Electromagnetic calculation method and system for hypersonic aircraft

Abstract

The present application relates to the field of high-speed aircraft electromagnetic characteristic calculation, and relates to a high-speed aircraft electromagnetic calculation method and system. Through the design of an intelligent agent system, the flow field calculation of a high-speed aircraft is intelligently classified, and the output key physical quantities are collected, reconstructed, backed up and high-fidelity line extracted, solving the problems of complicated data integration and low calculation accuracy in current high-speed aircraft electromagnetic calculation, and providing support for subsequent ground analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of hypersonic vehicle electromagnetic characteristic calculation, in particular to a hypersonic vehicle electromagnetic calculation method and system. BACKGROUND

[0002] In order to study the electromagnetic characteristics of the vehicle under extreme conditions at high speed, researchers at home and abroad generally rely on computational fluid dynamics (CFD) and computational electromagnetics (CEA) methods for numerical research. On the one hand, with the popularization of commercial software such as ANSYS and FASTRAN, numerical simulation has become cheap and fast. On the other hand, numerical simulation can make up for the configuration conditions that are difficult to achieve in wind tunnel tests and reveal complex mechanisms. However, there are still some limitations in the current calculation: for example, hypersonic targets involve multi-physical field coupling, which requires the use of computational fluid dynamics methods and computational electromagnetics methods, accompanied by data input compatibility problems, making information integration and analysis very tedious. At the same time, due to the uneven distribution of the plasma sheath on the surface of the vehicle, the traditional WKB method calculates the electromagnetic characteristics of the target by approximating the surface sheath as a metal layer with different dielectric constants, and the calculation accuracy is often determined by the surface layering strategy. Simplified surface layering will lead to a decrease in calculation accuracy. In addition, the flow field calculation needs to solve different N-S equations according to different flight speeds, which is deeply dependent on artificial experience.

[0003] Although with the improvement of computer supercomputing level, difficult engineering problems and complex scientific research are largely dependent on computer numerical simulation. However, at the present stage, there are still the following problems:

[0004] (1) Information integration is tedious. At the present stage, the calculation of the flow field environment of the hypersonic target widely relies on commercial software such as ANSYS and FASTRAN, while the electromagnetic calculation widely uses commercial software such as foke. Due to the need for interdisciplinary integration and multi-physical field coupling, researchers often calculate the flow field environment using fluid dynamics methods, and perform electromagnetic calculation according to the environmental parameters. Due to the interaction between disciplines, problems such as data compatibility (such as mesh partitioning, information import, etc.) often occur, and the current information integration is tedious.

[0005] (2) Dependence on artificial experience. The flow field environment calculation needs to select the flow field control equation according to different flight altitudes, speeds, atmospheric conditions and other limiting factors, and its intelligent degree is low, and it depends on artificial experience for selection and debugging.

[0006] (3) The calculation accuracy is not high. In the traditional electromagnetic calculation, the surface plasma sheath of the aircraft is processed in layers, and each layer of space is approximated as a stack of metal scattering layers with different dielectric constants. The layer-by-layer approximation destroys the continuity of the plasma physical parameters (such as electron density) in space, simplifying it to a discrete step function, which cannot accurately describe the gradient changes of physical quantities in key areas such as shock waves and boundary layers. Due to the existence of this principle error in the traditional "layer-by-layer approximation", the subsequent calculation accuracy is reduced.

[0007] The prior art needs to be improved in view of the above problems. SUMMARY

[0008] The purpose of the present application is to provide a high-speed flight electromagnetic calculation method and system with high calculation accuracy, good information integration analysis, and high intelligence. By intelligently classifying the high-speed flight vehicle flow field calculation and collecting, calculating, backing up and extracting the output key physical quantities, the problems of complicated data integration and low calculation accuracy in current high-speed flight vehicle electromagnetic calculation are solved, and support is provided for subsequent ground analysis.

[0009] In a first aspect, the present application provides a high-speed flight vehicle electromagnetic calculation method, and the technical solution is as follows:

[0010] Select an N-S control equation from a pre-prepared rule library according to user input parameters; the user input parameters include atmospheric environment parameters, flight height, and flight speed;

[0011] Calculate flow field data based on the N-S control equation and collect the flow field data; the flow field data includes physical quantities and chemical quantities;

[0012] Reconstruct the flow field data into electromagnetic parameters required for electromagnetic calculation to generate a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant, and electrical conductivity;

[0013] Determine the feature line of the aircraft surface, extract electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generate one-dimensional spatial sequence data distributed along the feature line;

[0014] Perform electromagnetic environment calculation according to the one-dimensional spatial sequence data; the electromagnetic environment calculation includes scattering characteristic calculation and transmission characteristic calculation.

[0015] Further, the calculation of flow field data based on the N-S control equation includes physical quantity calculation and chemical quantity calculation;

[0016] The physical quantity calculation includes: using the finite element method to discretely solve the N-S control equation on the spatial grid, calculating the flow field temperature and pressure;

[0017] In three-dimensional Cartesian coordinates, the N-S control equation is expressed as:

[0018]

[0019] Where Q is the conservative quantity, E, F, G are diffusion terms in x, y, z directions, E V , F V , G V are the convection terms in three directions, and S is the source vector.

[0020] Further, the chemical quantity calculation includes: if the user input parameters meet the chemical reaction conditions, the chemical reaction transport equation and the reaction kinetics equation in the Park reaction model or the Gupta reaction model are solved according to the actual situation of the environment, and the chemical variables are calculated; the chemical variables include electron density and reaction rate. In this example, the chemical calculation depends on existing chemical reaction models such as the park model and the Gupta model, and the calculation equation contains reactions of dozens of air components.

[0021] Further, the reconstruction of the flow field data into electromagnetic parameters required for electromagnetic calculation to generate a reconstructed electromagnetic parameter set includes:

[0022] Plasma frequency: ;

[0023] Where n e is the electron density, e is the electron charge, m e is the electron mass, and ε0 is the dielectric constant.

[0024] The collision frequency of electrons and neutral particles is calculated using the empirical formula based on gas density-temperature: Where is the collision frequency, is the total number of particles, and T is the temperature.

[0025] The Drude model based on the plasma with collision is used to calculate the relative dielectric constant: And the relative conductivity is calculated using ; Where is the dielectric constant in vacuum, is the relative dielectric constant, and are the real and imaginary parts of the relative dielectric constant, is the incident wave frequency, is the collision frequency, is the relative conductivity and are the real and imaginary parts of the relative conductivity; i is the imaginary part in the complex function, for a relative permittivity, for a permittivity in vacuum.

