Table look-up type deformation matching and electromagnetic mapping digital twinning system and method

Abstract

The invention discloses a table look-up type deformation matching and electromagnetic mapping digital twinning system and a table look-up type deformation matching and electromagnetic mapping digital twinning method. The system pre-constructs a multi-physical field simulation database with speed as a main key, stores a deformation three-dimensional model, pressure field data, radar cross section (RCS) data and feature point displacement, and establishes a reduced scale model deformation-speed association list. In the manual mode, the speed is directly input to call corresponding multi-physical field data; in an automatic mode, the displacement of the feature points of the reduced scale entity model is detected in real time through a displacement detection module, the current deformation quantity is calculated, a speed major key is reversely matched by adopting a minimum absolute difference method based on the association list, and then corresponding multi-physical field data is called; and synchronously displaying the deformation three-dimensional model, the pressure field pseudo-color distribution and the RCS map on a visual rendering platform, and realizing digital mapping from entity deformation to a multi-physical field state.

Description

Technical Field

[0001] This invention relates to the field of digital twin and multiphysics coupling simulation technology for aircraft, and particularly to a lookup table-based deformation matching and electromagnetic mapping digital twin system and method, which is applicable to the linkage analysis and visualization of the aerodynamic, structural and electromagnetic scattering characteristics of aircraft. Background Technology

[0002] During flight, aircraft exhibit significant coupling relationships between aerodynamic loads, structural deformation, and electromagnetic scattering characteristics. Particularly at different speeds, the pressure field on the aircraft surface changes, leading to elastic deformation in structural components such as wings and tail fins. This structural deformation further affects the aircraft's aerodynamic performance, structural safety, and radar cross-section (RCS) characteristics. Therefore, applications such as aircraft condition assessment, stealth performance analysis, flight safety verification, and educational demonstrations often require joint analysis and simultaneous presentation of aerodynamic, structural, and electromagnetic states.

[0003] Currently, there are two main approaches to multiphysics coupling analysis of aircraft: one is a case-by-case independent solution approach that performs aerodynamic flow field, structural mechanics, and electromagnetic scattering simulations for different speeds, attitudes, and other operating conditions. While this approach can obtain analysis results for a single operating condition, it typically involves long computation cycles and high computing costs, making it difficult to quickly retrieve and display results for multiple operating conditions in real time. The other approach is a digital twin technology solution for specific scenarios, such as Chinese patents with publication numbers CN121479922A and CN121580587A. Although digital twin applications have been implemented in relevant scenarios, a complete real-time digital mapping solution for the aerodynamic-structural-electromagnetic multiphysics coupling relationship of aircraft has not yet been formed.

[0004] Furthermore, existing technologies typically lack a mechanism for rapidly matching and synchronously mapping multi-physics states based on deformation detection results of physical models, making it difficult to simultaneously meet the application requirements of both rapid querying of fixed working conditions and dynamic synchronization driven by physical deformation. At the same time, existing solutions also fall short in terms of mode switching flexibility, ease of operation, and real-time interactivity in different scenarios such as teaching demonstrations, scheme presentations, experimental verification, and equipment evaluation.

[0005] Therefore, it is necessary to propose a lookup-based deformation matching and electromagnetic mapping digital twin system and method based on a pre-built multiphysics simulation database, so as to achieve rapid matching, synchronous display and visualization of the deformation of the aircraft entity and the multiphysics state without the need for real-time simulation calculation. Summary of the Invention

[0006] Technical Problem: The purpose of this invention is to provide a lookup-based deformation matching and electromagnetic mapping digital twin system and method to solve the problems of high computational cost, slow response speed, insufficient scene adaptability, and difficulty in simultaneously handling fast lookup under fixed conditions and dynamic synchronization driven by physical deformation in existing multiphysics coupling analysis of aircraft. By pre-constructing a multiphysics simulation database and performing lookup matching based on the current deformation of the physical model, this invention can achieve rapid mapping and visualization of structural deformation, pressure field, and electromagnetic scattering characteristics without the need for real-time simulation calculations.

[0007] Technical Solution: To achieve the above objectives, the present invention proposes the following technical solution:

[0008] A lookup-based deformation matching and electromagnetic mapping digital twin system includes:

[0009] The database module pre-builds and stores multiphysics data with velocity as the primary key. The multiphysics data includes at least a three-dimensional deformation model, pressure field data, RCS data, and feature point displacement.

[0010] The mode control module supports switching between manual and automatic modes and triggers the corresponding data matching process based on the mode type.

[0011] The displacement detection module is used to detect the displacement of feature points of the scaled solid model in real time in automatic mode and calculate the current deformation.

[0012] The communication module is used to realize real-time data transmission between the displacement detection module and the data matching module in automatic mode;

[0013] The data matching module, in manual mode, directly retrieves the database module based on the speed input by the user. In automatic mode, it retrieves the speed primary key in reverse by using the minimum absolute difference method of the deformation-velocity association list of the scaled model based on real-time deformation detection data, and then retrieves the corresponding multiphysics data.

[0014] The visualization rendering module synchronously renders the target's deformed 3D model, pressure field pseudo-color distribution, and RCS map in the visualization rendering platform based on the matching results, realizing real-time digital mapping of entity deformation to multi-physics field state.

[0015] Furthermore, the database module is pre-built through the following steps:

[0016] A full-size 3D solid model of the target is constructed using a 3D solid modeling tool, which serves as the initial geometric boundary.

