Differential field data generation method and device and electronic equipment

Abstract

The invention provides a difference field data generation method and device and electronic equipment, and belongs to the technical field of simulation. The method comprises the steps that heterogeneous data from M simulation sources are received, a space coordinate system is established based on the heterogeneous data of the M simulation sources, M is a positive integer, the heterogeneous data of the M simulation sources are converted based on the space coordinate system, M sets of simulation data are generated, the simulation data comprise at least one physical quantity, and M is a positive integer; and selecting at least two groups of simulation data from the M groups of simulation data as comparison objects, determining a physical quantity difference value of the comparison objects on at least one physical quantity, and generating difference field data. In this way, the problems that in the prior art, data alignment seriously depends on artificial experience, strict unification of space coordinates and physical quantity units is difficult to guarantee, generated difference field data errors are large, meanwhile, due to fragmentation of the comparison process, analysis efficiency is low, observation view angles are not consistent, and data alignment accuracy is poor can be solved. And the accurate judgment on the spatial difference is influenced.

Description

Technical Field

[0001] This application relates to the field of simulation technology, and in particular to a method, apparatus and electronic device for generating difference field data. Background Technology

[0002] In the field of computational simulation engineering, such as computational fluid dynamics, structural mechanics, and electromagnetic simulation, in order to verify the accuracy of simulation models, evaluate the consistency of calculation results from different simulation software, or compare and verify with physical experimental data, it is often necessary to conduct comparative analysis of simulation data from multiple sources (i.e., multi-source heterogeneous simulation data) to generate difference field data, thereby evaluating the deviation between simulation results and benchmarks or experiments.

[0003] In related technologies, existing methods for generating difference field data mainly rely on manual processing. This involves importing data from different sources into different windows, manually adjusting the views to approximate alignment, and then generating difference field data through qualitative or local quantitative comparisons using side-by-side static cloud map screenshots or by extracting finite cross-sectional curves and discrete point values. However, this method heavily relies on human experience for data alignment, making it difficult to ensure strict consistency between spatial coordinates and physical quantity units. This results in significant errors in the generated difference field data. Furthermore, the fragmented comparison process leads to low analytical efficiency and inconsistent observation perspectives, affecting the accurate judgment of spatial differences. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, and electronic device for generating difference field data, to solve the technical problems of existing technologies that rely heavily on human experience during data alignment, making it difficult to ensure strict consistency between spatial coordinates and physical quantity units, resulting in large errors in the generated difference field data. Furthermore, the fragmented comparison process leads to low analysis efficiency and inconsistent observation perspectives, affecting the accurate judgment of spatial differences. The specific technical solution is as follows: In a first aspect of this application, a method for generating difference field data is provided, the method comprising: Receive heterogeneous data from M simulation sources, and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer; Based on the spatial coordinate system, the heterogeneous data of the M simulation sources are transformed to generate M sets of simulation data, each set of simulation data containing at least one physical quantity. Select at least two sets of simulation data from the M sets as comparison objects; Determine the physical quantity difference of the comparison object in at least one physical quantity, and generate difference field data.

[0005] In an optional implementation, establishing a spatial coordinate system based on the heterogeneous data of the M simulation sources includes: Receive user selection instructions; Based on the user selection instructions, baseline simulation data is determined from the heterogeneous data of the M simulation sources; The spatial coordinate system is established based on the coordinates and mesh structure corresponding to the benchmark simulation data.

[0006] In an optional implementation, the step of transforming the heterogeneous data of the M simulation sources based on the spatial coordinate system to generate M sets of simulation data includes: Based on a predefined coordinate transformation matrix, the heterogeneous data of the M simulation sources are transformed to the spatial coordinate system to generate M sets of simulation data; And / or, According to the preset unit conversion rules, the physical quantities in the heterogeneous data of the M simulation sources are converted to a unified unit of measurement to generate M sets of simulation data. And / or, Adaptive mesh resampling is performed on the simulation data that is inconsistent with the reference mesh in the spatial coordinate system to generate M sets of simulation data.

