A modeling method for temperature-varying media based on TDFIT

Abstract

The present invention discloses a temperature-varying medium modeling method based on TDFIT. First, the corresponding antenna cover model is drawn using 3D modeling, and then the rectangular coordinate axis parallel lines and right hexahedron grid covering the calculation domain are established, and the point cloud information obtained by thermal simulation is mapped to the right hexahedron grid of TDFIT electromagnetic simulation. Then the electromagnetic simulation is completed and the accuracy of the distributed material model is verified. The beneficial effects of the present invention are as follows: compared with uniform layered simulation, it can more accurately characterize the medium parameter information that changes with temperature, with a wider range of applications and higher calculation accuracy; the integrated analysis antenna cover can effectively simulate the changes in the electrical properties of the antenna cover at high temperature, avoiding multiple repeated cycles of design and testing during the design process, and can effectively shorten the iteration time and cost of the antenna cover design, with high engineering value.

Description

Technical Field

[0001] The present invention relates to the technical field of electromagnetic physics simulation, and in particular to a temperature-varying medium modeling method based on TDFIT. Background Art

[0002] With the continuous advancement of aerospace technology, various aircraft have achieved breakthrough performance improvements in diverse areas. In aircraft design, the radome, located at the very front of the vehicle, plays a crucial role in protecting the aircraft and its critical electronic components. During high-speed flight, the radome is exposed to high pressure and high temperature. High pressure can cause deformation, while high temperature can alter the material properties of the radome, directly impacting its electrical performance during flight. Therefore, performing mechanical, thermal, and electrical simulation analysis of the radome is crucial.

[0003] In existing technology, simulating the electrical performance of a radome under high pressure is typically performed by inputting the deformation of a geometric model. Simulating the electrical performance of a radome under high temperature requires decomposing it into calculations of the ablation amount, the temperature field, and then layering the radome according to the temperature gradient where the dielectric constant changes significantly. Finally, the layered radome is imported into simulation software and converted into a multi-layer dielectric electrical performance simulation problem. However, this method has certain limitations. In reality, the temperature of a radome does not change layer by layer, and each part of the radome may be affected differently by high temperature. Therefore, the electrical performance results of the radome calculated in layers are inaccurate. Furthermore, existing simulation software rarely provides methods for the integrated mechanical, thermal, and electrical simulation of a radome, which has become a key issue that urgently needs to be addressed in electromagnetic simulation. Summary of the Invention

[0004] The object of the present invention is to provide a temperature-variable medium modeling method based on TDFIT to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a temperature-dependent medium modeling method based on TDFIT, comprising the following steps:

[0006] Step S1: Draw the corresponding radome model using 3D modeling, then export the model and perform electromagnetic simulation based on TDFIT;

[0007] Step S2: Grid generation, establishing parallel lines to the rectangular coordinate axes covering the computational domain, wherein at least three groups of parallel lines to the rectangular coordinate axes are established and are independent of each other, and each group is parallel to the rectangular coordinate plane, and the three orthogonal line groups form a right hexahedron in space;

[0008] Step S3: characterizing the target medium parameters under temperature variation;

[0009] Step S4: Based on step S3, the grid is mapped to a rectangular hexahedron for electromagnetic simulation, and then, according to the intersection between the grid and the target, each rectangular hexahedron is filled with a medium. The medium specifically refers to the material of the target model, that is, the material of the target model is filled into each rectangular hexahedron;

[0010] Step S5: Verify the accuracy of the distributed material model. When the radome is heated, the temperature distribution changes, and the corresponding medium parameters change from uniform distribution to non-uniform distribution. The distributed material model can be degenerated into a layered uniform medium model. In other words, verify whether the distributed material model is equivalent to the layered uniform medium model.

[0011] Furthermore, in step S4, the following steps are also included:

[0012] Step S4.1: After performing thermal simulation on the target medium using Abaqus software, the coordinate information and corresponding temperature information of each node in space are obtained;

[0013] Step S4.2: The actual correspondence between the medium parameters and the temperature can be obtained through actual measurement. Combined with step S4.1, the correspondence between each node information and the medium parameter information can be further obtained.

[0014] Step S4.3: Use the octree method to divide the space. Each leaf node stores the point cloud data in the corresponding area to prepare for the subsequent inverse distance weighted interpolation acceleration.