[0017] In the multiphysics simulation platform and the electromagnetic scattering simulation platform, the mesh generation that meets the requirements is completed based on the initial geometric boundary, wherein the size of the electromagnetic simulation mesh is no greater than 1 / 10 of the minimum wavelength of the working frequency band;

[0018] A unidirectional coupling simulation process of aerodynamics and structure is built on a multiphysics simulation platform. Coupled simulation is performed on multiple speed conditions within a preset speed range to obtain structural deformation results under each condition and export the three-dimensional deformation model file and pressure field data.

[0019] The electromagnetic scattering simulation platform uses the electromagnetic scattering simulation method to import a model file with consistent deformation and solve for the RCS data containing amplitude and phase information under the corresponding working conditions.

[0020] A multiphysics simulation database with velocity as the primary key is constructed, and a scaled model deformation-velocity correlation list is built based on the displacement of feature points as a data source for automatic pattern reverse matching.

[0021] Furthermore, the construction rules for the association list are as follows: extract the original displacement data of the feature points in the Z direction of the full-size model under each velocity condition from the multiphysics simulation database; determine the scaling factor between the full-size model and the scaled detection model, and convert the displacement data into the deformation of the scaled model according to the scaling factor; associate the deformation of the scaled model with the corresponding velocity one by one to form an association list with one-to-one index position; and unify the precision of the deformation data in the list to 3 decimal places, consistent with the output precision of the displacement detection module.

[0022] Furthermore, in the automatic mode, the data matching module performs the following reverse matching process:

[0023] The displacement detection module receives the Z-direction displacement of the feature points of the scaled solid model in real time, and takes the absolute value of the difference between the current Z coordinate of the feature point and the Z coordinate of the feature point under the initial no-load state as the current deformation. Then, based on the preloaded association list, the minimum absolute difference method is used to traverse the list of deformations of the scaled model to determine the matching index that is closest to the current deformation. The corresponding velocity primary key is extracted through the matching index, and then the complete multiphysics data at that velocity is retrieved from the multiphysics simulation database.

[0024] Furthermore, in the manual mode, the user can directly input the speed condition through the speed input box on the visual interactive interface. The system uses the input speed as the retrieval key to directly retrieve the multiphysics data of the corresponding condition from the database, without going through the deformation detection and table lookup matching process. In this mode, the speed input box is enabled, while in the automatic mode, the speed input box is disabled.

[0025] The present invention also provides a lookup-based deformation matching and electromagnetic mapping digital twin method applied to the system, comprising the following steps:

[0026] Step 1: Pre-build a multiphysics simulation database: Obtain the deformation 3D model, pressure field data, RCS data and feature point displacement under different speed conditions through multiphysics simulation, and establish a database with velocity as the primary key. At the same time, build a correlation list of deformation and velocity of the scaled model based on the feature point displacement.

[0027] Step 2: Receive the mode selection instruction and execute different data acquisition processes according to the selected mode:

[0028] If it is in manual mode, the system receives the speed condition input by the user and directly retrieves the corresponding multiphysics data from the database using that speed as the primary search key.

[0029] In automatic mode, the displacement detection module detects the displacement of feature points of the scaled solid model in real time and calculates the current deformation. The deformation is transmitted to the data matching module through the communication module. Based on the association list, the minimum absolute difference method is used to obtain the velocity primary key through reverse matching. Then, the corresponding multiphysics data is retrieved from the database using the velocity primary key.

[0030] Step 3: Simultaneously render the multiphysics data retrieved in Step 2 in the visualization rendering module to achieve real-time digital mapping of entity deformation to multiphysics state; in manual mode, the rendering is updated in real time according to user input, and in automatic mode, Step 2 to Step 3 are executed cyclically according to the deformation detection results.

[0031] Preferably, the specific steps for pre-constructing the multiphysics simulation database in step one include:

[0032] Based on the actual structural parameters, geometric features and physical properties of the target entity, a full-size 3D model of the target entity is constructed using 3D modeling tools. The model completely restores the key structure of the target and is consistent with the entity. This model is used as the initial geometric boundary.

[0033] In the multiphysics simulation platform and the electromagnetic scattering simulation platform, mesh generation was completed based on the initial geometric boundary to meet the corresponding simulation requirements. The size of the electromagnetic simulation mesh was strictly controlled to be no more than 1 / 10 of the minimum wavelength of the working frequency band.

[0034] Aerodynamic-structural unidirectional coupling simulation was performed on a multiphysics simulation platform to obtain three-dimensional deformation models and pressure field data under different speed conditions.

[0035] Electromagnetic scattering simulation consistent with structural deformation was performed on the electromagnetic scattering simulation platform to obtain radar scattering cross section data under the corresponding working conditions.

[0036] The data is organized and stored with velocity as the primary key. The Z-direction displacement of the feature points of the full-size simulation model is converted into scaled model deformations according to the scaling factor. A scaled model deformation-velocity association list is formed with the corresponding velocity value, and the association list is a two-column parallel association list. The data in the list is uniformly reserved to 3 decimal places.

[0037] Preferably, the reverse matching in automatic mode in step two specifically includes:

[0038] The displacement detection module is activated to monitor the feature points of the scaled solid model in real time, collect displacement data in the Z direction, and calculate the absolute value of the difference between the current coordinate and the reference coordinate as the current actual deformation using the initial unloaded state as the reference. A low-latency communication link is established through the communication module to convert the deformation data into a character encoded string and transmit it to the data matching module.

