0170] Specifically, the FIT solver can be used to calculate the scattering parameters (S-parameters) of the patch antenna, and the calculation results are as follows: Figure 13As shown, M3 is the result obtained by dividing the mesh lines using the mesh generation method provided in this invention and then calculating it using the FIT solver. Ref is the result calculated by commercial simulation software whose core algorithm is FIT. The curve trends of the two results are basically consistent, which proves that the mesh generation method of this invention is reliable. Figure 13 The horizontal axis represents frequency in GHz, and the vertical axis represents S-parameters in dB. S-parameters reflect the impedance matching between the antenna and the feeding system (such as feed line and RF front end).

[0171] This embodiment also provides a mesh generation device and an electromagnetic simulation device. The mesh generation device is used to implement the above-described mesh generation method embodiments and preferred embodiments, and the electromagnetic simulation device is used to implement the above-described mesh generation method embodiments and preferred embodiments. Details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0172] This embodiment provides a mesh generation device, such as... Figure 14 As shown, it includes:

[0173] Extraction module 1401 is used to extract multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause the electromagnetic field to produce singular behavior.

[0174] The first determining module 1402 is used to determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model;

[0175] The second determining module 1403 is used to determine the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor. The refinement step size is the grid step size of the grid refinement region. The refinement step size is less than the maximum grid step size and greater than the minimum grid step size. The grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes.

[0176] The mesh generation module 1404 is used to generate multiple mesh points based on multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size and mesh smoothing factor, so as to divide the metal geometry model into multiple meshes.

[0177] In some alternative implementations, the mesh generation module 1404 includes:

[0178] The deletion / merging processing unit is used to delete or merge multiple feature points according to the minimum grid step size to obtain updated feature points.

[0179] The generation unit is used to generate multiple grid points under the constraints of multiple updated feature points, maximum grid step size, minimum grid step size, grid refinement region and refinement step size. The multiple grid points are located in multiple intervals, and the grid step size is different for each interval.

[0180] The smoothing unit is used to smooth the grid step size corresponding to different intervals according to the grid smoothing factor, so as to obtain the smoothed grid step size.

[0181] Insertion cells are used to insert new grid points between multiple grid points according to a smoothed grid step size.

[0182] In some alternative implementations, the first determining module 1402 includes:

[0183] The first determining unit is used to determine the first grid step size based on the shortest wavelength and the first preset factor;

[0184] The second determining unit is used to determine the second mesh step size based on the longest side of the bounding box of the metal geometry model and the second preset factor.

[0185] The third determining unit is used to determine the minimum value between the first grid step size and the second grid step size as the maximum grid step size.

[0186] In some alternative implementations, the second determining module 1403 includes:

[0187] The fourth determining unit is used to determine the minimum grid step size based on the maximum grid step size and the third preset factor;

[0188] The fifth determining unit is used to determine the encryption step size based on the maximum grid step size and the fourth preset factor, where the fourth preset factor is less than the third preset factor.

[0189] The sixth determining unit is used to determine the grid encryption area and grid smoothing factor in response to user operations.

[0190] In some alternative implementations, the grid smoothing factor ranges from 1.2 to 1.5.

[0191] In some optional implementations, the plurality of feature points include at least one of the following: coordinate points in two directions of the coordinate plane traversed by the edge of the metal geometry model parallel to the coordinate axis; coordinate points in the axial direction perpendicular to the coordinate plane of the surface of the metal geometry model parallel to the coordinate plane; coordinates of the center of the arc edge of the metal geometry model parallel to the coordinate plane and coordinate points of its bounding box in two directions of the coordinate plane; coordinates of the bounding box of the sphere model in the metal geometry model and coordinate points of the center of the sphere in three coordinate axis directions; and coordinate points of the cylinder model in the metal geometry model whose height direction is parallel to the coordinate axis and coordinate points of the center point of the cylinder model in three coordinate axis directions.