[0007] In an optional implementation, selecting at least two sets of simulation data from the M sets of simulation data as comparison objects includes: Receive user differential analysis commands; Based on the user difference analysis command and / or preset matching rules, at least two sets of simulation data are selected from the M sets of simulation data as the comparison objects.

[0008] In an optional implementation, determining the physical quantity difference between the comparison objects in at least one physical quantity and generating difference field data includes: For any of the physical quantities, parameters of at least two sets of simulation data in the comparison object are read node by node or cell by cell center; According to the preset difference rule, the difference between the parameters of at least two sets of simulation data in the comparison object is determined, and the difference field data is generated.

[0009] In an optional implementation, before reading the parameters of at least two sets of simulation data in the comparison object node-by-node or cell-by-cell center for any of the physical quantities, the following is included: Determine whether at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system; If at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system, the step of reading the parameters of at least two sets of simulation data in the comparison object node by node or cell center for any physical quantity is performed.

[0010] In an optional implementation, the method further includes: Create M windows, each window being used to display a set of the simulation data; A viewpoint synchronization mechanism is created, which is used to synchronize the viewpoints of other windows when a viewpoint change operation is performed in any of the windows.

[0011] In an optional implementation, after generating the difference field data, the following steps are included: The difference field data is rendered into a three-dimensional cloud map, and the three-dimensional cloud map and the comparison object are synchronously displayed in the same spatial perspective through the perspective synchronization linkage mechanism.

[0012] In a second aspect of this application, an apparatus for generating difference field data is also provided, the apparatus comprising: A coordinate system establishment module is used to receive heterogeneous data from M simulation sources and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer; The simulation data generation module is used to transform the heterogeneous data of M simulation sources based on the spatial coordinate system to generate M sets of simulation data, wherein the simulation data contains at least one physical quantity. The comparison object selection module is used to select at least two sets of simulation data from the M sets of simulation data as comparison objects; The difference field data generation module is used to determine the difference in physical quantities of the comparison objects in at least one physical quantity, and generate difference field data.

[0013] In a third aspect of the embodiments of this application, an electronic device is also provided, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method for generating difference field data as described in any of the first aspects above.

[0014] In a fourth aspect of the embodiments of this application, a storage medium is also provided, wherein the storage medium stores instructions that, when run on a computer, cause the computer to execute the method for generating difference field data as described in any of the first aspects above.

[0015] In a fifth aspect of the embodiments of this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the method for generating difference field data as described in any of the first aspects above.

[0016] The technical solution provided in this application receives heterogeneous data from M simulation sources and establishes a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer. Based on the spatial coordinate system, the heterogeneous data from the M simulation sources is transformed to generate M sets of simulation data. Each set of simulation data contains at least one physical quantity. At least two sets of simulation data are selected from the M sets as comparison objects, and the difference in physical quantities of the comparison objects in at least one physical quantity is determined to generate difference field data. By establishing a spatial coordinate system based on the heterogeneous data from M simulation sources to transform the heterogeneous data and generate M sets of simulation data, the import, transformation, and difference comparison of heterogeneous data from multiple simulation sources can be realized. This solves the technical problems of existing technologies, which heavily rely on manual experience for data alignment, making it difficult to ensure strict consistency between spatial coordinates and physical quantity units, resulting in large errors in the generated difference field data. Furthermore, the fragmented comparison process leads to low analysis efficiency and inconsistent observation perspectives, affecting the accurate judgment of spatial differences. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0020] Figure 1 A schematic diagram illustrating the implementation process of a method for generating difference field data provided in this application embodiment; Figure 2 A schematic diagram illustrating the implementation process of another method for generating difference field data provided in this application embodiment; Figure 3 A schematic diagram illustrating the implementation process of another method for generating difference field data provided in this application embodiment; Figure 4 A schematic diagram of the structure of a difference field data generation system provided in an embodiment of this application; Figure 5 A schematic diagram of a device for generating difference field data provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0023] To address the technical problems in existing technologies where data alignment heavily relies on human experience, making it difficult to ensure strict consistency between spatial coordinates and physical quantity units, resulting in large errors in the generated difference field data, and where fragmented comparison processes lead to low analysis efficiency and inconsistent observation perspectives, affecting the accurate judgment of spatial differences, this application provides a method, apparatus, and electronic device for generating difference field data. The method receives heterogeneous data from M simulation sources and establishes a spatial coordinate system (M being a positive integer) based on this data. Using this spatial coordinate system, the heterogeneous data from the M simulation sources is transformed to generate M sets of simulation data, each containing at least one physical quantity. At least two sets of simulation data are selected from these M sets as comparison objects, and the difference in physical quantities between the comparison objects is determined, generating the difference field data. This method, establishing a spatial coordinate system based on the heterogeneous data from M simulation sources to transform and generate M sets of simulation data, enables the import, transformation, and difference comparison of heterogeneous data from multiple simulation sources.