[0039] After the data matching module decodes and restores the deformation data, it traverses the preloaded scaled model deformation-velocity association list, calculates the absolute difference between the current deformation and each deformation in the list, filters the minimum difference and obtains the corresponding index, extracts the matching velocity value as the velocity primary key, and provides a retrieval basis for multiphysics data retrieval.

[0040] Preferably, the synchronous rendering of the visualization rendering module in step three includes:

[0041] Load the deformed 3D model for 3D display;

[0042] The pressure field distribution is rendered in pseudo-color.

[0043] Draw RCS maps to cover the entire spatial angular range;

[0044] The visual interactive interface simultaneously displays the current mode type, speed value, deformation, and detection frame rate;

[0045] In manual mode, the speed input box is enabled, while in automatic mode, the speed input box is disabled.

[0046] Preferably, in the automatic mode, if the association list fails to load or is empty, a preset single-sample matching function is called to obtain a preset default velocity value as the velocity primary key, and the corresponding multiphysics data is retrieved from the database using this velocity primary key.

[0047] Beneficial effects: Compared with the prior art, the present invention has at least the following beneficial effects:

[0048] (I) Advantages in Technological Innovation

[0049] 1. By pre-constructing a multiphysics simulation database with velocity as the primary key, and replacing traditional real-time simulation with a lookup-and-match method, the inherent drawbacks of high computational cost and slow response speed of traditional solutions are fundamentally avoided. During system operation, no real-time simulation calculations are required; multiphysics data can be retrieved in milliseconds simply through primary key lookup, significantly reducing computational load. Furthermore, the multiphysics data comes from industry-standard high-precision simulation software such as ANSYS and CST, without relying on machine learning prediction models, thus avoiding prediction bias at its source. The data is traceable and reproducible, fully meeting the needs of high-precision scientific research and engineering applications.

[0050] 2. A control logic for one-click switching between manual and automatic modes was designed, which can simultaneously cover two core application scenarios: static evaluation and dynamic interaction. Manual mode allows users to directly input speed and operating conditions to quickly retrieve corresponding data, meeting the static requirements of fixed-condition queries and multi-condition performance comparisons. Automatic mode, through the efficient UDP communication protocol and the minimum absolute difference method, achieves near-delayed updates of entity deformation and the virtual model, meeting the dynamic requirement of real-time entity-virtual synchronization and solving the problem of insufficient scenario adaptability in traditional single-mode systems.

[0051] 3. A reverse mapping from deformation to speed is achieved using a dual-column parallel association list and the minimum absolute difference method. This algorithm is easy to implement, has high traversal efficiency, and controllable matching accuracy. Simultaneously, the system has a built-in degradation and fault tolerance mechanism. When the dual-column parallel association list fails to load or is empty, a preset single-sample matching function can be called to ensure normal system operation, avoiding interruptions due to abnormal data loading and effectively improving the system's stability and fault tolerance.

[0052] 4. A multi-platform modular architecture is adopted, decoupling the simulation automation process, cross-platform data interaction, and visualization rendering functions. The standardized interfaces of each module ensure strong compatibility, resolving the issues of high coupling and difficult maintenance and iteration inherent in traditional integrated platforms. Simultaneously, the multiphysics simulation database possesses exceptional scalability, supporting not only the core velocity dimension but also flight attitude, material properties, and shape parameters, without requiring reconstruction of the system's core architecture and matching logic, significantly improving the system's reusability and adaptability.

[0053] (II) Practical Application Value

[0054] 1. By using three-dimensional visualization, abstract multiphysics data such as structural deformation, pressure field distribution, and RCS characteristics are transformed into intuitive visual images. This clearly presents the coupling mechanism of aerodynamic-structural-electromagnetic multiphysics, significantly reducing the understanding threshold of multiphysics coupling simulation technology. It is very suitable for classroom teaching, experimental demonstrations, and popular science display scenarios in related majors in universities.

[0055] 2. It supports real-time comparison and verification between physical scaled-down models and simulation data, and can intuitively present the influence of structural deformation on electromagnetic scattering characteristics and aerodynamic load distribution. It can be directly used for experimental verification of related topics such as the influence of aircraft structural deformation on electromagnetic characteristics, aerodynamic load distribution, and stealth performance optimization, effectively shortening the scientific research experimental cycle and improving research efficiency.

[0056] 3. The visual interactive interface can intuitively present the core working condition parameters and multi-physics field distribution. It is easy to operate and has a low threshold for use. The manual mode can quickly respond to the working condition query needs, and the automatic mode can realize unattended automated operation. It can perfectly adapt to engineering application scenarios such as equipment scheme demonstration, on-site condition assessment, and stealth performance testing, and solves the problem that traditional simulation systems have high operating thresholds and cannot adapt to on-site applications.

[0057] 4. At the same time, relying on the core technological advantages of high real-time performance and high adaptability, this invention can be widely applied to core areas such as aerodynamic status assessment of various aircraft, electromagnetic stealth characteristic demonstration, and construction of multi-physics field coupled digital twin systems. It comprehensively covers diversified application scenarios such as teaching and training, scientific research, equipment performance evaluation, and scheme demonstration. It has both technological advancement and engineering feasibility, and has strong practicality and promotion value. Attached Figure Description

[0058] Figure 1 This is the overall flowchart of the present invention.

[0059] Figure 2 This is a flowchart of the multiphysics simulation database construction process.

[0060] Figure 3 This is a flowchart of the aerodynamic-structural unidirectional coupling solution process.

[0061] Figure 4 This is a schematic diagram of the electromagnetic scattering simulation process.

[0062] Figure 5 This is a schematic diagram of the deformation detection process of displacement detection equipment.