[0192] This embodiment provides an electromagnetic simulation device, such as... Figure 15 As shown, it includes:

[0193] Extraction module 1401 is used to extract multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause the electromagnetic field to produce singular behavior.

[0194] The first determining module 1402 is used to determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model;

[0195] The second determining module 1403 is used to determine the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor. The refinement step size is the grid step size of the grid refinement region. The refinement step size is less than the maximum grid step size and greater than the minimum grid step size. The grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes.

[0196] Mesh generation module 1404 is used to generate multiple mesh points based on multiple feature points, maximum mesh step size, minimum mesh step size, mesh refinement region, refinement step size and mesh smoothing factor, so as to divide the metal geometry model into multiple meshes;

[0197] The electromagnetic simulation module 1501 is used to input the meshed metal geometric model into the finite integral method solver for simulation calculation, and obtain the electromagnetic field distribution results of the metal parts corresponding to the metal geometric model.

[0198] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0199] In this embodiment, the mesh generation device and the electromagnetic simulation device are presented in the form of functional units. Here, a unit refers to an application-specific integrated circuit (ASIC), a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0200] This invention also provides a computer device, such as... Figure 16 As shown, the computer device includes one or more processors 1610, memory 1620, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processor can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces).

[0201] Processor 1610 may be a central processing unit, a network processor, or a combination thereof. Processor 1610 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0202] The memory 1620 stores instructions executable by at least one processor 1610 to cause the at least one processor 1610 to perform the method shown in the above embodiments.

[0203] The memory 1620 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function; and the data storage area may store data created based on the use of the computer device. Furthermore, the memory 1620 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device.

[0204] The memory 1620 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 1620 may also include combinations of the above types of memory.

[0205] The computer device also includes an input device 1630 and an output device 1640. The processor 1610, memory 1620, input device 1630, and output device 1640 can be connected via a bus or other means. Figure 16 Taking the example of a connection between China and Israel via a bus.

[0206] Input device 1630 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 1640 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0207] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium after being downloaded via a network. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium may also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0208] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0209] In the description of this specification, the references to terms such as "this embodiment," "an embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0210] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0211] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the present invention.

Claims

1. A mesh generation method, characterized in that, The method includes: Multiple feature points are extracted from the metal geometric model, wherein the multiple feature points are used to characterize the key points in the metal geometric model that cause the electromagnetic field to produce singular behavior; The maximum mesh step size is determined based on the shortest wavelength and the longest side of the bounding box of the metal geometry model. Determine the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor, wherein the refinement step size is the grid step size of the grid refinement region, the refinement step size is less than the maximum grid step size and greater than the minimum grid step size, and the grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes; Multiple grid points are generated based on the multiple feature points, the maximum grid step size, the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor to divide the metal geometry model into multiple grids.

2. The method according to claim 1, characterized in that, The process of generating multiple grid points based on the multiple feature points, the maximum grid step size, the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor includes: Based on the minimum grid step size, the multiple feature points are deleted or merged to obtain updated feature points. Under the constraints of the updated multiple feature points, the maximum grid step size, the minimum grid step size, the grid encryption region, and the encryption step size, multiple grid points are generated, wherein the multiple grid points are located in multiple intervals, and the grid step size corresponding to each interval is different; Based on the grid smoothing factor, the grid step size corresponding to different intervals is smoothed to obtain the smoothed grid step size. Insert new grid points between the plurality of grid points according to the smoothed grid step size.

3. The method according to claim 1, characterized in that, Determining the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model includes: The first grid step size is determined based on the shortest wavelength and the first preset factor; The second mesh step size is determined based on the longest side of the bounding box of the metal geometry model and the second preset factor. The minimum value between the first grid step size and the second grid step size is determined as the maximum grid step size.