[0024] like Figure 1 The diagram shown illustrates the implementation flow of a method for generating difference field data according to an embodiment of this application, which may specifically include the following steps: S101 receives heterogeneous data from M simulation sources and establishes a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer.

[0025] In this embodiment, heterogeneous data from M simulation sources are received, and a spatial coordinate system is established based on the heterogeneous data from the M simulation sources, where M is a positive integer (e.g., M is 1, 2, 3, etc.). Here, simulation source refers to the software, algorithm, or experimental testing system that generates simulation data, such as CFD software, FEA solvers, electromagnetic simulation tools, or physical experiment data acquisition equipment. Heterogeneous data refers to simulation result data from different simulation sources that differ in data format, mesh type, spatial coordinate system, physical quantity units, or storage structure. The spatial coordinate system refers to a reference three-dimensional coordinate system established to unify the spatial reference of multi-source data. Its origin, axes, and scale can be determined based on reference data or user-specified rules, and it is used to map all simulation data to the same spatial frame for alignment and comparison.

[0026] S102, based on the spatial coordinate system, transforms the heterogeneous data of M simulation sources to generate M sets of simulation data, each containing at least one physical quantity.

[0027] In this embodiment, based on a spatial coordinate system, heterogeneous data from M simulation sources are transformed to generate M sets of simulation data, each containing at least one physical quantity. The simulation data refers to a structured data set that has undergone standardization processes such as coordinate unification, unit normalization, and mesh alignment, possessing a consistent coordinate reference, physical quantity units, and mesh topology, allowing for direct numerical comparison and visualization. The physical quantity refers to the field variables to be analyzed contained in the simulation data, such as flow velocity, pressure, temperature, stress, displacement, and electric potential, which can be in scalar, vector, or tensor form; this embodiment does not limit the specific form.

[0028] S103, Select at least two sets of simulation data from the M sets of simulation data as comparison objects.

[0029] In this embodiment, at least two sets of simulation data are selected from M sets of simulation data as comparison objects. The comparison objects are the simulation datasets to be compared, selected according to user-specified or preset matching rules.

[0030] S104, determine the physical quantity difference of the comparison object in at least one physical quantity, and generate difference field data.

[0031] In this embodiment, the physical quantity difference between the comparison objects in at least one physical quantity is determined, and difference field data is generated. The physical quantity difference refers to the difference in physical quantities between at least two sets of simulation data in the comparison objects. The difference field data is a structured dataset that records the spatial distribution of the physical quantity difference.

[0032] Based on the above description of the technical solution provided in the embodiments of this application, heterogeneous data from M simulation sources are received, and a spatial coordinate system is established based on the heterogeneous data from the M simulation sources, where M is a positive integer. Based on the spatial coordinate system, the heterogeneous data from the M simulation sources are transformed to generate M sets of simulation data. Each set of simulation data contains at least one physical quantity. At least two sets of simulation data are selected from the M sets of simulation data as comparison objects, and the difference in physical quantities of the comparison objects in at least one physical quantity is determined to generate difference field data. By establishing a spatial coordinate system based on the heterogeneous data from M simulation sources to transform the heterogeneous data from the M simulation sources and generate M sets of simulation data, the import, transformation, and difference comparison of heterogeneous data from multiple simulation sources can be realized. This solves the technical problems of existing technologies, which heavily rely on manual experience during data alignment, making it difficult to ensure strict consistency between spatial coordinates and physical quantity units, resulting in large errors in the generated difference field data. Furthermore, the fragmented comparison process leads to low analysis efficiency and inconsistent observation perspectives, affecting the accurate judgment of spatial differences.