[0063] Figure 6 This is a flowchart of the automatic table lookup matching and visualization rendering process.

[0064] Figure 7 This is the RCS distribution diagram under typical operating conditions in the 150MHz frequency band.

[0065] Figure 8 This is a comparison chart of RCS curves under different deformation conditions.

[0066] Figure 9 These are comparison diagrams of the three-dimensional deformation models corresponding to different speed conditions.

[0067] Figure 10 This is a schematic diagram of the MQ-9 UAV simulation mesh.

[0068] Figure 11 It is a pseudo-color distribution of the pressure field.

[0069] Figure 12 It is a three-dimensional model diagram of the deformation corresponding to the preset maximum speed working condition.

[0070] Figure 13 This is a screenshot of the real-time display interface of the visualization rendering platform in manual mode.

[0071] Figure 14 This is a screenshot of the multiphysics joint interface displayed in real time by the visualization rendering platform in automatic mode after table lookup and matching.

[0072] Figure 15 It uses the PROF storage format for aerodynamic pressure field data of the full-size model.

[0073] Figure 16 It is the CSV storage format used for the scaled model deformation-velocity correlation list.

[0074] Figure 17 This is a data format example. Detailed Implementation

[0075] To further illustrate the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. The following embodiments correspond to the core steps of system construction and operation: Embodiment 1 corresponds to modeling and mesh generation; Embodiment 2 corresponds to aerodynamic-structural unidirectional coupling simulation and displacement conversion; Embodiment 3 corresponds to electromagnetic scattering simulation; Embodiment 4 corresponds to the construction of a multiphysics simulation database; and Embodiment 5 corresponds to dual-mode control, data matching, and visualization rendering. Figure 1 The overall process of the present invention is shown. In manual mode, the user inputs the speed conditions and retrieves the corresponding multiphysics data from the database for visualization. In automatic mode, the deformation of the solid model is detected by the displacement detection device, the deformation is transmitted through the communication link and the table matching is completed, and the corresponding multiphysics data is rendered synchronously.

[0076] Example 1: Model System Definition and 3D Modeling

[0077] (I) Core Correspondence of the Two-Level Model

[0078] Defining the dimensional correspondence between the simulation model and the measured model is the foundation for displacement conversion and automatic pattern matching.

[0079] 1. Simulation Model: A 1:1 scale full-size model of the real MQ-9 UAV is used as the analysis object for the aerodynamic-structural unidirectional coupling simulation;

[0080] 2. Measured model: A scaled-down model based on the full-size model, used for deformation acquisition by the displacement detection device, preferably a binocular camera displacement detection device;

[0081] 3. Scaling logic: Let the scaling factor be k. The scaling factor k is the size ratio between the full-size simulation model and the scaled-down model. It can be selected according to the spatial conditions of the actual test scene and the accuracy requirements of the equipment. In this embodiment, k=55 is preferred. The displacement conversion follows: displacement of scaled-down model = displacement of full-size model / k.

[0082] (II) SolidWorks Basic Geometric Modeling and Global Mesh Standards

[0083] A 1:1 full-size 3D model is created for the target entity. To ensure the accuracy of subsequent multiphysics simulations and cross-platform consistency, a unified mesh generation standard is defined for each downstream simulation platform:

[0084] The fluid computational mesh must be adapted to the standard k-epsilon turbulence model solution requirements of the ANSYS Fluent stage, ensuring mesh quality and reasonable boundary layer division.

[0085] The structural calculation mesh is adapted to the structural statics solution requirements of the ANSYS Mechanical stage. The ratio of mesh thickness to actual structural thickness is not less than 1:5 to avoid stress calculation distortion.

[0086] The high-frequency electromagnetic grid is adapted to the electromagnetic scattering simulation requirements of the CST stage. For the simulation frequency band of 100MHz-200MHz, the corresponding minimum wavelength is 1.5m, and the maximum size of the electromagnetic calculation grid is no more than 0.15m, that is, no more than 1 / 10 of the minimum wavelength of the working frequency band.

[0087] After each platform completes the mesh generation according to the above standards, it exports the initial 3D model file of the 1:1 full-size model. The file name can be in_speed_50.stl, so that it can be called in the subsequent simulation process and version management. Figure 10 A schematic diagram of the simulation mesh for the MQ-9 UAV is shown, in which the fluid mesh, structural mesh, and electromagnetic mesh are all divided according to the above standards to ensure the accuracy and consistency of the multiphysics simulation.

[0088] Example 2: ANSYS aerodynamic-structural one-way coupling simulation and displacement conversion

[0089] (I) Full-size model simulation process

[0090] Using the initial 3D model file of the 1:1 full-size model exported in Example 1 as the geometric basis, the fluid and structural meshes were generated and the core data was extracted in the ANSYS platform:

[0091] First, import the initial geometric model into the Mechanical module and divide the structural mesh according to the aforementioned mesh thickness ratio requirements; at the same time, generate a fluid computation mesh that meets the requirements of the k-epsilon model in the Fluid module, and set the velocity range of 50m / s to 300m / s in the Fluent solver. In this embodiment, the preferred velocity step size is 1m / s.

[0092] The fluid solution uses the standard k-epsilon turbulence model and the SIMPLE algorithm with hybrid initialization and 300 iterations per single case. Then, the aerodynamic pressure field data calculated by Fluent is extracted by a Python script and imported into the Mechanical module to solve for the Z-direction displacement of the wingtip feature points of the full-size model, denoted as Z-displacement.