[0026] generate a reconstructed electromagnetic parameter set according to the plasma frequency, collision frequency, permittivity, conductivity, and store in a log library.

[0027] Further, the determination of the aircraft surface feature line, extraction of electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generation of one-dimensional spatial sequence data distributed along the feature line, comprises:

[0028] Determination of at least one feature line of the aircraft surface, and generation of a corresponding feature line point set; association and positioning of feature points in the feature line point set with grid vertices of the aircraft surface;

[0029] Based on the physical quantities at the associated grid vertices, the physical quantity values of each point on the aircraft surface feature line are obtained by interpolation calculation;

[0030] Generation of one-dimensional data sequence of continuous change of physical quantity values distributed along the aircraft surface feature line.

[0031] Further, the determination of at least one feature line of the aircraft surface comprises: based on the geometric features of the aircraft, at least one of the continuous curves on the symmetry plane from the nose cone vertex to the tail end, the head stagnation point line, and the wing edge line is extracted;

[0032] The association and positioning of feature points in the feature line point set with grid vertices of the aircraft surface comprises: from the feature point, a ray is emitted along the approximate normal direction of the grid element where it is located, and the intersection of the ray with the aircraft surface grid is calculated to determine the nearest surface grid vertex.

[0033] Further, the scattering characteristic calculation comprises:

[0034] When electromagnetic waves irradiate the target, the target surface scattering electric field is obtained by physical optics (PO) method E s :

[0035]

[0036] In the formula, K is the incident wave beam, r is the position vector of the field point, r^ is the scattering unit vector, n^ is the outer unit normal vector of the facet, Z0 is the wave impedance in free space, r' is the position vector of the source point, E and H are the total electric field and magnetic field on the boundary respectively.

[0037] Further, the transmission characteristic calculation comprises:

[0038] The WKB method is used to calculate the propagation characteristics of electromagnetic waves in a plasma sheath; the transmission characteristics include signal attenuation, transmission coefficient, and reflection coefficient.

[0039] In a second aspect, the application further provides a smart agent-based hypersonic vehicle electromagnetic calculation system, comprising a smart agent subsystem, a calculation subsystem, and a post-processing subsystem; the smart agent subsystem comprises a smart classification module, a pre-prepared strategy library, a data collection module, a data integration module, a log library, and a data extraction module; the calculation subsystem comprises a flow field calculation module and an electromagnetic calculation module; the post-processing subsystem comprises a data receiving module and a visualization processing module; wherein:

[0040] The smart classification module is configured to automatically identify, evaluate, and classify user input parameters, and select N-S control equations based on the pre-prepared strategy library; the user input parameters include atmospheric environment parameters, flight altitude, and flight speed.

[0041] The pre-prepared strategy library is configured to store a rule set for the smart classification module to call;

[0042] The flow field calculation module is configured to perform computational fluid dynamics simulation based on the selection result of the smart classification module to obtain flow field data; the flow field data includes physical quantities and chemical quantities.

[0043] The data integration module is configured to reconstruct the flow field data into electromagnetic parameters required for electromagnetic calculation to generate a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant, and electrical conductivity.

[0044] The data extraction module is configured to determine a feature line of a vehicle surface, extract electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generate one-dimensional spatial sequence data distributed along the feature line.

[0045] The electromagnetic calculation module is configured to perform electromagnetic environment calculation according to the one-dimensional spatial sequence data; the electromagnetic environment calculation includes scattering characteristic calculation and transmission characteristic calculation.

[0046] The visualization processing module is configured to visualize the electromagnetic environment calculation result.

[0047] Further, the system is deployed on a hardware platform comprising a high-performance computing server, a large-capacity storage device, and a high-speed internal bus; the modules interact with each other through the high-speed internal bus.

[0048] The data collection module is configured to capture and convert flow field calculation results; the log library is configured to store, back up, and manage all intermediate and final data; and the data receiving module is configured to receive and back up electromagnetic calculation results.

[0049] Compared with the prior art, the hypersonic vehicle electromagnetic calculation method and system provided by the application has the following remarkable beneficial effects:

[0050] 1. The precision and physical fidelity of electromagnetic calculation are improved: the core innovation of the application is to adopt a "data line extraction" technology, which directly extracts a one-dimensional continuous electromagnetic parameter sequence from the integrated and reconstructed three-dimensional data set along the aircraft surface contour line or feature line through linear interpolation sampling. This method completely discards the simplified model in the traditional WKB method, which approximates the plasma sheath as a finite number of discrete dielectric constant layers. By completely preserving the spatial gradient information and continuity of physical parameters (such as electron density and plasma frequency) along the surface, the model error introduced by layering and roughness is fundamentally avoided. Compared with the traditional layering strategy, the application can obtain more accurate electromagnetic scattering and transmission characteristic calculation results under the same grid density, especially can more realistically reflect the electromagnetic effects of key areas such as shock waves and boundary layers.

[0051] 2. Efficient and automatic integration of cross-disciplinary data is realized, and manual intervention and integration complexity are reduced. The application builds a fully automated data processing pipeline through an "intelligent classification module", a "data integration module", and a "log library". The intelligent classification module automatically identifies input parameters and selects control equations; the data integration module automatically reconstructs the flow field data into the input parameters required for electromagnetic calculation through built-in physical algorithms (such as electron density and plasma frequency calculation formulas), and stores them in association. This scheme solves the information integration problem caused by the incompatibility of data format and grid system between CFD and CEM two disciplines. The system realizes full-link automation from flow field calculation to electromagnetic parameter generation, and researchers do not need to manually perform tedious data format conversion, transmission and preprocessing work, greatly improving work efficiency and reducing the risk of errors caused by human operation errors, making it possible for rapid and multi-condition numerical analysis.

[0052] 3. The algorithm usage threshold and dependence on specific artificial experience are reduced, and the intelligent level is improved. The intelligent agent subsystem (especially the intelligent classification module) of the application integrates a "pre-made strategy library" formed by domain expert knowledge, which can automatically and intelligently select the most suitable N-S control equation and chemical reaction model according to the input flight conditions. This design enables researchers without deep fluid mechanics background to quickly and accurately start complex multi-physical field simulation calculation.