4. The method according to any one of claims 1 to 3, characterized in that, The determination of the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor includes: The minimum grid step size is determined based on the maximum grid step size and the third preset factor; The encryption step size is determined based on the maximum grid step size and the fourth preset factor, wherein the fourth preset factor is less than the third preset factor; In response to the user's action, the grid encryption region and the grid smoothing factor are determined.

5. The method according to claim 4, characterized in that, The value range of the grid smoothing factor is 1.2 to 1.

5.

6. The method according to any one of claims 1 to 3, characterized in that, The plurality of feature points include at least one of the following: coordinate points in two directions of the coordinate plane traversed by the edge of the metal geometric model parallel to the coordinate axis; coordinate points of the surface of the metal geometric model parallel to the coordinate plane in the direction perpendicular to the coordinate plane; coordinates of the center of the arc edge of the metal geometric model parallel to the coordinate plane and the coordinate points of its bounding box in two directions of the coordinate plane; coordinates of the bounding box of the sphere model in the metal geometric model and the coordinate points of the center of the sphere in three coordinate axes; and coordinate points of the cylinder model whose height direction is parallel to the coordinate axis and the center point of the cylinder model in three coordinate axes.

7. An electromagnetic simulation method, characterized in that, The method includes: Multiple feature points are extracted from the metal geometric model, wherein the multiple feature points are used to characterize the key points in the metal geometric model that can cause the electromagnetic field to produce singular behavior; The maximum mesh step size is determined based on the shortest wavelength and the longest side of the bounding box of the metal geometry model. Determine the minimum grid step size, the grid refinement region, the refinement step size, and the grid smoothing factor, wherein the refinement step size is the grid step size of the grid refinement region, the refinement step size is less than the maximum grid step size and greater than the minimum grid step size, and the grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes; Based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor, multiple mesh points are generated to divide the metal geometry model into multiple meshes; The meshed metal geometric model is input into the finite integral method solver for simulation calculation to obtain the electromagnetic field distribution results of the metal component corresponding to the metal geometric model.

8. A mesh generation device, characterized in that, The device includes: An extraction module is used to extract multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause the electromagnetic field to produce singular behavior. The first determining module is used to determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model; The second determining module is used to determine the minimum grid step size, the grid densification region, the densification step size, and the grid smoothing factor, wherein the densification step size is the grid step size of the grid densification region, the densification step size is less than the maximum grid step size and greater than the minimum grid step size, and the grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes. The meshing module is used to generate multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor, so as to divide the metal geometric model into multiple meshes.

9. An electromagnetic simulation device, characterized in that, The device includes: An extraction module is used to extract multiple feature points from a metal geometric model, wherein the multiple feature points are used to characterize key points in the metal geometric model that can cause the electromagnetic field to produce singular behavior. The first determining module is used to determine the maximum mesh step size based on the shortest wavelength and the longest side of the bounding box of the metal geometry model; The second determining module is used to determine the minimum grid step size, the grid densification region, the densification step size, and the grid smoothing factor, wherein the densification step size is the grid step size of the grid densification region, the densification step size is less than the maximum grid step size and greater than the minimum grid step size, and the grid smoothing factor is used to characterize the rate of change between two adjacent grid step sizes. The meshing module is used to generate multiple mesh points based on the multiple feature points, the maximum mesh step size, the minimum mesh step size, the mesh refinement region, the refinement step size, and the mesh smoothing factor, so as to divide the metal geometric model into multiple meshes; The electromagnetic simulation module is used to input the meshed metal geometric model into the finite integral method solver for simulation calculation, and obtain the electromagnetic field distribution results of the metal parts corresponding to the metal geometric model.

10. A computer device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the mesh generation method of any one of claims 1 to 6, or the electromagnetic simulation method of claim 7.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the mesh generation method of any one of claims 1 to 6, or the electromagnetic simulation method of claim 7.

12. A computer program product, characterized in that, It includes computer instructions for causing a computer to perform the mesh generation method of any one of claims 1 to 6, or to perform the electromagnetic simulation method of claim 7.

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