[0093] Based on the scaling factor k, the Z-displacement of the full-size model is converted into the equivalent deformation variable corresponding to the scaled model, denoted as Rescaled Z-displacement. The conversion formula is as follows:

[0094]

[0095] For example, when k=55 and the full-size model Z-displacement=0.03239m, the scaled model RescaledZ-displacement=0.000589m.

[0096] Finally, the velocity values ​​and displacements corresponding to each working condition are integrated and stored in an associated file as the basis for table lookup in automatic mode. The full-size model deformation 3D model file after loading is exported according to the velocity working condition. The naming rule can be in_speed_XXX.stl, where XXX is the velocity value. Figure 3 The solution process for aerodynamic-structural unidirectional coupling is shown; Figure 9 The comparison of the deformation three-dimensional models corresponding to different speed conditions is shown.

[0097] (II) Data Format Example

[0098] 1. Full-size model aerodynamic pressure field data can be stored in PROF format, such as... Figure 15 As shown.

[0099] 2. The scaled model deformation-velocity correlation list can be implemented in CSV format, serving as the data source for lookup matching in automatic mode. Its fields may include Speed, Z-displacement, and Rescaled Z-displacement, such as... Figure 16As shown.

[0100] Example 3: CST Electromagnetic Scattering Simulation

[0101] This embodiment is based on the full-size model deformation 3D model file exported from Embodiment 2. It completes radar cross section (RCS) simulation and data processing under different flight speed conditions in the CST electromagnetic simulation platform, as detailed below:

[0102] (1) Import the corresponding three-dimensional deformation model files under different flight speed conditions into the CST electromagnetic simulation platform in sequence. During the import process, perform necessary geometric repair and topology optimization to eliminate geometric anomalies that may occur during format conversion and export, and ensure that the simulation model is geometrically complete, topologically standardized and has continuous surfaces.

[0103] (2) After the model repair is completed, high-frequency meshing is performed according to the electromagnetic mesh standard defined in Example 1; then, a solution model suitable for full-angle RCS calculation is established based on the finite-time integral method, the aircraft material properties are set as ideal conductors, the plane wave excitation direction is set along the fuselage axis, and the far-field monitor is configured as full-space coverage mode to achieve complete acquisition of scattering information in the range of azimuth angle 0°~360° and pitch angle 0°~180°.

[0104] (3) The simulation parameters for multiple operating conditions are set in batches using a script. In this embodiment, the simulation frequency is set to 150MHz, the angle scanning range is set to azimuth 0°~360° and pitch 0°~180°, the angle step is 1°, and the polarization mode is horizontal polarization. After the parameters are set, the deformation three-dimensional model corresponding to different flight speeds is solved sequentially to obtain the full-angle RCS data under each operating condition, and exported as a TXT format file. The file can contain parameters such as pitch angle, azimuth angle, RCS amplitude and RCS phase. The exported RCS data is uniformly associated and stored with the deformation three-dimensional model, pressure field data and feature point displacement under the corresponding speed operating condition to form a complete multiphysics data correspondence. Figure 4 The electromagnetic scattering simulation process is shown; Figure 7 The RCS distribution diagram for a typical operating condition in the 150MHz band is shown. Figure 8 The comparison of RCS curves under different deformation conditions is shown.

[0105] Data format example (RCS data files may contain core fields such as Theta, Phi, and Abs(RCS), such as...) Figure 17 As shown.

[0106] Figure 7 The results show that the RCS value of the aircraft's nose region is high under typical operating conditions. Figure 8The comparative results show that structural deformation under different speed conditions affects local electromagnetic scattering characteristics, thus providing a simulation basis for the mapping between structural deformation and electromagnetic scattering characteristics.

[0107] Example 4: Multiphysics Simulation Data Organization and Correlation

[0108] (a) Data storage rules

[0109] Using velocity as the core association key, a distributed storage method with a root directory and subdirectories is used to construct a multiphysics simulation database. An example storage root directory could be D: / MultiPhysics_Data / , with subdirectories categorized by data type: Deformation 3D model directory D: / MultiPhysics_Data / STL / for storing deformation 3D model files corresponding to each velocity condition; Pressure field data directory D: / MultiPhysics_Data / Pressure / for storing pressure field data files corresponding to each velocity condition; RCS data directory D: / MultiPhysics_Data / RCS / for storing RCS data files corresponding to each velocity condition; and Scaled model deformation-velocity association list directory D: / MultiPhysics_Data / Displacement / for storing a unique association list file, which could be named data_ALPHA.csv.

[0110] The naming convention is as follows: Deformation 3D model files, pressure field data files, and RCS data files are all identified by `in_speed_XXX`, where `XXX` represents the velocity value. This ensures that different types of data under the same speed condition can be associated using a unified identifier. The association list file is a single CSV file containing Z-displacement and Rescaled Z-displacement data for all speed conditions. It does not need to be split and named by velocity. Examples of specific storage paths and filenames are shown in the table below. Table 1. Examples of storage paths and filenames

[0111]

[0112] Figure 2 The process of building a multiphysics simulation database is shown, demonstrating the organization from aerodynamic-structural unidirectional coupling simulation and electromagnetic scattering simulation to unified storage of multi-condition data.

[0113] (II) Design of Classified Data Retrieval Scripts

[0114] Each script follows a unified execution logic of "path generation → file reading → data parsing → result output," and performs retrieval and processing of different types of data to adapt to data retrieval requirements in both manual and automatic modes.