[0053] 4、The application constructs a complete, efficient and traceable simulation analysis ecosystem. The technical scheme of the application is a complete system integrating intelligent classification, flow field calculation, data integration, line extraction, electromagnetic calculation and visualization. The "log library" designed in the system records all intermediate data and process logs from the initial decision to the final result. The ecosystem ensures high reproducibility and traceability of the calculation process. The results of any calculation can be completely traced back, facilitating error analysis, scheme optimization and knowledge accumulation. At the same time, the modules are connected through a high-speed bus and accelerated by hardware such as GPU, maintaining the overall calculation efficiency while ensuring high precision, which can meet the demand for large-scale and high-precision simulation in engineering practice. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0055] Figure 1 is a flowchart of the steps of the hypersonic vehicle electromagnetic calculation method disclosed by the embodiments of the application;

[0056] Figure 2 is a structural diagram of the hypersonic vehicle electromagnetic calculation system based on intelligent agents disclosed by the embodiments of the application;

[0057] Figure 3 is an operation flowchart of the hypersonic vehicle electromagnetic calculation system based on intelligent agents disclosed by the embodiments of the application. DETAILED DESCRIPTION

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments belong; the terminology used in the specification of the application is only for the purpose of describing specific embodiments and is not intended to limit the embodiments; the specification of the embodiments and the above description of the drawings are intended to cover non-exclusive inclusion. The terms "include" and "have" in the specification of the embodiments and the above description of the drawings, and any variations thereof, are intended to cover non-exclusive inclusion. The terms "first", "second" and the like in the specification of the embodiments and the above description of the drawings are used to distinguish different objects, not to describe a specific order.

[0059] The implementation details of the technical solutions of the embodiments will be described in detail as follows:

[0060] The application proposes a hypersonic vehicle electromagnetic calculation method, as shown in Figure 1 the method comprises:

[0061] S101, select an N-S control equation from a pre-prepared rule library according to user input parameters; the user input parameters include atmospheric environment parameters, flight height, and flight speed.

[0062] Specifically, according to the user input parameters, the embodiment needs to realize the automatic identification and classification of the input parameters. Among them, the intelligent classification is the preprocessing step of the embodiment, which is executed by the intelligent agent system to realize the automatic identification and classification of the input parameters and reduce manual intervention. Specifically, it includes the following sub-steps:

[0063] (1) Format classification

[0064] After the intelligent agent receives the user input model parameters, it first judges the format by file header analysis, extension recognition, and content feature detection, determines whether the input model is three-dimensional or two-dimensional, and selects the appropriate calculation format.

[0065] (2) Input parameter evaluation

[0066] The intelligent agent evaluates the parsed parameter content, including atmospheric environment parameters, flight height, flight speed, chemical reaction model, etc. The evaluation process checks the integrity and reasonableness of the parameters. For example, through atmospheric environment parameter evaluation, it is determined whether the fluid is compressible, through flight speed evaluation, it is determined whether there is an ion sheath, and through chemical reaction model evaluation, it is determined whether the fluid is a thermo-chemical non-equilibrium flow.

[0067] (3) Control equation selection

[0068] Based on the evaluation results, the intelligent agent will intelligently select the appropriate N-S equation from the pre-prepared rule library, and the selection process will consider the flow state, thermodynamic process, realize adaptive matching of equation type, and improve the calculation efficiency and accuracy. For example, for a vehicle flying at an altitude of 61 km and a speed of 23 Mach, the intelligent agent will select a three-dimensional compressible N-S control equation, a 7-component chemical reaction model, and a viscous solid wall to solve the flow field environment.

[0069] S102, calculate flow field data based on the N-S control equation and collect the flow field data; the flow field data includes physical quantities and chemical quantities;

[0070] Further, the calculation of flow field data based on the N-S control equation includes physical quantity calculation and chemical quantity calculation; wherein the physical quantity calculation includes: using the finite element method to discretely solve the N-S control equation on the spatial grid, calculating the flow field temperature and pressure.

[0071] Further, the chemical quantity calculation includes: if the user input parameters satisfy the chemical reaction conditions, solving the chemical reaction transport equation and reaction kinetics equation to calculate the chemical variable; the chemical variable includes electron density and reaction rate.

[0072] Specifically, in the embodiment, the flow field environment calculation is a precondition for electromagnetic calculation, and is performed by a flow field calculation module, mainly by solving the N-S equation selected by the intelligent agent to obtain flow field data. The specific sub-steps are as follows:

[0073] (1) Physical process calculation (physical quantity calculation)

[0074] The flow field calculation module uses the finite element method to discretely solve the N-S equation on the spatial grid to calculate the flow field temperature, pressure and other physical quantities. In three-dimensional Cartesian coordinates, the three-dimensional conservative form of compressible N-S equation can be expressed as:

[0075]

[0076] Where Q is the conservative quantity, E, F, G are the diffusion terms in x, y, z directions, E V , F V , G V are the convection terms in three directions, and S is the source vector. Its expression is as follows:

[0077]

[0078] In the above formula, u, v, w are the velocities in x, y, z directions, p, ρ, ρ S are the pressure, density and density of component s of the gas; ρ s is the fluid density, is the turbulent energy density; , , are the x, y, z directions in the momentum density; is the total energy density; is the x-direction species mass flux; is the x-direction turbulent energy flux; is the x-direction energy flux; , , are the x, y, z directions of the momentum flux in the X direction; is the x-direction total enthalpy flux.

[0079] During the calculation process, the calculation module iteratively solves according to the boundary conditions until the physical quantities converge, which reveals the flow characteristics of the aircraft surface, such as shock wave position and boundary layer distribution, providing a qualitative distribution reference for subsequent electromagnetic calculation.

[0080] (1) Chemical process calculation (Chemical quantity calculation)

[0081] According to the flight height and speed, if the input parameters meet the chemical reaction, the flow field calculation module additionally solves the chemical reaction transport equation and reaction kinetics equation to calculate the chemical variables such as electron density and reaction rate. The module is compatible with multiple chemical reaction models, such as Gupta_7 / 11, Park97, Dunn Kang, and other chemical reaction models.

[0082] During the calculation process, the calculation module iteratively solves according to the chemical reaction conditions until the chemical variables converge. This step reveals the chemical reaction characteristics of the surface of the vehicle, such as the concentration distribution of the substance, providing quantitative reference for subsequent electromagnetic calculation.

[0083] S103, reconstructing the flow field data into electromagnetic parameters required for electromagnetic calculation to generate a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant, and electrical conductivity.