[0033] like Figure 2 The diagram shown illustrates the implementation flow of another method for generating difference field data provided in this application, which may specifically include the following: S201 receives heterogeneous data from M simulation sources, where M is a positive integer.

[0034] In this embodiment of the application, this step is similar to step S101 above, and will not be described in detail here.

[0035] S202, Receive user selection instructions.

[0036] In this embodiment of the application, a user selection instruction is received. The user selection instruction is an instruction issued by the user through a graphical interface, command line, or configuration file to specify the reference data for establishing a spatial coordinate system. Specifically, the user's selection, dragging, or specified operation on a data object in a list can be received as the user selection instruction.

[0037] S203 determines the baseline simulation data from the heterogeneous data of M simulation sources based on user-selected instructions.

[0038] In this embodiment, benchmark simulation data is determined from heterogeneous data from M simulation sources based on user selection instructions. The benchmark simulation data serves as a reference for spatial alignment and difference calculation. Specifically, the identifier of the specific simulation source selected by the user can be obtained by parsing the user selection instructions, thereby determining the heterogeneous data corresponding to that data source as the benchmark simulation data.

[0039] S204 establishes a spatial coordinate system based on the coordinates and mesh structure corresponding to the baseline simulation data.

[0040] In this embodiment, a spatial coordinate system is established based on the coordinates and mesh structure corresponding to the benchmark simulation data. Specifically, the spatial origin, coordinate axis directions, scale, and spatial topological relationships of mesh nodes / cells defined in the benchmark simulation data can be extracted to construct a unified spatial coordinate system. This embodiment does not limit this aspect.

[0041] S205, based on a spatial coordinate system, transforms heterogeneous data from M simulation sources to generate M sets of simulation data, each containing at least one physical quantity.

[0042] In this embodiment of the application, based on a spatial coordinate system, the heterogeneous data of M simulation sources are transformed to generate M sets of simulation data, each containing at least one physical quantity.

[0043] Specifically, based on a spatial coordinate system, the heterogeneous data from M simulation sources are transformed to generate M sets of simulation data, which may include: Based on a predefined coordinate transformation matrix, the heterogeneous data from M simulation sources are transformed into a spatial coordinate system to generate M sets of simulation data. And / or, According to the preset unit conversion rules, the physical quantities in the heterogeneous data of M simulation sources are converted to a unified unit of measurement to generate M sets of simulation data. And / or, Adaptive mesh resampling is performed on simulation data that is inconsistent with the reference mesh in the spatial coordinate system to generate M sets of simulation data.

[0044] In this embodiment, the predefined coordinate transformation matrix is ​​a homogeneous transformation matrix defined based on the spatial relationship (such as rotation, translation, and scaling) between the reference coordinate system and the local coordinate systems of each heterogeneous data, used to map the heterogeneous data to a unified spatial framework. The predefined spatial transformation rules are predefined physical quantity unit conversion rules, used to ensure the comparability of all physical quantities. Adaptive mesh resampling is an interpolation algorithm that interpolates physical quantity values ​​on non-reference meshes to the nodes or cell centers of the reference mesh, thus solving the problem of inconsistent mesh resolution or topology between different simulation sources. This embodiment does not limit this aspect.

[0045] S206, Receive user difference analysis command.

[0046] In this embodiment, a user difference analysis command is received. This user difference analysis command is a user-initiated command used to start difference calculation and comparison analysis. The user difference analysis command may include parameters such as the type of physical quantity to be compared, the selection of the comparison data group, and the difference calculation method (e.g., absolute difference, relative error). This embodiment does not limit these parameters.