[0115] 1. Script for reading deformed 3D models

[0116] For each target velocity, a corresponding deformation 3D model file path is generated. After verifying the validity of the path, the vertex and face data of the model are parsed and converted into a structured model data format adapted to the visualization rendering platform for output. In specific execution, the target velocity is first input and the file path is concatenated. After verifying the existence of the file, the ASCII format STL file is read, the vertex coordinates and face information are extracted, and finally the structured model data is output.

[0117] 2. Pressure field data reading script

[0118] The system generates a pressure field data file path based on the target velocity, parses and processes the x / y / z 3D coordinates and pressure values ​​within the file, and outputs a standardized pressure field array. Specifically, the target velocity is first input and the file path is concatenated. After verifying the file's existence, the relevant pressure field information is extracted, and the 3D coordinates and pressure values ​​are uniformly formatted and then output.

[0119] 3. RCS data reading script

[0120] The process generates an RCS data file path based on the target velocity, parses the RCS data amplitude, azimuth, and elevation angle information in the file, and converts it into a two-dimensional matrix adapted for polar coordinate display on a visualization rendering platform. In practice, the target velocity is first input and the file path is concatenated. After verifying the file's existence, the original RCS data is read, and the one-dimensional RCS values ​​are reconstructed into a two-dimensional matrix with azimuth × elevation dimensions before being output.

[0121] 4. Script for reading the variable-velocity association list of scaled model (core of automatic mode)

[0122] This script uses a full traversal reading method to parse the correspondence between all Speed ​​and Rescaled Z-displacement values ​​in the CSV file and outputs standardized correlation data. During execution, it reads the correlation list file path at a fixed time and verifies the existence of the file. After reading all rows of data, it filters out invalid rows, including records where Speed ​​or Rescaled Z-displacement is not numeric, missing values, or Speed ​​exceeds the preset valid range. Then, it sorts the data in ascending order of Speed ​​to generate a correlation list of "Speed ​​(floating-point) - Rescaled Z-displacement (floating-point)," which serves as the sole data source for reverse lookup matching in automatic mode.

[0123] (III) Reverse Matching Logic

[0124] In automatic mode, the system reads the script by calling the association list and traverses the full set of association data to complete the reverse matching of "current deformation variable of the scaled model → velocity primary key", as follows:

[0125] 1. Data Source Matching: The sole data source for the matching process is the Speed ​​and Rescaled Z-displacement correspondence list output by the associated list reading script. This list is generated by reading each line of a CSV file and then performing data cleaning, type unification, and sorting to ensure data consistency and repeatability in the reverse matching process in automatic mode.

[0126] 2. Matching Algorithm: The algorithm takes the measured deformation variable `measured_rescaled_z` of the scaled model obtained from the displacement detection equipment as the input parameter. It iterates through the preloaded association list line by line, calculates the absolute difference between `measured_rescaled_z` and each Rescaled Z-displacement value in the list, and records the difference and the corresponding velocity value. After the iteration is complete, the velocity value corresponding to the record with the smallest absolute difference is selected as the final matching result. If multiple identical minimum differences exist, the smaller velocity value is selected as the output by default to reduce matching ambiguity.

[0127] 3. Performance optimization: To reduce matching latency caused by repeated file reading, the entire associated list is preloaded into system memory at once during the automatic mode startup phase. All subsequent reverse matching is performed directly based on the memory data, without repeatedly accessing the local file system, thereby improving the response efficiency and continuous operation capability in automatic mode.

[0128] Example 5: Dual-mode control, data matching, and visualization rendering

[0129] This embodiment, through the design of manual and automatic modes, realizes two types of application requirements: rapid query for specific working conditions and synchronous mapping of entities and virtual entities. Figure 6 The data matching and visualization rendering process is shown: After receiving the velocity value or deformation, the visualization rendering platform first performs data validity verification; in manual mode, it verifies whether the input velocity is within the range supported by the database, and in automatic mode, it verifies whether the current deformation is within the preset valid threshold range; after the verification is passed, data matching and retrieval are performed, and the synchronous rendering of the deformation 3D model, the pressure field pseudo-color distribution and the RCS map are completed respectively.

[0130] In this embodiment, the preferred visualization rendering platform is Unity.

[0131] The system modules involved in this embodiment include: a database module, a mode control module, a displacement detection module, a Python communication module, a data matching module, and a visualization rendering module. Each module works together through a data interface and a communication link, consistent with the module definitions in the aforementioned system architecture block diagram.

[0132] 5.1 Manual Mode

[0133] 5.1.1 Mode Startup and Parameter Input

[0134] When the system switches to manual mode, the mode control module automatically enables the speed input box in the visual interactive interface to distinguish it from the disabled state in automatic mode. The input range is consistent with the speed operating condition range pre-stored in the database module, allowing users to directly input and modify speed values ​​and submit requests. During the input process, the system verifies the validity of parameters in real time; if the input speed exceeds the database's supported range or is a non-numeric type, the user is prompted to re-enter the value to ensure the validity of the retrieval primary key.

[0135] 5.1.2 Data Matching

[0136] After a user submits a valid speed, the data matching module does not need to go through deformation detection and table lookup matching. Instead, it directly uses the input speed as the retrieval key to retrieve the complete multiphysics data for the corresponding working condition from the database module. The data includes at least: the 3D deformation model file for the corresponding speed, pressure field data, RCS data, and feature point displacement data, thereby achieving a direct mapping from "speed key → complete working condition data".

