Reactor core fine three-dimensional grid rendering method and system and medium

Abstract

The invention discloses a rendering method and system for a fine three-dimensional grid of a reactor core and a medium. Relates to the technical field of nuclear reactor engineering software development. According to the scheme, visual models of different professional calculation result data are uniformly converted into standardized grid data in a data preprocessing link, so that a uniform data description rule is provided for geometric structures and space physics field data of multi-professional fine grids of a nuclear reactor core; space physics field data of different specialties and different structural forms are stored in a standardized mode; through a mode of combining visual grid model reconstruction and shielding elimination processing, the scale of vertex data which actually needs to be processed by software and hardware is reduced, the rendering efficiency of full-core large-scale grid data is remarkably improved, and the software use experience of designers is improved; through a method of combining spatial region decomposition and parallel rendering, the processing efficiency of existing hardware is brought into full play, and the fluency degree of reactor core fine three-dimensional grid rendering can be further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear reactor engineering software development, in particular to a reactor core fine three-dimensional grid rendering method, system and medium. BACKGROUND

[0002] Using numerical methods to simulate various physical parameters of nuclear reactors on computers can greatly reduce the cost of physical prototype simulation and shorten the development cycle of reactors. Currently, numerical simulation of reactors has become a key link in reactor design, and different research institutes and universities have developed a variety of numerical calculation software for different professions. These reactor numerical calculation software usually discretize the target object into grids, and then complete the numerical solution of each discrete unit. With the update and iteration of computer hardware and software technology, research institutes are constantly improving the grid fineness of numerical simulation in actual engineering design, thereby obtaining more accurate simulation results.

[0003] With the improvement of the fineness of the calculation grid, the scale of the result data generated by the calculation software also increases significantly. The statistical analysis capability for these calculation data is of great significance to improve the efficiency of these calculation data. In addition, it is very difficult to analyze the traditional direct text data for the irregular structure used in new reactor cores.

[0004] Core physics calculation and thermal-hydraulic analysis are highly dependent on numerical simulation of three-dimensional fine grid models. The current mainstream method generates massive three-dimensional data fields (usually up to millions of grid nodes) containing neutron flux, temperature field, burnup distribution, coolant flow field, etc. through multi-physics field coupling calculation of neutron transport equation, fluid dynamics equation, etc. However, the existing technology has the following key defects: 1. Low efficiency of data visualization and analysis, and insufficient interactivity; 2. Lack of spatial correlation analysis, and difficulty in locating local anomalies; 3. Weak multi-physics field collaborative analysis capability, lack of field coupling visualization, and insufficient time evolution analysis.

[0005] The data post-processing module of the existing core design software still remains in the two-dimensional slice era, and the designer needs to rely on experience to supplement the three-dimensional physical field distribution, which becomes a bottleneck restricting the optimization of reactor safety and economy, leading to an extended design iteration cycle (single analysis time exceeds 48 hours), and it is difficult to capture potential risks caused by complex three-dimensional effects (such as local DNB deviation from nucleate boiling caused by grid mixing). Therefore, it is urgent to develop a special analysis system that supports intelligent analysis of three-dimensional spatial data fields, to realize interactive exploration and spatial correlation quantification of core multi-physics fields. SUMMARY

[0006] The technical problem this invention aims to solve is that the post-processing modules of existing reactor core design software's two-dimensional slice data lead to extended design iteration cycles (single analysis time exceeding 48 hours) and difficulty in capturing potential risks caused by complex three-dimensional effects (such as local DNB deviation and nucleus boiling caused by grid mixing). This invention aims to provide a rendering method, system, and medium for fine three-dimensional meshes of reactor cores to support the development of three-dimensional visualization data analysis software for fine reactor meshes. This solution improves upon existing technologies by uniformly converting the visualization models of different professional calculation results into standardized mesh data during data preprocessing. This provides unified data description rules for the geometric structure and spatial physics field data of multi-professional fine meshes in nuclear reactor cores, enabling standardized storage of spatial physics field data from different professions and structural forms. By combining visualization mesh model reconstruction and occlusion removal, the scale of vertex data that the software and hardware actually need to process is reduced, significantly improving the rendering efficiency of large-scale mesh data across the entire reactor core and enhancing the software user experience for designers. Furthermore, by combining spatial region decomposition and parallel rendering, the processing power of existing hardware is fully utilized, further improving the smoothness of fine three-dimensional mesh rendering of the reactor core.