[0047] S207, based on the user's difference analysis command and / or preset matching rules, select at least two sets of simulation data from the M sets of simulation data as comparison objects.

[0048] In this embodiment, at least two sets of simulation data are selected as comparison objects from M sets of simulation data based on user difference analysis instructions and / or preset matching rules. The user difference analysis instruction specifies the identifier of the data set to be compared. The preset matching rules are logic that automatically pairs comparison groups based on metadata such as data labels, simulation conditions, and physical quantity names. For example, data whose names contain "Baseline" are automatically paired with data whose names contain "Test".

[0049] S208, determine the physical quantity difference of the comparison object in at least one physical quantity, and generate difference field data.

[0050] In this embodiment of the application, this step is similar to step S104 above, and will not be described in detail here.

[0051] like Figure 3 The diagram shown illustrates the implementation flow of another method for generating difference field data provided in this application, which may specifically include the following: S301 receives heterogeneous data from M simulation sources and establishes a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer.

[0052] In this embodiment of the application, this step is similar to step S101 above, and will not be described in detail here.

[0053] S302, based on a spatial coordinate system, transforms heterogeneous data from M simulation sources to generate M sets of simulation data, each containing at least one physical quantity.

[0054] In this embodiment of the application, this step is similar to step S102 above, and will not be described in detail here.

[0055] S303: Select at least two sets of simulation data from the M sets of simulation data as comparison objects.

[0056] In this embodiment of the application, this step is similar to step S103 above, and will not be described in detail here.

[0057] S304: For any physical quantity, read the parameters of at least two sets of simulation data from the comparison object node by node or cell center.

[0058] In the embodiments of this application, for any physical quantity, the parameters of at least two sets of simulation data in the comparison object are read node by node or cell by cell center. Specifically, each grid node or cell center in the spatial coordinate system can be traversed, and the value of the same physical quantity at that location can be read from at least two sets of simulation data in the comparison object.

[0059] S305, according to the preset difference rule, determine the difference in parameters of at least two sets of simulation data in the comparison object, and generate difference field data.

[0060] In this embodiment of the application, the difference between parameters of at least two sets of simulation data in the comparison object is determined according to a preset difference rule, and difference field data is generated. The preset difference rule includes, but is not limited to, calculation methods such as absolute difference, relative error, percentage error, and normalized difference.

[0061] Before reading the parameters of at least two sets of simulation data from the comparison object node by node or cell center for any physical quantity, it is also necessary to ensure that the simulation data has been meshed in the spatial coordinate system. This can specifically include the following steps: Step 51: Determine whether at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system.

[0062] In this embodiment of the application, it is determined whether at least two sets of simulation data in the comparison objects have been meshed in the spatial coordinate system. Mesh alignment means that the data of all comparison objects have been mapped to the same set of spatial mesh topology, that is, each mesh node or cell corresponds strictly in spatial position.

[0063] Step 52: If at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system, perform the step of reading the parameters of at least two sets of simulation data in the comparison object node by node or cell center for any physical quantity.

[0064] In this embodiment of the application, when at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system, the step of reading the parameters of at least two sets of simulation data in the comparison object node by node or cell center for any physical quantity is performed. That is, step S305.

[0065] In another embodiment of this application, if at least two sets of simulation data in the comparison object are not meshed in the spatial coordinate system, a mesh resampling or interpolation process is triggered until the alignment condition is met.

[0066] S306, create M windows, each window is used to display a set of simulation data.

[0067] In this embodiment, M windows are created, each window displaying a set of simulation data. Each window independently loads and renders a set of simulation data, including cloud plots, isosurfaces, or vector fields, providing users with data preview and preliminary comparison capabilities.

[0068] S307, Create a view synchronization mechanism. This mechanism is used to synchronize the view of other windows when a view is changed in any window.