[0084] Before S103, the method further includes a flow field data collection step. The flow field data collection step is performed by a data collection module to achieve comprehensive collection and storage of flow field calculation results. Specifically, it includes the following sub-steps:

[0085] (1) Data collection: the module connects with the CFD solver through an interface to read the flow field output data, including grid node temperature, pressure, velocity, etc.

[0086] (2) Format conversion: in order to be compatible with the format requirements of various post-processing software, the module has a built-in format conversion program that can convert the data format to the required format, such as ASCII, CGNS, Binary, etc., according to user requirements.

[0087] Further, S103 is the data integration and reconstruction step of the present embodiment. The data integration and reconstruction step converts the flow field data into input parameters required for electromagnetic calculation, solving the multi-physical field data compatibility problem, and the specific process is as follows:

[0088] The module has built-in physical algorithms for reconstruction calculation of flow field output data. For example, according to the chemical reaction concentration, the electron density is derived from the temperature and pressure.

[0089] Using the formula:

[0090]

[0091] Deriving the plasma frequency, where n e is the electron density, e is the electron charge, m e is the electron mass, and ε0 is the dielectric constant.

[0092] The collision frequency of the electron-neutral particle is calculated by using an empirical formula based on the gas density-temperature.

[0093] The reconstructed parameters include the plasma frequency, the collision frequency, the dielectric constant, the conductivity, etc. The parameters are stored in the log library in association to realize data backup and fast retrieval.

[0094] The collision frequency of the electron-neutral particle is calculated by using an empirical formula based on the gas density-temperature. The collision frequency of the electron-neutral particle is calculated by using an empirical formula based on the gas density-temperature. is the collision frequency, is the total number of particles, and T is the temperature.

[0095] The relative dielectric constant is calculated by using the Drude model of the plasma with collision: The relative conductivity is calculated by using ; wherein is the dielectric constant in vacuum, is the relative dielectric constant, and are the real part and the imaginary part of the relative dielectric constant, respectively, is the incident wave frequency, is the collision frequency, is the relative conductivity and are the real part and the imaginary part of the relative conductivity, respectively; i is the imaginary part in the complex function, is the relative dielectric constant, is the dielectric constant in vacuum.

[0096] In S104, the feature line of the aircraft surface is determined, the electromagnetic input parameters are extracted from the reconstructed electromagnetic parameter set, and one-dimensional spatial sequence data distributed along the feature line is generated.

[0097] Further, the determination of the feature line of the aircraft surface, the extraction of the electromagnetic input parameters from the reconstructed electromagnetic parameter set, and the generation of the one-dimensional spatial sequence data distributed along the feature line include: determining at least one feature line of the aircraft surface, and generating a corresponding feature line point set; correlating and positioning the feature points in the feature line point set with the grid vertices of the aircraft surface; based on the physical quantities at the correlated grid vertices, the physical quantity values of the points on the feature line of the aircraft surface are obtained by interpolation calculation; and one-dimensional data sequence with continuous change of the physical quantity values distributed along the feature line of the aircraft surface is generated.

[0098] Furthermore, determining at least one feature line on the surface of the aircraft includes: extracting at least one of the following from the nose cone apex to the tail tip on the plane of symmetry: a continuous curve, a nose stagnation line, and a wing edge line, based on the geometric features of the aircraft; associating and locating the feature points in the feature line point set with the grid vertices on the surface of the aircraft includes: emitting a ray from the feature point along the approximate normal direction of its grid cell, calculating the intersection of the ray with the grid on the surface of the aircraft, and determining the nearest surface grid vertex.

[0099] Specifically, in this embodiment, S104 is the data extraction step.

[0100] The data extraction step is performed by the data extraction module, which focuses on extracting key electromagnetic input parameters from the integrated and reconstructed dataset with high fidelity. Specifically, this includes:

[0101] (1) Determining surface feature lines: The data extraction module first establishes feature lines based on the aircraft's geometric features, such as extracting continuous curves from the tip of the nose cone to the tip of the tail fin, nose stationary point lines, wing edge lines, or user-specified paths on the plane of symmetry. Then, it outputs a set of feature line points L. i (i=1, 2, 3, ..., n)

[0102] (2) Mesh Association: For the extracted feature lines, this module uses the ray projection method to map the L-axis of each target on the feature lines. i The location association with the target surface mesh is specifically implemented as follows: A ray is emitted from the target point along the approximate line of its corresponding mesh cell; the intersection of this ray with all surface meshes is calculated; and the nearest intersecting cell C with the target is found. j .

[0103] (3) High-fidelity interpolation: Once the data extraction module determines that the target point is within the grid cell, it performs interpolation calculations. Based on the physical quantity (such as electron density) values ​​P(V0), P(V1), and P(V2) at the grid vertices V0, V1, and V2, the physical quantity at the target point can be obtained by linear interpolation: P(L i )=λ0* P(V0)+λ1* P(V1)+λ2* P(V2)

[0104] (4) One-dimensional sequence generation: all target points L on the feature line i After the above calculations, a set of spatially continuous physical quantity values ​​{P(L)} distributed along the characteristic line is finally obtained. i The one-dimensional data sequence is stored in the form of data pairs, which fully describes the continuous distribution of physical quantities along the characteristic line and is transmitted to the electromagnetic calculation module.

[0105] Since the "line extraction" provides high-fidelity boundary conditions with spatial continuity, the subsequent physical optics and WKB methods can play their due potential of precision.

[0106] S105, the base according to the one-dimensional spatial sequence data to perform electromagnetic environment calculation;The electromagnetic environment calculation includes scattering characteristic calculation and transmission characteristic calculation.

[0107] Specifically, the embodiment, S105 is the electromagnetic environment calculation step. The electromagnetic environment calculation step uses the extracted line data to analyze electromagnetic characteristics, including scattering characteristics and transmission characteristics. Specifically, the following sub-steps are included:

[0108] (1) Scattering characteristic calculation: the module solves Maxwell's equation based on the physical optics (PO) method to calculate the radar scattering cross section of the aircraft. This method can complete fast calculation while maintaining calculation accuracy, and is compatible with high-frequency electromagnetic wave calculation. When electromagnetic waves irradiate the target, the PO method can obtain the target surface scattering electric field E s :

[0109]

[0110] In the formula, K is the incident wave beam, r is the field point position vector, r ^ is the scattering unit vector, n ^ is the outer unit normal vector of the facet, Z 0 is the wave impedance of free space, r’ is the source point position vector, E and H are the total electric field and magnetic field on the boundary, respectively. The calculation module takes the extracted surface electromagnetic data as input parameters and outputs the scattering field distribution and the trend of the radar scattering cross section with angle and frequency. j is the imaginary unit, which can be understood as i, jk and jkr are the multiplication of the above physical quantities, but not the individual physical quantities, jk is the wave number k multiplied by the imaginary unit j, which represents the phase change rate, jkr is jk multiplied by distance r, which represents the total phase delay at distance r, and jkr^ is jk multiplied by r^, which represents the wave number multiplied by the scattering direction unit vector.