[0137] 5.1.3 Visual Rendering

[0138] After data retrieval is complete, the visualization rendering module synchronously loads the deformation 3D model under the corresponding working condition, displaying the target structural morphology, such as... Figure 12 As shown; simultaneously, the pressure field distribution is rendered in pseudo-color, such as... Figure 11 As shown, the RCS map for the corresponding working condition is plotted; the interactive interface synchronously displays the current mode type, current speed value and related parameter information. Figure 13 The visual display interface in manual mode is shown.

[0139] 5.2 Automatic Mode

[0140] 5.2.1 Displacement Detection Module: Construction of Displacement Detection Equipment Deformation Detection System

[0141] In automatic mode, the displacement detection module performs real-time deformation detection on the scaled-down solid model. The displacement detection device is preferably a binocular camera displacement detection device. During the detection process, feature points at key locations such as the wingtips of the solid model can be identified using ArUco markers or other feature point markers, and a reference coordinate system is established under initial no-load conditions. Figure 5 The deformation detection process of the displacement detection equipment is shown.

[0142] 5.2.2 Python Communication Module: Real-time Deformation Acquisition and Data Communication

[0143] When the solid model deforms, the displacement detection module collects the current position of feature points at a preset frame rate and calculates the absolute value of the difference between the current Z-coordinate of the feature point and the Z-coordinate of the feature point in the initial unloaded state, using this as the current deformation. Subsequently, the Python communication module encodes the deformation data and sends it to the visualization rendering platform to support subsequent data matching and rendering updates in automatic mode.

[0144] 5.2.3 Data Matching Module: Reverse Table Lookup Matching

[0145] After receiving the current deformation, the visualization rendering module traverses the pre-loaded scaled model deformation-velocity association list, calculates the absolute difference between the current deformation and each deformation in the list, filters the index position corresponding to the smallest absolute difference, and extracts the corresponding velocity value as the velocity primary key. Then, using this velocity primary key, it retrieves the corresponding multiphysics data from the database module. If the association list fails to load or is empty, a preset function is called to obtain the default velocity value and subsequent data retrieval is performed to ensure continuous operation of the automatic mode process.

[0146] 5.2.4 Visualization Rendering Module: Visualization Rendering in Automatic Mode

[0147] After the data matching is completed, the visualization rendering module uses the same rendering logic as the manual mode, and synchronously loads and updates the corresponding deformation 3D model, pressure field pseudo-color distribution and RCS map; the interactive interface refreshes the current working mode, the matched velocity value, deformation, detection frame rate and current frame number and other running information in real time. Figure 14 The diagram illustrates the real-time multiphysics interface displayed by the visualization rendering platform in automatic mode after table lookup and matching. As the deformation of the ground entity model continuously changes, the system automatically executes a closed-loop process of "deformation acquisition → data communication → data matching → rendering update" to achieve synchronous mapping between the entity model and the virtual model in terms of structural morphology, pressure field distribution, and electromagnetic scattering characteristics.

[0148] 5.3 Mode Control Module: Dual-Mode Switching Mechanism

[0149] The two modes can be switched via a manual / automatic mode switch button on the visual interactive interface. This switching function is managed uniformly by the mode control module. During the switching process, the system saves the rendering state of the current mode, including the currently loaded deformed 3D model, pressure field display results, RCS map, and interface parameters; after the switch is completed, the data corresponding to the target mode is loaded in real time and the display is updated.

[0150] When the system switches from manual mode to automatic mode, the mode control module automatically disables the speed input box and initiates the communication link between the displacement detection module and the Python communication module. When the system switches from automatic mode back to manual mode, the mode control module closes the communication link and restores the speed input box to the enabled state. This design improves the continuity of state and ease of operation during mode switching.

Claims

1. A lookup-based deformation matching and electromagnetic mapping digital twin system, characterized in that, include: The database module pre-builds and stores multiphysics data with velocity as the primary key. The multiphysics data includes at least a three-dimensional deformation model, pressure field data, RCS data, and feature point displacement. The mode control module supports switching between manual and automatic modes and triggers the corresponding data matching process based on the mode type. The displacement detection module is used to detect the displacement of feature points of the scaled solid model in real time in automatic mode and calculate the current deformation. The communication module is used to realize real-time data transmission between the displacement detection module and the data matching module in automatic mode; The data matching module, in manual mode, directly retrieves the database module based on the speed input by the user. In automatic mode, it retrieves the speed primary key in reverse by using the minimum absolute difference method of the deformation-velocity association list of the scaled model based on real-time deformation detection data, and then retrieves the corresponding multiphysics data. The visualization rendering module synchronously renders the target's deformed 3D model, pressure field pseudo-color distribution, and RCS map in the visualization rendering platform based on the matching results, realizing real-time digital mapping of entity deformation to multi-physics field state.

2. The system according to claim 1, characterized in that, The database module is pre-built through the following steps: A full-size 3D solid model of the target is constructed using a 3D solid modeling tool, which serves as the initial geometric boundary. In the multiphysics simulation platform and the electromagnetic scattering simulation platform, the mesh generation that meets the requirements is completed based on the initial geometric boundary, wherein the size of the electromagnetic simulation mesh is no greater than 1 / 10 of the minimum wavelength of the working frequency band; A unidirectional coupling simulation process of aerodynamics and structure is built on a multiphysics simulation platform. Coupled simulation is performed on multiple speed conditions within a preset speed range to obtain structural deformation results under each condition and export the three-dimensional deformation model file and pressure field data. The electromagnetic scattering simulation platform uses the electromagnetic scattering simulation method to import a model file with consistent deformation and solve for the RCS data containing amplitude and phase information under the corresponding working conditions. A multiphysics simulation database with velocity as the primary key is constructed, and a scaled model deformation-velocity correlation list is built based on the displacement of feature points as a data source for automatic pattern reverse matching.