[0069] In this embodiment, a viewpoint synchronization mechanism is created. This mechanism ensures that when a viewpoint transformation operation is performed in any viewpoint window, the viewpoints of the other viewpoints are updated synchronously. The transformation operation can include rotation, translation, scaling, etc. Specifically, this can be achieved by sharing camera parameters, listening to interactive events, and broadcasting the transformation matrix, ensuring that all viewpoints maintain the same viewing orientation and scaling ratio.

[0070] For example, if a user rotates the model in window A, the viewpoints of windows B and C will automatically follow the rotation, maintaining visual consistency across multiple windows and facilitating visual comparison for the user.

[0071] After generating the difference field data, it may also include: rendering the difference field data into a 3D cloud map, and displaying the 3D cloud map and the comparison object synchronously from the same spatial perspective through a viewpoint synchronization linkage mechanism.

[0072] Furthermore, in this application embodiment, the method for generating difference field data provided in this application embodiment is described with reference to specific examples: like Figure 4 The diagram shown is a structural schematic of a difference field data generation system provided in an embodiment of this application, which may specifically include the following: The data preprocessing module, serving as a unified data abstraction layer, defines a common internal data model and parsing interface for various simulation formats such as VTK, CGNS, and HDF5. This achieves a high degree of decoupling between parsing logic and business processing. It receives data files from different simulation software or experimental acquisition systems, with file formats including VTK, CGNS, HDF5, and CSV. A unified data description interface is used to parse, convert, and normalize data files in different formats. During the conversion process, a unified spatial coordinate system can be established, and grid resampling and physical quantity unit matching can be performed, ensuring that data from different sources can be directly compared in spatial location and numerical dimensions. Specifically, parsers for specific formats can be dynamically loaded through a factory pattern. Coordinate unification is achieved by applying a fourth-order transformation matrix, while physical quantity unit matching relies on a pre-defined SI conversion table. This fundamentally shields the heterogeneity of data sources. When a new data source format is input, only a new parser needs to be implemented and registered with the factory; no modification to any business logic is required, greatly improving the system's maintainability and scalability.

[0073] The multi-source data unified management module is a format fusion and data scheduling center based on a unified data abstraction layer. It is used to receive and store standardized data processed by the data preprocessing module, and to unify the internal format of the data and associate metadata.

[0074] The physical quantity difference calculation and rendering module automatically calculates the physical quantity differences between corresponding nodes or cells after data alignment. For example, it employs a strategy combining octree-based spatial indexing and trilinear interpolation, reading values ​​from data source A and data source B node by node or cell by cell center, and performing calculations according to preset rules (e.g., difference = AB). For data with inconsistent meshes, a three-dimensional spatial interpolation algorithm based on volume cell centers can be used for matching to ensure spatial consistency in the difference calculation. The calculated difference field can be added to the rendering pipeline as a new scalar field and displayed as a cloud map using pseudo-color mapping, making the error distribution spatially visible.

[0075] Specifically, this can include index construction: using the spatial bounding box of the reference grid as the root node, recursively dividing it into eight equal parts until the number of grid cells in the leaf nodes falls below a set threshold. Point localization and interpolation: for each query point in the simulation data, the octree is traversed starting from the root node to quickly locate its leaf node. Subsequently, among all candidate cells contained in that node, the specific hexahedral cell containing it is precisely located using the ray intersection method. Finally, trilinear interpolation is performed using the physical quantity values ​​of the eight vertices of that cell to calculate the matching reference value. Compared to traditional nearest neighbor interpolation, this algorithm can significantly improve the accuracy and smoothness of the difference field, and can more realistically reflect the continuous characteristics of the physical field.

[0076] The intelligent filter combination module provides various filter types, such as contour lines, iso-sections, streamlines, sections, tangents, and vectors. Users can select different filter types through the interface. It can also maintain a filter dependency graph, enabling automatic result updates and cascading responses. For example, when a user moves the slice plane, the associated streamline distribution and difference cloud map are automatically refreshed, achieving consistent and interconnected analysis of differing regions from multiple perspectives and scales, thus improving the depth and efficiency of the analysis.