[0007] This invention is achieved through the following technical solution: This solution provides a method for rendering a fine 3D mesh of a reactor core, including: The calculation results data of the reactor core are collected, and the calculation results data are preprocessed to obtain standardized grid data; A visual grid model is reconstructed based on the standardized grid data, and an occlusion removal process is performed on the visual grid model to obtain a lightweight grid model. Vertex association attribute data is extracted from a lightweight mesh model, and the vertex association attribute data is visualized and mapped. Construct a projection view matrix, and perform spatial transformation on the visualized vertex association attribute data based on the projection view matrix to obtain the target scene; After occlusion culling of the target scene, the space is divided into multiple sub-regions. After parallel rendering of each sub-region, the sub-regions are merged to obtain the complete rendering scene.

[0008] A further optimized solution is that the preprocessing includes the following methods: Geometric mesh data and space physics field data are extracted from the calculation results; the geometric mesh data includes geometric structure data and general attribute data. Transform geometric grid data and space physics field data into standardized grid data.

[0009] A further optimized solution involves converting geometric grid data and space physics field data into standardized grid data, including the following methods: Data state, grid type, and geometric state are extracted from the calculation results to describe the general attribute data; The geometric data set and corresponding time series are extracted from the calculation results data to describe the geometric structure data; The variable array, corresponding node data, and corresponding grid data are extracted from the calculation results data to describe the space physical field data; wherein, the node data and grid data both include variable parameters and corresponding time series.

[0010] A further optimized solution involves reconstructing a visual grid model based on the standardized grid data, including the following methods: A pre-defined mesh architecture is used, and spatial registration is performed on the mesh architecture to calculate the geometric topology information of each mesh cell. The geometric topology information includes the vertex information, face information, and edge information of the mesh cell. Construct a standardized mapping between grid data and grid cells.

[0011] A further optimized solution is that the occlusion culling process includes: Obtain the surface normal vector of each mesh cell and calculate the occlusion relationship of different primitives on each mesh cell; Extract the skin surface of the visualized mesh model, and map the physical field parameters of the associated mesh cells to the skin mesh cells on the skin surface according to the occlusion relationship. The observation vector is calculated based on the camera position and mesh vertices. Invisible primitives are then removed based on the observation vector and the surface normal vector of each mesh cell.

[0012] A further optimization scheme is to perform a visualization mapping of vertex-related attribute data, including the method of mapping vertex-related attribute data into corresponding display attributes based on the meaning of different variable parameters, wherein the display attributes include transparency and color.

[0013] A further optimized solution involves constructing a projection view matrix and performing spatial transformation on the visualized vertex association attribute data based on the projection view matrix to obtain the target scene; including the following methods: The vertex-related attribute data after visualization mapping is cached in the graphics card, and a projection view matrix is ​​constructed. The method for constructing the projection view matrix includes: obtaining the real-time state of user observation, calculating the virtual camera parameters in the rendering scene based on the real-time state of user observation, wherein the virtual camera parameters include position, orientation, upward direction and field of view angle; and constructing the projection view matrix based on the virtual camera parameters. The coordinates of each vertex are transformed using the projected view matrix.

[0014] A further optimization scheme is that the method for parallel rendering of each sub-region includes: The target scenario is decomposed into multiple sub-regions according to the arrangement of fuel components, ensuring that the fuel components in different sub-regions are independent of each other; Draw the target scene background and organize it into a hierarchical structure tree. Starting from the root, construct a list of child elements for the target scene, treating each sub-region as a child element. Then, traverse and render the list of child elements for the target scene. a) Determine if the list of child elements in the current target scene is empty; if yes, end rendering; otherwise, proceed to step b. b. Determine if the number of child elements at index i is less than the number of child elements of the root node. If yes, proceed to step c; otherwise, end the rendering. c. Update the vertex information of the i-th child element and render the scene of the i-th child element, then proceed to step d. d, i = i + 1, return to step b.