[0111] (2) Transmission characteristic calculation: the module uses the WKB method to calculate the propagation characteristics of electromagnetic waves in the plasma sheath, including signal attenuation, transmission coefficient, reflection coefficient, etc. Transmission characteristics are used to evaluate the performance of communication links and signal penetration ability.

[0112] Further, the embodiment further comprises a result visualization processing step. Wherein, the electromagnetic wave calculation result data is received by the calculation visualization module, and the binary data set is visualized by a graphical interface and a data report form to support user analysis and decision-making. The visualization content includes radar scattering cross section distribution, transmission attenuation curve, electromagnetic transmission intensity distribution, etc.

[0113] In a second aspect, the embodiment further provides a smart agent-based hypersonic vehicle electromagnetic calculation system, as shown in the accompanying drawings, the system comprises a smart agent subsystem, a calculation subsystem, and a post-processing subsystem; the smart agent subsystem comprises an intelligent classification module, a pre-prepared strategy library, a data collection module, a data integration module, a log library, and a data extraction module; the calculation subsystem comprises a flow field calculation module and an electromagnetic calculation module; the post-processing subsystem comprises a data receiving module and a visualization processing module; wherein: Figure 2

[0114] The intelligent classification module is used for automatic identification, evaluation and classification of user input parameters, and selection of N-S control equation based on the pre-prepared strategy library; the user input parameters include atmospheric environment parameters, flight height, and flight speed;

[0115] The pre-prepared strategy library is used for storing a rule set for calling by the intelligent classification module;

[0116] The flow field calculation module is used for executing computational fluid dynamics simulation based on the selection result of the intelligent classification module to obtain flow field data; the flow field data includes physical quantities and chemical quantities;

[0117] The data integration module is used for reconstructing the flow field data into electromagnetic parameters required for electromagnetic calculation to generate a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant, and electrical conductivity;

[0118] The data extraction module is used for determining a feature line of a vehicle surface, extracting electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generating one-dimensional spatial sequence data distributed along the feature line;

[0119] The electromagnetic calculation module is used for performing electromagnetic environment calculation according to the one-dimensional spatial sequence data; the electromagnetic environment calculation includes scattering characteristic calculation and transmission characteristic calculation;

[0120] The visualization processing module is used for visualizing electromagnetic environment calculation results.

[0121] ​Further, the system is deployed on a hardware platform comprising high-performance computing servers, mass storage devices, and high-speed internal buses, and the modules interact with each other through the high-speed internal buses. Among them, the data collection module is used to capture and convert the flow field calculation results; the log library is used to store, back up and manage all intermediate and final data; and the data receiving module is used to receive and back up the electromagnetic calculation results.

[0122] As shown in Figure 3 The operation flowchart of the intelligent agent-based hypersonic vehicle electromagnetic calculation system of the present embodiment is shown.

[0123] 1. Intelligent classification module:

[0124] This module is responsible for automatically identifying, evaluating and classifying the initial model parameters input by the user, replacing the traditional manual experience selection process. The module is integrated and deployed on the front-end server and operates by calling the pre-made policy library. The main functions include:

[0125] (a) Format recognition: Analyze the file header, extension and internal data structure of the input file, automatically determine whether the model is in two-dimensional or three-dimensional format, and adapt the data interface required by the subsequent calculation process accordingly.

[0126] (b) Parameter evaluation: Perform logical and physical checks on the parsed parameter content to evaluate the completeness and reasonableness of the parameters (atmospheric environment, flight speed, flight altitude, chemical reaction flag). For example, determine whether a plasma sheath will be generated based on the flight speed, and determine whether the flow is in a thermochemical non-equilibrium state based on the flight altitude and chemical composition.

[0127] (c) Selection decision: Based on the evaluation results, query and call the rules in the pre-made policy library, intelligently select the most suitable N-S control equation and chemical reaction model, and issue instructions to the flow field calculation module.

[0128] 2. Flow field calculation module:

[0129] This module is responsible for performing computational fluid dynamics simulation and accurately solving the control equations specified by the intelligent classification module to obtain the flow field distribution around the vehicle. The module runs on a high-performance server that handles large-scale numerical calculations, and the main functions include:

[0130] (a) Physical solution: Discretize and iterate the N-S equation in space using the finite element method until the flow field physical quantities (such as temperature, pressure, density, and velocity) converge.

[0131] (b) Chemical solution: When the chemical reaction flag is enabled, this module solves the chemical component transport equation and reaction kinetics equation in parallel to calculate chemical parameters such as electron density and component concentration.

[0132] 3. Data collection module:

[0133] This module is responsible for capturing the original calculation results comprehensively and losslessly from the output of the flow field calculation module. It is connected with the flow field calculation module through a high-speed internal bus (such as PCIe) to achieve low-latency throughput of output data; at the same time, it has built-in multiple data converters that can automatically convert raw data into formats required by general or specific post-processing software such as ASCII, CGNS, etc., ensuring the downstream compatibility of data.

[0134] 4. Data integration module:

[0135] This module is responsible for converting flow field data into input parameters that can be directly used for electromagnetic calculation, relying on the central processor of the system to call built-in physical algorithms to perform a series of conversion calculations on the collected flow field data. For example, using the concentration of chemical reaction components combined with temperature and pressure to calculate electron density; using the electron density and plasma frequency correlation formula:

[0136]

[0137] deduce the plasma frequency; use the gas density and temperature formula to deduce the collision frequency, etc. At the same time, logically associate the reconstructed electromagnetic parameters (dielectric constant, conductivity, etc.) with the original flow field data to form a complete multi-physics data set.

[0138] 5. Log library:

[0139] The log library is responsible for storing, backing up and managing all intermediate and final data, mainly implemented by a large-capacity disk array, not only storing the reconstructed parameters output by the data integration module, but also recording the decision logs of the intelligent classification module, flow field calculation raw data, electromagnetic calculation output data, etc., supporting fast retrieval and backtracking analysis of data.