[0077] The multi-window visualization and linkage module is used to create multiple visualization windows, each corresponding to a set of simulation data or difference fields. Each window contains an independent rendering pipeline. The multi-window visualization and linkage module achieves synchronized viewpoint linkage between multiple windows by sharing unified camera parameters and an interactive event listening mechanism. When the user performs rotation, scaling, or panning operations in any window, the camera matrix change parameters can be captured and broadcast to other windows in real time through the viewpoint synchronization module, achieving multi-window viewpoint linkage.

[0078] Specifically, the multi-viewport visualization and linkage module can employ a frame synchronization strategy with anti-shake features. It samples high-frequency mouse movement events and sets a de-shake window of approximately 50 milliseconds, capturing only the final camera state after the operation has stabilized. The de-shakeed camera state parameters (position, focus, up direction vector) are appended with a high-precision timestamp and are not immediately broadcast. Instead, they wait for the vertical synchronization signal of the next graphics rendering cycle. When this signal is triggered, the latest camera state is broadcast to all slave windows at once.

[0079] By establishing a real-time interactive synchronization mechanism between multiple visualization windows, automatic linkage of viewpoints (zoom, rotation, translation) can be achieved. When a user adjusts the view in any window, other windows automatically maintain the same spatial observation angle, thereby achieving consistency in the comparison of multi-source simulation data. It can support the synchronous display of simulation data from different sources (different grids, coordinate systems, or unit systems) under a unified reference system.

[0080] The difference field calculated from "simulation results - baseline data (or experimental data)" is used as a new physical quantity for 3D visualization. The difference cloud map can automatically adjust the color band range, outlier threshold, and transparency mapping to achieve an intuitive display of the spatial distribution of errors. It supports difference calculation and rendering for various data formats, including point clouds, structured meshes, and unstructured meshes.

[0081] The quantitative indicator generation and reporting module is used to determine global and local quantitative indicators (such as mean error, root mean square error, mean absolute error, correlation coefficient, coefficient of determination, standardized root mean square error, etc.) based on preset or user-defined formulas. It integrates all results, charts, and statistical summaries, automatically generating standardized analysis reports saved in PDF, WORD, and other formats for export. Specifically, it can automatically generate a multi-dimensional indicator system including mean error, root mean square error, mean absolute error, coefficient of determination, and correlation coefficient, based on the input simulation data type and engineering scenario. Adaptive indicator templates can be defined according to industry needs, enabling automatic evaluation for different engineering fields (such as fluid mechanics, structural mechanics, thermal analysis, etc.). Finally, it generates a standardized simulation evaluation report, including data visualization results, statistical indicators, and automatic conclusion judgments.

[0082] Corresponding to the above method embodiments, this application also provides an apparatus for generating difference field data, such as... Figure 5 As shown, the device may include a coordinate system establishment module 501, a simulation data generation module 502, a comparison object selection module 503, and a difference field data generation module 504.

[0083] The coordinate system establishment module 501 is used to receive heterogeneous data from M simulation sources and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer. The simulation data generation module 502 is used to transform the heterogeneous data of M simulation sources based on a spatial coordinate system to generate M sets of simulation data, each containing at least one physical quantity. The comparison object selection module 503 is used to select at least two sets of simulation data from M sets of simulation data as comparison objects; The difference field data generation module 504 is used to determine the difference in physical quantities of the comparison objects in at least one physical quantity and generate difference field data.

[0084] This application also provides an electronic device, such as... Figure 6 As shown, it includes a processor 601, a communication interface 602, a memory 603, and a communication bus 604, wherein the processor 601, the communication interface 602, and the memory 603 communicate with each other through the communication bus 604. Memory 603 is used to store computer programs; In one embodiment of this application, when the processor 601 executes a program stored in the memory 603, it performs the following steps: Receive heterogeneous data from M simulation sources and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer; transform the heterogeneous data from the M simulation sources based on the spatial coordinate system to generate M sets of simulation data, each containing at least one physical quantity; select at least two sets of simulation data from the M sets of simulation data as comparison objects; determine the difference in physical quantities of the comparison objects in at least one physical quantity, and generate difference field data.