3. The system according to claim 2, characterized in that, The construction rules for the association list are as follows: extract the original displacement data of the feature points in the Z direction of the full-size model under each velocity condition from the multiphysics simulation database; determine the scaling factor between the full-size model and the scaled detection model, and convert the displacement data into the deformation of the scaled model according to the scaling factor; associate the deformation of the scaled model with the corresponding velocity to form an association list with one-to-one index position; and unify the precision of the deformation data in the list to 3 decimal places, consistent with the precision of the displacement detection module output.

4. The system according to claim 1, characterized in that, In the automatic mode, the data matching module performs the following reverse matching process: The displacement detection module receives the Z-direction displacement of the feature points of the scaled solid model in real time, and takes the absolute value of the difference between the current Z coordinate of the feature point and the Z coordinate of the feature point under the initial no-load state as the current deformation. Then, based on the preloaded association list, the minimum absolute difference method is used to traverse the list of deformations of the scaled model to determine the matching index that is closest to the current deformation. The corresponding velocity primary key is extracted through the matching index, and then the complete multiphysics data at that velocity is retrieved from the multiphysics simulation database.

5. The system according to claim 1, characterized in that, In manual mode, the user directly inputs the speed condition through the speed input box on the visual interactive interface. The system uses the input speed as the retrieval key to directly retrieve the multiphysics data of the corresponding condition from the database, without going through the deformation detection and table lookup matching process. The speed input box is enabled in this mode, while it is disabled in automatic mode.

6. A lookup-based deformation matching and electromagnetic mapping digital twin method applied to the system described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1: Pre-build a multiphysics simulation database: Obtain the deformation 3D model, pressure field data, RCS data and feature point displacement under different speed conditions through multiphysics simulation, and establish a database with velocity as the primary key. At the same time, build a correlation list of deformation and velocity of the scaled model based on the feature point displacement. Step 2: Receive the mode selection instruction and execute different data acquisition processes according to the selected mode: If it is in manual mode, the system receives the speed condition input by the user and directly retrieves the corresponding multiphysics data from the database using that speed as the primary search key. In automatic mode, the displacement detection module detects the displacement of feature points of the scaled solid model in real time and calculates the current deformation. The deformation is transmitted to the data matching module through the communication module. Based on the association list, the minimum absolute difference method is used to obtain the velocity primary key through reverse matching. Then, the corresponding multiphysics data is retrieved from the database using the velocity primary key. Step 3: Simultaneously render the multiphysics data retrieved in Step 2 in the visualization rendering module to achieve real-time digital mapping of entity deformation to multiphysics state; in manual mode, the rendering is updated in real time according to user input, and in automatic mode, Step 2 to Step 3 are executed cyclically according to the deformation detection results.

7. The method according to claim 6, characterized in that, The specific steps for pre-constructing the multiphysics simulation database in step one include: Based on the actual structural parameters, geometric features and physical properties of the target entity, a full-size 3D model of the target entity is constructed using 3D modeling tools. The model completely restores the key structure of the target and is consistent with the entity. This model is used as the initial geometric boundary. In the multiphysics simulation platform and the electromagnetic scattering simulation platform, mesh generation was completed based on the initial geometric boundary to meet the corresponding simulation requirements. The size of the electromagnetic simulation mesh was strictly controlled to be no more than 1 / 10 of the minimum wavelength of the working frequency band. Aerodynamic-structural unidirectional coupling simulation was performed on a multiphysics simulation platform to obtain three-dimensional deformation models and pressure field data under different speed conditions. Electromagnetic scattering simulation consistent with structural deformation was performed on the electromagnetic scattering simulation platform to obtain radar scattering cross section data under the corresponding working conditions. The data is organized and stored with velocity as the primary key. The Z-direction displacement of the feature points of the full-size simulation model is converted into scaled model deformations according to the scaling factor. A scaled model deformation-velocity association list is formed with the corresponding velocity value, and the association list is a two-column parallel association list. The data in the list is uniformly reserved to 3 decimal places.

8. The method according to claim 6, characterized in that, The reverse matching in automatic mode in step two specifically includes: The displacement detection module is activated to monitor the feature points of the scaled solid model in real time, collect displacement data in the Z direction, and calculate the absolute value of the difference between the current coordinate and the reference coordinate as the current actual deformation using the initial unloaded state as the reference. A low-latency communication link is established through the communication module to convert the deformation data into a character encoded string and transmit it to the data matching module. After the data matching module decodes and restores the deformation data, it traverses the preloaded scaled model deformation-velocity association list, calculates the absolute difference between the current deformation and each deformation in the list, filters the minimum difference and obtains the corresponding index, extracts the matching velocity value as the velocity primary key, and provides a retrieval basis for multiphysics data retrieval.

9. The method according to claim 6, characterized in that, The synchronous rendering of the visualization rendering module in step three includes: Load the deformed 3D model for 3D display; The pressure field distribution is rendered in pseudo-color. Draw RCS maps to cover the entire spatial angular range; The visual interactive interface simultaneously displays the current mode type, speed value, deformation, and detection frame rate; In manual mode, the speed input box is enabled, while in automatic mode, the speed input box is disabled.

10. The method according to claim 6, characterized in that, In the automatic mode, if the association list fails to load or is empty, a preset single-sample matching function is called to obtain a preset default velocity value as the velocity primary key, and the corresponding multiphysics data is retrieved from the database using this velocity primary key.

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