[0015] This solution also provides a rendering system for a fine 3D mesh of a reactor core, used to implement the rendering method for a fine 3D mesh of a reactor core described above; the system includes: The preprocessing module is used to collect the calculation results data of the reactor core and preprocess the calculation results data to obtain standardized grid data; The reconstruction module is used to reconstruct a visual grid model based on the standardized grid data, and to perform occlusion removal processing on the visual grid model to obtain a lightweight grid model. The mapping module is used to extract vertex association attribute data from the lightweight mesh model and to visualize and map the vertex association attribute data. The view transformation module is used to construct the projection view matrix and perform spatial transformation on the vertex association attribute data after visualization mapping based on the projection view matrix to obtain the target scene; The rendering module is used to perform occlusion culling on the target scene, divide the space into multiple sub-regions, render each sub-region in parallel, and then merge the sub-regions to obtain the complete rendering scene.

[0016] This solution also provides a computer-readable medium storing a computer program that, when executed by a processor, can implement a method for rendering a fine three-dimensional mesh of a reactor core as described above.

[0017] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. This invention provides a rendering method, system, and medium for fine 3D meshes of reactor cores; used to support the development of 3D visualization data analysis software for fine reactor meshes. This solution improves upon existing technologies by uniformly converting visualization models of different professional calculation results into standardized mesh data during data preprocessing. This provides unified data description rules for the geometric structure and spatial physics field data of multi-professional fine meshes in nuclear reactor cores, enabling standardized storage of spatial physics field data from different professions and structural forms. By combining visualization mesh model reconstruction and occlusion removal, the scale of vertex data that the software and hardware actually need to process is reduced, significantly improving the rendering efficiency of large-scale mesh data across the entire reactor core and enhancing the software user experience for designers. By combining spatial region decomposition and parallel rendering, the processing power of existing hardware is fully utilized, further improving the smoothness of fine 3D mesh rendering of the reactor core.

[0018] 2. The present invention provides a rendering method, system and medium for fine three-dimensional mesh of reactor core; by combining visualization mesh model reconstruction and occlusion element culling processing, the scale of vertex data that the software and hardware actually need to process is reduced, which can significantly improve the rendering efficiency of large-scale mesh data of the entire reactor core and improve the software user experience for designers.

[0019] 3. The present invention provides a rendering method, system and medium for fine three-dimensional meshes of reactor cores; by combining spatial region decomposition and parallel rendering, the processing efficiency of existing hardware is fully utilized, which can further improve the smoothness of fine three-dimensional mesh rendering of reactor cores, realize high-performance rendering of fine three-dimensional mesh data of reactor cores, realize accurate display of fine meshes at the reactor rod grid level, improve the efficiency of reactor design simulation calculation data, and has good economic and social benefits. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A schematic diagram of the rendering process for a fine 3D mesh of a reactor core; Figure 2 A schematic diagram of the rendering process for a fine 3D mesh of a reactor core; Figure 3 A schematic diagram of standardized grid data; Figure 4This is a schematic diagram of the occlusion culling method; Figure 5 This is a schematic diagram of the parallel rendering method process; Figure 6 A schematic diagram illustrating the rendering process for a single scene character; Figure 7 This is a schematic diagram of the region decomposition parallel rendering method. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0022] The existing core design software's two-dimensional slice data post-processing module leads to extended design iteration cycles (a single analysis takes over 48 hours) and makes it difficult to capture potential risks caused by complex three-dimensional effects (such as local DNB deviation from nucleus boiling caused by grid mixing). Therefore, this solution provides the following embodiments to address the above technical problems: Example 1: This example provides a method for rendering a fine 3D mesh of a reactor core, such as... Figure 1 and Figure 2 As shown, it includes: Step 1: Collect the calculation results data of the reactor core and preprocess the calculation results data to obtain standardized grid data; in this step, the preprocessing includes the following methods: S11, extract geometric mesh data and space physical field data from the calculation result data; the geometric mesh data includes geometric structure data and general attribute data; in this scheme, the calculation result data may be generated by different professional software or come from different calculation result files. First, parse the calculation result data, filter out redundant information, and extract geometric mesh data and space physical field data to form standardized mesh data.