[0015] Step S4.4: Each small cubic unit obtained by dividing the right hexahedron is called a cell. The center point of the cell is the center, which represents the point to be interpolated. The discrete points near it are searched. The closer the distance to the cell center point, the higher the weight given. Conversely, the farther the distance from the cell center point, the smaller the weight ratio. The weighting function is: Where p is any positive real number, usually 2, i and j represent different discrete points, h i and h j They all represent the distance from the discrete point to the interpolation point, and the expression is: In this expression, (x,y,z) is the interpolation point, (x i ,y i ,z i ) are the coordinates of discrete points;

[0016] Step S4.5: Calculate the distances between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located according to step S4.4;

[0017] Step S4.6: Calculate the weight of each leaf node;

[0018] Step S4.7: Combine steps S4.4 to S4.6 to calculate the medium parameters of the points to be interpolated, and realize the medium mapping of the point cloud to the hexahedral grid.

[0019] Furthermore, in step S3, the medium parameters are specifically dielectric constant and loss tangent value.

[0020] Furthermore, the implementation of the inverse distance weighted interpolation method is mainly divided into three steps:

[0021] Step 1: Calculate the distance between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located;

[0022] Step 2: Calculate the weight of each point. The weight is a function of the inverse of the distance. That is, take p as a positive real number 2, and then substitute it into the weighting function to get:

[0023] Step 3: Calculate the medium parameters of the interpolation point. The calculation formula is as follows:

[0024] Furthermore, when interpolating the point to be interpolated, the leaf node where the point to be interpolated is located can be located, and all points far away from the point to be interpolated can be excluded. In this way, the number of discrete points required for discrete interpolation will be reduced, thereby shortening the calculation time. The leaf node is the smallest unit in the cell, and the medium parameter expression of the point to be interpolated is:

[0025] Furthermore, in step S5, if the calculation results of the degradation model of the inhomogeneous medium model are similar to those of the layered medium model and differ greatly from those of the uniform medium model, it indicates that the degradation model can be equivalent to the layered medium model; if the calculation results of the degradation model or the layered medium model gradually approach a certain curve as the number of layers gradually increases, it indicates that when the number of layers is infinitely divided, the calculation results are infinitely close to the calculation results of the inhomogeneous medium model, thereby demonstrating the correctness of the inhomogeneous medium model.

[0026] Compared with the existing technology, the beneficial effects of the present invention are: through the TDFIT-based temperature-dependent medium modeling method, the influence of temperature change on the antenna cover is mapped into the change of the medium parameters of each node in space, and the material mapping is performed from the point cloud to the hexahedral grid, thereby achieving the purpose of integrated force, heat and electricity analysis of the antenna cover; this method can more accurately characterize the medium parameter information that changes with temperature, has a wider range of applications and higher calculation accuracy; the integrated analysis of the antenna cover can effectively simulate the changes in the electrical performance of the aircraft during high-speed flight, avoid multiple repeated cycles of design and testing in the design process, can effectively shorten the iteration time and cost of the antenna cover design, and has high engineering value. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A flowchart of material mapping of a point cloud to a hexahedral mesh according to the present invention;

[0029] Figure 2 This is part of the file output of the thermal simulation temperature information of the abaqus software of the present invention;

[0030] Figure 3 The corresponding relationship between the dielectric constant and temperature of a certain material of the present invention;

[0031] Figure 4 The corresponding relationship between the loss tangent and temperature of a certain material of the present invention;

[0032] Figure 5 Schematic diagram of the octree structure of the present invention;

[0033] Figure 6 is the distributed material degradation model of the present invention;

[0034] Figure 7 This is a comparison diagram of the RCS results of the three models of the present invention when Phi=0 in space;

[0035] Figure 8 This is a comparison diagram of the RCS results of the three models of the present invention when Phi=90 in space;

[0036] Figure 9 Schematic diagram of the non-uniform gradient medium model of the present invention;

[0037] Figure 10 This is a comparison diagram of RCS results of different layered models on the ZOX plane of the present invention;

[0038] Figure 11 The far-field gain curves of the antenna of the present invention at room temperature and high temperature are shown. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0040] See also Figure 1-11 In an embodiment of the present invention, a temperature-varying medium modeling method based on TDFIT includes the following steps:

[0041] Step S1: Draw the corresponding radome model using 3D modeling, then export the model and perform electromagnetic simulation based on TDFIT;

[0042] Step S2: Grid generation, establishing parallel lines to the rectangular coordinate axes covering the computational domain, wherein at least three groups of parallel lines to the rectangular coordinate axes are established and are independent of each other, and each group is parallel to the rectangular coordinate plane, and the three orthogonal line groups form a right hexahedron in space;

[0043] Step S3: characterizing the target medium parameters under temperature variation;

[0044] Step S4: Based on step S3, the grid is mapped to a rectangular hexahedron for electromagnetic simulation, and then, according to the intersection between the grid and the target, each rectangular hexahedron is filled with a medium. The medium specifically refers to the material of the target model, that is, the material of the target model is filled into each rectangular hexahedron;

[0045] Step S5: Verify the accuracy of the distributed material model. When the radome is heated, the temperature distribution changes, and the corresponding medium parameters change from uniform distribution to non-uniform distribution. The distributed material model can be degenerated into a layered uniform medium model. In other words, verify whether the distributed material model is equivalent to the layered uniform medium model.

[0046] In step S4, the following steps are also included:

[0047] Step S4.1: After performing thermal simulation on the target medium using Abaqus software, the coordinate information and corresponding temperature information of each node in space are obtained;

[0048] Step S4.2: The actual correspondence between the medium parameters and the temperature can be obtained through actual measurement. Combined with step S4.1, the correspondence between each node information and the medium parameter information can be further obtained. The output file is as follows: Figure 2 As shown;

[0049] Step S4.3: Use the octree method to divide the space. Each leaf node stores the point cloud data in the corresponding area to prepare for the subsequent inverse distance weighted interpolation acceleration.

[0050] Step S4.4: Each small cubic unit obtained by dividing the right hexahedron is called a cell. The center point of the cell is the center, which represents the point to be interpolated. The discrete points near it are searched. The closer the distance to the cell center point, the higher the weight given. Conversely, the farther the distance from the cell center point, the smaller the weight ratio. The weighting function is: Where p is any positive real number, usually 2, i and j represent different discrete points, h i and h j They all represent the distance from the discrete point to the interpolation point, and the expression is: In this expression, (x,y,z) is the interpolation point, (x i ,y i ,z i ) are the coordinates of discrete points;

[0051] Step S4.5: Calculate the distances between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located according to step S4.4;

[0052] Step S4.6: Calculate the weight of each leaf node;

[0053] Step S4.7: Combine steps S4.4 to S4.6 to calculate the medium parameters of the points to be interpolated, and realize the medium mapping of the point cloud to the hexahedral grid.

[0054] The specific implementation steps of the inverse distance weighted interpolation method can be divided into the following three steps:

[0055] Step 1: Calculate the distance between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located;

[0056] Step 2: Calculate the weight of each point. The weight is a function of the inverse of the distance. That is, take p as a positive real number 2, and then substitute it into the weighting function to get:

[0057] Step 3: Calculate the medium parameters of the interpolation point. The calculation formula is as follows:

[0058] In this way, the point cloud can be mapped to a hexahedral medium, thereby realizing the electromagnetic simulation of temperature-dependent media.

[0059] Example 1:

[0060] The specific implementation steps of the temperature-variable medium modeling method are as follows:

[0061] D1: After performing thermal simulation on the target using Abaqus software, all nodes and their corresponding temperature information are output;

[0062] D1.1: Import the stp radome model;

[0063] D1.2: Set material properties according to work requirements. If the material parameters are temperature-related, check "Use temperature-related data";

[0064] D1.3: Enter the analysis step interface, create an analysis step, modify the analysis step name, and create a heat transfer analysis step;

[0065] D1.4: Enter the load interface, create a surface heat flux load, select the surface to which the load is to be added, select OK, modify the load surface heat flux size, and select the amplitude;

[0066] D1.5: Add boundary conditions. You can add temperature boundaries and mechanical boundaries. When the bottom is fixed, apply a completely fixed mechanical boundary.

[0067] D1.6: Double-click the predefined field, select all solid parts, and apply the initial temperature;

[0068] D1.7: Enter the meshing interface, assign control properties to the mesh, specify the type of mesh element, modify the global seed size, and mesh the component.