[0085] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0086] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0087] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0088] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0089] In another embodiment provided in this application, a storage medium is also provided, which stores instructions that, when run on a computer, cause the computer to execute the method for generating difference field data as described in any of the above embodiments.

[0090] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the method for generating difference field data as described in any of the above embodiments.

[0091] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a storage medium or transmitted from one storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0092] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0093] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0094] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the protection scope of this application.

Claims

1. A method for generating difference field data, characterized in that, The method includes: Receive heterogeneous data from M simulation sources, and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer; Based on the spatial coordinate system, the heterogeneous data of the M simulation sources are transformed to generate M sets of simulation data, each set of simulation data containing at least one physical quantity. Select at least two sets of simulation data from the M sets as comparison objects; Determine the physical quantity difference of the comparison object in at least one physical quantity, and generate difference field data.

2. The method according to claim 1, characterized in that, The establishment of a spatial coordinate system based on heterogeneous data from the M simulation sources includes: Receive user selection instructions; Based on the user selection instructions, baseline simulation data is determined from the heterogeneous data of the M simulation sources; The spatial coordinate system is established based on the coordinates and mesh structure corresponding to the benchmark simulation data.

3. The method according to claim 1, characterized in that, Based on the spatial coordinate system, the heterogeneous data of the M simulation sources are transformed to generate M sets of simulation data, including: Based on a predefined coordinate transformation matrix, the heterogeneous data of the M simulation sources are transformed to the spatial coordinate system to generate M sets of simulation data; And / or, According to the preset unit conversion rules, the physical quantities in the heterogeneous data of the M simulation sources are converted to a unified unit of measurement to generate M sets of simulation data. And / or, Adaptive mesh resampling is performed on the simulation data that is inconsistent with the reference mesh in the spatial coordinate system to generate M sets of simulation data.

4. The method according to claim 1, characterized in that, The step of selecting at least two sets of simulation data from the M sets of simulation data as comparison objects includes: Receive user differential analysis commands; Based on the user difference analysis command and / or preset matching rules, at least two sets of simulation data are selected from the M sets of simulation data as the comparison objects.

5. The method according to claim 1, characterized in that, Determining the difference in physical quantities of the comparison objects in at least one physical quantity, and generating difference field data, includes: For any of the physical quantities, parameters of at least two sets of simulation data in the comparison object are read node by node or cell by cell center; According to the preset difference rule, the difference between the parameters of at least two sets of simulation data in the comparison object is determined, and the difference field data is generated.

6. The method according to claim 5, characterized in that, Before reading the parameters of at least two sets of simulation data in the comparison object node by node or cell center for any of the physical quantities, the process includes: Determine whether at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system; If at least two sets of simulation data in the comparison object have been meshed in the spatial coordinate system, the step of reading the parameters of at least two sets of simulation data in the comparison object node by node or cell center for any physical quantity is performed.

7. The method according to claim 1, characterized in that, The method further includes: Create M windows, each window being used to display a set of the simulation data; A viewpoint synchronization mechanism is created, which is used to synchronize the viewpoints of other windows when a viewpoint change operation is performed in any of the windows.

8. The method according to claim 7, characterized in that, After generating the difference field data, the following is included: The difference field data is rendered into a three-dimensional cloud map, and the three-dimensional cloud map and the comparison object are synchronously displayed in the same spatial perspective through the perspective synchronization linkage mechanism.

9. A device for generating difference field data, characterized in that, The device includes: A coordinate system establishment module is used to receive heterogeneous data from M simulation sources and establish a spatial coordinate system based on the heterogeneous data from the M simulation sources, where M is a positive integer; The simulation data generation module is used to transform the heterogeneous data of M simulation sources based on the spatial coordinate system to generate M sets of simulation data, wherein the simulation data contains at least one physical quantity. The comparison object selection module is used to select at least two sets of simulation data from the M sets of simulation data as comparison objects; The difference field data generation module is used to determine the difference in physical quantities of the comparison objects in at least one physical quantity, and generate difference field data.

10. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method described in any one of claims 1-8.

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