[0140] 6. Data extraction module:

[0141] This module is responsible for accurately extracting electromagnetic parameters from the surface of the aircraft from the integrated three-dimensional data set, and its operation relies on the integrated graphics processing unit hardware and efficient network topology processing hardware of the system. This module first automatically identifies the surface grid nodes based on the aircraft geometric model; at the same time, along the preset surface contour line or characteristic line, a one-dimensional, continuous parameter sequence (such as the electron density distribution along a generatrix from the aircraft nose cone to the tail) is sampled and extracted from the three-dimensional data set through linear interpolation. This "line extraction" method avoids traditional layered approximation and completely preserves the spatial gradient information of the data.

[0142] 7. Electromagnetic calculation module:

[0143] The module is responsible for the simulation of the interaction between electromagnetic wave and the aircraft and its plasma sheath based on the extracted surface current data. Mainly includes the following functions:

[0144] (a) Electromagnetic scattering characteristics calculation: the physical optics method is used to solve Maxwell's equations to calculate the radar scattering cross section of the aircraft. The calculation process takes the extracted surface electromagnetic parameters as the boundary conditions, and outputs the scattering field data varying with angle and frequency.

[0145] (b) Electromagnetic propagation characteristics calculation: the WKB calculation method is used to analyze the propagation effect of electromagnetic wave in the plasma sheath, and the attenuation, transmission and reflection coefficients of the signal are calculated to evaluate the communication link performance.

[0146] 8、Data receiving module:

[0147] The module is responsible for receiving the output results of the electromagnetic calculation module. It is connected with the electromagnetic calculation module through a high-speed internal bus (such as PCIe) to realize low-delay throughput of the output data; at the same time, it is connected with the intelligent agent log library to quickly save the received data to the log library for backup.

[0148] 9、Visualization processing module:

[0149] The visualization processing module serves as the interactive interface between the system and the user, responsible for converting binary results into intuitive graphics and reports. The module is responsible for receiving data from the data receiving module, generating radar scattering cross section distribution graph, transmission attenuation curve, electromagnetic field intensity cloud map and other visualization results, supporting user's interactive analysis, result export and report generation.

[0150] 10、Preparation strategy library:

[0151] As the knowledge support of the intelligent classification module, it stores the rule set formed by the domain expert knowledge and historical calculation experience, mainly stored in high-speed storage (such as SSD) for real-time reading by the intelligent classification module; the rules in the library exist in the form of "condition-action" pairs. For example, the rule is defined as: "condition: flight speed > 20 Mach, flight altitude > 60 km; action: select three-dimensional compressible N-S equation, select temperature-based input window, start 7-component chemical reaction model (such as Gupta_7), set viscous solid wall boundary conditions."

[0152] Further, the embodiment takes the electromagnetic characteristics of the classic hypersonic target RAMC-II aircraft at a flight altitude of 60 km and a flight speed of 20 Mach as an example to demonstrate the implementation process of the system. The software program of the system is deployed on one or more high-performance computing servers interconnected through a network. These servers are equipped with multi-core central processors, large-capacity memories, high-speed solid-state drives and professional graphics processing units. The specific implementation steps are as follows:

[0153] Step 1: Parameter input and intelligent classification

[0154] (1) User operation: The user uploads a three-dimensional geometric model mesh file (such as.stl or.obj format) of the RAMC-II aircraft through the graphical interface of the system, and inputs the flight conditions in the parameter setting interface: flight altitude 60 km, flight speed 20 Mach (about 6800 m / s), and checks the "enable chemical reaction" option.

[0155] (2) System execution - intelligent classification:

[0156] The intelligent classification module automatically parses the file header of the uploaded file and confirms that it is a three-dimensional model format, and prepares the three-dimensional calculation process accordingly. Further, the module evaluates the input flight conditions. According to the high speed of 20 Mach and the altitude of 60 km, it is determined that the flow is compressible and a plasma sheath will be generated; the enable chemical reaction flag indicates that a thermochemical non-equilibrium calculation needs to be performed.

[0157] Based on the above evaluation, the intelligent classification module queries the pre-prepared strategy library and matches the rule: "if the flight speed > 5 Mach and the chemical reaction is enabled, select the three-dimensional compressible N-S control equation, and use the 7-component air chemical reaction model (such as Park model), set the viscous, no-slip wall boundary conditions". Then, the decision instruction is issued to the flow field calculation module.

[0158] Step 2: Flow field environment calculation

[0159] The flow field calculation module receives the instruction from the intelligent classification module and starts the computational fluid dynamics solver.

[0160] Physical process calculation: The solver solves the three-dimensional compressible N-S equation based on the finite volume method discretization and iteration of 10000 steps, and calculates the temperature, pressure, density and velocity distribution of the flow field. The calculation continues until the residual of all physical quantities converges to the preset threshold 10 -5 From now on, the flow field reaches a steady state.

[0161] Chemical process calculation: In parallel, the solver solves the chemical component transport equation according to the specified 7-component chemical reaction model to calculate the chemical component concentration such as electron density and ion density in the flow field.

[0162] Step 3: Flow field data collection and format conversion

[0163] The data collection module follows the flow field calculation process, and immediately reads all the grid nodes' physical quantities (temperature, pressure, etc.) and chemical quantities (electron density, etc.) from the CFD solver through the application program interface after the calculation converges. In this embodiment, the nitrogen gas accounts for 79%, the oxygen gas accounts for 19%, and other gases account for 2% in the flow field of the RAMC aircraft. The stagnation temperature is 7000K, and the stagnation pressure is 9000Pa.

[0164] To realize seamless docking with subsequent modules, the module automatically converts the original binary data into the standard ASCII format, ensuring that the data structure is complete and easy to process subsequently.

[0165] Step 4: Data integration reconstruction

[0166] The data integration module reads the flow field data in the ASCII format. Then, built-in physical algorithms are called for reconstruction calculation: the electron density ne is calculated using the chemical reaction concentration correlation; the plasma frequency ωp is calculated point by point using the frequency formula ; and the electron-neutral particle collision frequency is calculated according to the gas density and temperature in the flow field through an empirical formula. All the reconstructed electromagnetic parameters (plasma frequency, collision frequency, dielectric constant, and conductivity derived therefrom) are associated and packaged together with the original flow field data and stored in the log library for backup and recording.