[0069] D1.8: Enter the job interface, create a job, enter the job manager, and submit the job;

[0070] D1.9: Field output, output all nodes of the target and the temperature information corresponding to the nodes;

[0071] D2: Since temperature and medium parameters have a one-to-one correspondence, the specific values need to be measured, thereby further obtaining the corresponding information between the node coordinate information and the medium parameters;

[0072] D3: Divide the target into a hexahedron based on the TDFIT algorithm, and map the point cloud data obtained through thermoelectric simulation into the hexahedron;

[0073] D3.1: Each small cubic unit obtained by dividing a right hexahedron is called a cell;

[0074] D3.2: Using the cell center as the cell, directly search for data on points near the cell, and use local interpolation to accurately determine the medium parameter information at the interpolation point.

[0075] The space is divided into two parts by using an octree, and each leaf node stores the point cloud data in the corresponding area.

[0076] Each small cubic unit obtained by dividing the right hexahedron is called a cell. Taking the center point or vertex of the cell as the center, some discrete points near it are searched. The closer the point is to the center point or vertex of the cell, the higher the weight ratio is given to it, and the farther the point is from the center point or vertex of the cell, the smaller the weight ratio is.

[0077] (1) Calculate the distance between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located;

[0078] (2) Calculate the weight of each point: the weight is a function of the inverse of the distance;

[0079] (3) Calculate the medium parameters of the points to be interpolated.

[0080] D4: Analyze the wave transmission performance of the radome under temperature changes based on the target model using FASTEM software.

[0081] D4.1: Import the target model and all node and medium parameter information (point cloud) output from D1.9 into the FASTEM software;

[0082] D4.2: Input frequency and temperature variation range;

[0083] D4.3: Set the excitation method, solution algorithm, and observation parameters;

[0084] D4.4: Submit the calculation to obtain the far-field gain results of the radome under temperature variation. Compare the temperature variation results with the results at normal temperature. Figure 11 shown.

[0085] Example 2:

[0086] Mapping the medium corresponding to the point cloud to the hexahedron mainly includes two parts:

[0087] Point cloud data partitioning and local interpolation calculation in space: The space is divided into octrees. Each leaf node stores the point cloud data in the corresponding area, preparing for subsequent inverse distance weighted interpolation acceleration.

[0088] Inverse distance weighted interpolation: With the center point or vertex of the cell as the center, search for some discrete points near it. The closer the point is to the cell center point or cell vertex, the higher the weight ratio is given to it, and the farther the point is from the cell center point or cell vertex, the smaller the weight ratio is.

[0089] The specific weighting function is: Where p is any positive real number, usually 2, i and j represent different discrete points, h i and h j They all represent the distance from the discrete point to the interpolation point, and the expression is: In this expression, (x,y,z) is the interpolation point, (x i ,y i ,z i ) are the coordinates of discrete points.

[0090] like Figure 6As shown in Figure 2, in the extreme case, when the distributed material model is divided into countless blocks, the degradation model approximates a material with a uniform dielectric constant gradient along a certain direction. Therefore, it is crucial to determine whether the layered uniform medium model is equivalent to the degradation model of the distributed material model.

[0091] for Figure 6 The equivalence of is verified from two perspectives:

[0092] 1. If the calculation results of the degradation model of the inhomogeneous medium model are similar to those of the stratified medium model and are significantly different from those of the homogeneous medium model, it means that the degradation model can be equivalent to the stratified medium model.

[0093] Taking a radome model of any material as an example, the results of the non-uniform gradient medium model (degenerate model), the three-layer uniform medium model and the uniform medium model are calculated and compared. The results are as follows: Figure 7-8 shown.

[0094] like Figure 7-8 As shown in the figure, it can be seen that the results of the non-uniform gradient medium model and the three-layer uniform medium model are basically consistent, and the calculation results of the uniform medium model are quite different from the former two, indicating that the degradation model can be equivalent to the layered medium model.

[0095] Second: If the calculation results of the degenerate model or the layered medium model gradually approach a certain curve as the number of layers increases, it means that when the number of layers is infinitely divided, the calculation results are infinitely close to the calculation results of the inhomogeneous medium model, which further proves the correctness of the inhomogeneous model.

[0096] like Figure 9 As shown, a 0.01m*0.03m*0.03m rectangular parallelepiped is used as the non-uniform medium gradient model. The non-uniform medium model has a relative dielectric constant that changes from 2 to 10 from left to right. The model is evenly divided into 3 layers, 6 layers, and 20 layers respectively. The simulation results are shown in Figure 10 shown.

[0097] from Figure 10 It can be seen that as the number of divided layers gradually increases, the curve is gradually approaching the result of the inhomogeneous medium model, indicating that infinite division of the model can make the result infinitely close to the accuracy, proving the correctness of the distributed material simulation method.

[0098] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0099] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A temperature-variable medium modeling method based on TDFIT, characterized in that: The following steps are involved: Step S1: Draw the corresponding radome model using 3D modeling, then export the model and perform electromagnetic simulation based on TDFIT; Step S2: Grid generation, establishing parallel lines to the rectangular coordinate axes covering the computational domain, wherein at least three groups of parallel lines to the rectangular coordinate axes are established and are independent of each other, and each group is parallel to the rectangular coordinate plane, and the three orthogonal line groups form a right hexahedron in space; Step S3: characterizing the target medium parameters under temperature variation; Step S4: Based on step S3, the grid is mapped to a rectangular hexahedron for electromagnetic simulation, and then, according to the intersection between the grid and the target, each rectangular hexahedron is filled with a medium. The medium specifically refers to the material of the target model, that is, the material of the target model is filled into each rectangular hexahedron; Step S5: Verify the accuracy of the distributed material model. When the radome is heated, the temperature distribution changes, and the corresponding medium parameters change from uniform distribution to non-uniform distribution. The distributed material model can be degenerated into a layered uniform medium model. In other words, verify whether the distributed material model is equivalent to the layered uniform medium model. In step S4, the following steps are also included: Step S4.1: After performing thermal simulation on the target medium using Abaqus software, the coordinate information and corresponding temperature information of each node in space are obtained; Step S4.2: The actual correspondence between the medium parameters and the temperature can be obtained through actual measurement. Combined with step S4.1, the correspondence between each node information and the medium parameter information can be further obtained. Step S4.3: Use the octree method to divide the space. Each leaf node stores the point cloud data in the corresponding area to prepare for the subsequent inverse distance weighted interpolation acceleration. Step S4.4: Each small cubic unit obtained by dividing the right hexahedron is called a cell. The center point of the cell is the center, which represents the point to be interpolated. The discrete points near it are searched. The closer the distance to the cell center point, the higher the weight given. Conversely, the farther the distance from the cell center point, the smaller the weight ratio. The weighting function is: Where p is any positive real number, which is 2, i and j represent different discrete points, h i and h j They all represent the distance from the discrete point to the interpolation point, and the expression is: In this expression, (x, y, z) is the interpolation point, (x i ,y i , z i ) are the coordinates of discrete points; Step S4.5: Calculate the distances between the point to be interpolated and all discrete points carried by the leaf node where the point to be interpolated is located according to step S4.4; Step S4.6: Calculate the weight of each leaf node; Step S4.7: Calculate the medium parameters of the interpolation point by combining steps S4.4 to S4.6, and implement medium mapping from the point cloud to the hexahedral grid; When interpolating the point to be interpolated, locate the leaf node where the point to be interpolated is located. The leaf node is the smallest unit in the cell, and all points far away from the point to be interpolated are excluded. In this way, the number of discrete points required for discrete interpolation will be reduced, thereby shortening the calculation time. The medium parameter expression of the point to be interpolated is:

2. The TDFIT-based temperature-variable medium modeling method according to claim 1, characterized in that: In step S3, the medium parameters are specifically dielectric constant and loss tangent value.

3. The TDFIT-based temperature-variable medium modeling method according to claim 1, characterized in that: In step S5, if the calculation results of the degradation model of the inhomogeneous medium model are similar to those of the layered medium model and differ greatly from those of the uniform medium model, it indicates that the degradation model can be equivalent to the layered medium model. If the calculation results of the degradation model or the layered medium model gradually approach a certain curve as the number of layers gradually increases, it indicates that when the number of layers is infinitely divided, the calculation results are infinitely close to the calculation results of the inhomogeneous medium model, thereby demonstrating the correctness of the inhomogeneous model.

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