[0167] In this embodiment, the calculation shows that the peak value of the flow field electron density is 1020 (Ne / m3), the axial plasma frequency is 25GHz-9GHz, and the collision frequency is 0.9GHz-2GHz.

[0168] Step 5: Electromagnetic parameter extraction

[0169] The data extraction module obtains the three-dimensional data set integrated by the data integration module. First, the surface grid of the RAM-II aircraft geometric model is identified. Then, along a key feature line (such as the generatrix on the symmetry plane, the normal line of the vertical wall surface, and the stagnation point line) from the nose cone vertex to the tail fin on the aircraft surface, the electron density, plasma frequency, and collision frequency data of all nodes on the line are accurately extracted through linear interpolation sampling technology. Finally, a one-dimensional line array that maintains spatial continuity is generated and sent to the electromagnetic calculation module for calculation. This "line extraction" method avoids the information loss caused by traditional rough layering, and compared with "three-dimensional body extraction", it avoids full three-dimensional field calculation and reduces the calculation amount.

[0170] Step 6: Electromagnetic environment calculation

[0171] (1) Scattering property calculation: the module adopts the physical optics (PO) method. The extracted surface line data is taken as the electromagnetic boundary condition, the incident electromagnetic wave frequency (such as X-band 10GHz) and the incident angle (0° for the vertical wall) are set, and the Maxwell equation set is solved. The scattering field of the aircraft is obtained by calculating the integral, and then the curve of the radar scattering cross section with the observation angle and the incident frequency is calculated.

[0172] (2) Transmission property calculation: the module adopts the WKB method. The propagation process of the continuous frequency (0-10GHz) communication electromagnetic wave in the calculated plasma sheath (whose characteristics are described by the extracted parameters) is analyzed, the signal attenuation constant, the transmission coefficient and the reflection coefficient are calculated, and the severity of the "black barrier" effect of the aircraft in this flight state and the communication link performance are evaluated.

[0173] Through calculation, the penetration coefficient rises to 80% and the radar scattering cross section decreases by 15dB when the incident electromagnetic wave is 10GHz.

[0174] Step 7: result visualization and output

[0175] The visualization processing module obtains the original result data of electromagnetic calculation from the data receiving module. On a graphics workstation, it renders binary data into intuitive charts, including: the radar scattering cross section distribution cloud chart of the RAM-II aircraft. The polar coordinate graph of the radar scattering cross section with the change of the azimuth angle. The signal attenuation curve of the electromagnetic wave in the plasma sheath with the change of the frequency. The signal transmission / reflection coefficient curve of the electromagnetic wave in the plasma sheath with the change of the frequency. Users can interactively view these charts on the graphical interface, zoom in, rotate and analyze, and can export the charts and data reports for the final technical report and performance evaluation.

[0176] Through the above seven logically rigorous steps (step 1-step 7), this embodiment completely demonstrates how the system and method automatically complete the flow field calculation, data conversion and integration through the intelligent agent from the original parameter input, and finally provide intuitive visualization results for users by using high-precision line extraction data as the input parameters of electromagnetic simulation. The whole process minimizes human intervention, solves the problem of data integration under multi-physical field coupling, and significantly improves the calculation accuracy due to the preservation of complete surface data gradient, fully embodying the superiority and practicality of the present application.

[0177] Compared with the prior art, the intelligent calculation method and system of electromagnetic characteristics of hypersonic aircraft based on intelligent agent provided by the present application, through its complete technical scheme, brings the following significant beneficial effects:

[0178] 1. The accuracy and physical fidelity of electromagnetic calculation are improved. The core innovation of the present application is to use the "data line extraction" technology to directly extract a one-dimensional continuous electromagnetic parameter sequence along the aircraft surface contour line or feature line by linear interpolation sampling from the integrated and reconstructed three-dimensional data set. This method completely abandons the simplified model in the traditional WKB method that approximates the plasma sheath as a finite number of discrete dielectric constant layers. By completely preserving the spatial gradient information and continuity of physical parameters (such as electron density and plasma frequency) along the surface, the model error introduced by layering and roughness is fundamentally avoided. Compared with the traditional layering strategy, the present application can obtain more accurate electromagnetic scattering and transmission characteristic calculation results under the same grid density, especially it can more realistically reflect the electromagnetic effects of key areas such as shock waves and boundary layers.

[0179] 2. Efficient and automatic integration of interdisciplinary data is realized, and manual intervention and integration complexity are reduced. The present application builds a fully automated data processing pipeline through "intelligent classification module", "data integration module" and "log library". The intelligent classification module automatically identifies input parameters and selects control equations; the data integration module automatically reconstructs the flow field data into the input parameters required for electromagnetic calculation through built-in physical algorithms (such as electron density and plasma frequency calculation formula), and stores them in association. This scheme solves the information integration problem caused by the incompatibility of data format and grid system between CFD and CEM two disciplines. The system realizes the full-link automation from flow field calculation to electromagnetic parameter generation, and researchers do not need to manually perform tedious data format conversion, transmission and preprocessing work, greatly improving the work efficiency and reducing the risk of errors caused by human operation errors, which provides the possibility for rapid and multi-condition numerical analysis.

[0180] 3. The algorithm usage threshold and dependence on specific artificial experience are reduced, and the intelligent level is improved. The intelligent agent subsystem (especially the intelligent classification module) integrates the "pre-made strategy library" formed by the knowledge of domain experts, which can automatically and intelligently select the most suitable N-S control equation and chemical reaction model according to the input flight conditions (altitude, speed, chemical reaction, etc.). This design enables researchers without deep fluid mechanics background to quickly and accurately start complex multi-physical field simulation calculation.

[0181] 4. A complete, efficient and traceable simulation analysis ecosystem is constructed. The technical scheme of the present application is a complete system integrating intelligent classification, flow field calculation, data integration, line extraction, electromagnetic calculation and visualization. The "log library" designed in the system records all intermediate data and process logs from initial decision to final result. The ecosystem ensures high reproducibility and traceability of the calculation process. The results of any calculation can be completely traced back, facilitating error analysis, scheme optimization and knowledge accumulation. At the same time, the modules are connected through a high-speed bus and accelerated by hardware such as GPU (e.g. data extraction and electromagnetic calculation), ensuring high precision while maintaining overall computing efficiency, which can meet the demand for large-scale and high-precision simulation in engineering practice.

[0182] The above merely describes the embodiments of the present application and is not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for electromagnetic calculation of hypersonic vehicles, characterized in that, include: A NS control equation is selected from a pre-built rule base based on user input parameters; the user input parameters include atmospheric environmental parameters, flight altitude, and flight speed. The flow field data is calculated based on the Navier-Stokes governing equations and collected; the flow field data includes physical and chemical quantities. The flow field data is reconstructed into electromagnetic parameters required for electromagnetic calculation, generating a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant, and conductivity; The surface feature lines of the aircraft are determined, electromagnetic input parameters are extracted from the reconstructed electromagnetic parameter set, and one-dimensional spatial sequence data distributed along the feature lines are generated. Electromagnetic environment calculations are performed based on the one-dimensional spatial sequence data; the electromagnetic environment calculations include scattering characteristic calculations and transmission characteristic calculations. The process of determining the surface feature lines of the aircraft, extracting electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generating one-dimensional spatial sequence data distributed along the feature lines includes: Identify at least one feature line on the surface of the aircraft and generate a corresponding feature line point set; associate and locate the feature points in the feature line point set with the mesh vertices on the surface of the aircraft. Based on the physical quantities at the associated grid vertices, the physical quantity values ​​of each point on the feature line of the aircraft surface are obtained by interpolation calculation; Generate a one-dimensional data sequence in which the physical quantity values ​​continuously change along the feature lines on the surface of the aircraft; The determination of at least one feature line on the surface of the aircraft includes: extracting at least one of the following based on the geometric features of the aircraft: a continuous curve on the plane of symmetry from the apex of the nose cone to the tip of the tail fin: a nose stagnation line; and a wing edge line. The step of associating and locating the feature points in the feature line point set with the mesh vertices on the aircraft surface includes: emitting a ray from the feature point along the approximate normal direction of its mesh cell, calculating the intersection of the ray with the mesh on the aircraft surface, and determining the nearest surface mesh vertex.

2. The electromagnetic calculation method for hypersonic vehicles according to claim 1, characterized in that, The calculation of flow field data based on the NS control equations includes calculations of physical quantities and chemical quantities. The physical quantity calculation includes: using the finite element method to discretize and solve the NS control equations on a spatial grid to calculate the flow field temperature and pressure; In three-dimensional Cartesian coordinates, the NS governing equations are expressed as: Where Q is a conserved quantity, and E, F, and G are diffusion terms in the x, y, and z directions, respectively. V F V G V Let S be the convection term in three directions, and S be the source vector.

3. The electromagnetic calculation method for hypersonic vehicles according to claim 2, characterized in that, The calculation of the chemical quantities includes: If the user-input parameters meet the chemical reaction conditions, the chemical reaction transport equations and reaction kinetic equations in the Park reaction model or Gupta reaction model are solved according to the actual environmental conditions, and the chemical variables are calculated; the chemical variables include electron density and reaction rate.

4. The electromagnetic calculation method for hypersonic vehicles according to claim 1, characterized in that, The step of reconstructing the flow field data into electromagnetic parameters required for electromagnetic calculation, and generating a reconstructed electromagnetic parameter set, includes: Plasma frequency: ; Where, n e where e is the electron density, e is the electron charge, and m is the electron density. e Where ε is the electron mass, and ε0 is the dielectric constant; Using an empirical formula based on gas density and temperature: Calculate the collision frequency between electrons and neutral particles; where For collision frequency, Where T is the total number of particles and T is the temperature; Using a collision-based plasma Drude model: Used to calculate the relative permittivity; , used to calculate relative conductivity; where, The dielectric constant in vacuum is . The relative permittivity, and These are the real and imaginary parts of the relative permittivity, respectively. The incident wave frequency, For collision frequency, relative conductivity and , respectively, represent the real and imaginary parts of the relative conductivity; i is the imaginary part of the complex function. The relative permittivity, It is the vacuum dielectric constant; A set of reconstructed electromagnetic parameters is generated based on the plasma frequency, collision frequency, dielectric constant, and conductivity, and stored in the log library.

5. The electromagnetic calculation method for hypersonic vehicles according to claim 1, characterized in that, The transmission characteristic calculation includes: The propagation characteristics of electromagnetic waves in a plasma sheath were calculated using the WKB method; the propagation characteristics include signal attenuation, transmission coefficient, and reflection coefficient.

6. A hypersonic vehicle electromagnetic calculation system based on intelligent agents, used to execute the hypersonic vehicle electromagnetic calculation method according to any one of claims 1-5, characterized in that, It includes an intelligent agent subsystem, a computing subsystem, and a post-processing subsystem; the intelligent agent subsystem includes an intelligent classification module, a pre-built strategy library, a data collection module, a data integration module, a log library, and a data extraction module; the computing subsystem includes a flow field calculation module and an electromagnetic calculation module; the post-processing subsystem includes a data receiving module and a visualization processing module; wherein: The intelligent classification module is used to automatically identify, evaluate, and classify user input parameters, and select the NS control equation based on a pre-built strategy library; the user input parameters include atmospheric environmental parameters, flight altitude, and flight speed. A pre-built strategy library is used to store rule sets for the intelligent classification module to call; The flow field calculation module is used to perform computational fluid dynamics simulation based on the selection results of the intelligent classification module to obtain flow field data; the flow field data includes physical quantities and chemical quantities. The data integration module is used to reconstruct the flow field data into electromagnetic parameters required for electromagnetic calculation, and generate a reconstructed electromagnetic parameter set; the electromagnetic parameters include plasma frequency, collision frequency, dielectric constant and conductivity; The data extraction module is used to determine the feature lines on the surface of the aircraft, extract electromagnetic input parameters from the reconstructed electromagnetic parameter set, and generate one-dimensional spatial sequence data distributed along the feature lines. The electromagnetic calculation module is used to perform electromagnetic environment calculations based on the one-dimensional spatial sequence data; the electromagnetic environment calculations include scattering characteristic calculations and transmission characteristic calculations. The visualization module is used to visualize the electromagnetic environment calculation results.

7. The electromagnetic computing system for hypersonic vehicles based on intelligent agents according to claim 6, characterized in that, The system is deployed on a hardware platform that includes a high-performance computing server, a large-capacity storage device, and a high-speed internal bus. The modules interact with each other through the high-speed internal bus. The data collection module is used to capture and convert the flow field calculation results; the log library is used to store, back up, and manage all intermediate and final data; and the data receiving module is used to receive and back up the electromagnetic calculation results.

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