[0023] S12, converting geometric mesh data and space physics field data into standardized mesh data. This step specifically includes the following methods: extracting data state, mesh type, and geometric state from the calculation result data to describe the general attribute data; extracting a geometric data set and corresponding time series from the calculation result data to describe the geometric structure data; extracting a variable array, corresponding node data, and corresponding mesh data from the calculation result data to describe the space physics field data; wherein, both the node data and mesh data include variable parameters and corresponding time series; the standardized mesh data constructed in this embodiment is as follows: Figure 3As shown, the geometric data set in the geometric structure data includes labels, types, and data content; the grid data and node data in the space physics field both contain variable 1-variable 3 (in this embodiment, variable 1-variable 3 are included, but in actual applications, they are set according to the situation), and each variable has corresponding variable data and corresponding time series; the variable array in the space physics field data includes type, range, number of tuples, tuple composition, name, and data cache.

[0024] This solution transforms calculation results from different disciplines into standardized grid data during the preprocessing stage, providing a unified data description rule for the geometric structure and space physics field data of multi-discipline fine grids in nuclear reactor cores, and enabling the standardized storage of space physics field data of different disciplines and structural forms.

[0025] Step 2: Reconstruct a visual grid model based on the standardized grid data, and perform occlusion removal processing on the visual grid model to obtain a lightweight grid model; In step two, a visual grid model is reconstructed based on the standardized grid data, including the following methods: A pre-defined mesh architecture is used, and spatial registration is performed on the mesh architecture to calculate the geometric topology information of each mesh cell. The geometric topology information includes the vertex information, face information, and edge information of the mesh cell. Construct a standardized mapping between grid data and grid cells.

[0026] This embodiment generates display grid data suitable for computer graphics processing, namely a visual grid model, by processing standardized grid data through spatial location registration, occlusion removal, and grid merging. Based on the preset grid data type, the geometric topology information such as vertices, edges, and faces of each grid cell is calculated using spatial location registration rules and converted into a grid data description method suitable for computer graphics processing.

[0027] In steps two and five, as Figure 4 As shown, the methods for occlusion culling include: Obtain the surface normal vector of each mesh cell and calculate the occlusion relationship of different primitives on each mesh cell; Extract the skin surface of the visualized mesh model (the skin of the original mesh model), and map the physical field parameters of the associated mesh cells to the skin mesh cells on the skin surface according to the occlusion relationship; The observation vector is calculated based on the camera position and mesh vertices. Invisible primitives are then removed based on the observation vector and the surface normal vector of each mesh cell.

[0028] This solution significantly reduces the number of vertices that the hardware and software actually need to process by removing occluded primitives from the visualized mesh model and retaining only visible primitives, thereby improving the rendering efficiency of the visualized mesh model. It uses the normal information of the mesh cell surface to complete the occlusion relationship calculation of different primitives in the mesh cell (specifically, if there are other mesh cells in the positive direction of the normal of the mesh cell surface, it means that the current mesh cell is an internal mesh cell and will be occluded by other mesh cells). Based on this, the skin surface of the mesh model is extracted, and the physical field parameters of the associated mesh cells are mapped to the skin mesh cells, thereby obtaining a lightweight mesh model that is much smaller than the original mesh data size.

[0029] Step 3: Extract vertex-related attribute data from the lightweight mesh model and perform a visual mapping on the vertex-related attribute data. This visualization mapping includes a method where, based on the meaning of different variable parameters, the vertex-related attribute data is mapped to corresponding display attributes, including transparency and color. This method completes the data association mapping between spatial physics data and the transformed mesh cells, thereby forming data suitable for mesh data rendering.

[0030] Step four involves constructing a projection view matrix and performing spatial transformations on the visualized vertex association attribute data based on the projection view matrix to obtain the target scene. This step specifically includes the following methods: S41, cache the vertex association attribute data after visualization mapping in the graphics card, and construct a projection view matrix; the method for constructing the projection view matrix includes: obtaining the real-time state of user observation, calculating the virtual camera parameters in the rendering scene based on the real-time state of user observation (specifically, by default, the maximum bounding box of the complete scene is calculated, the camera uses the default forward direction, upward direction and field of view angle parameters, and is located outside the bounding box at a specific position that can completely observe the entire scene; for the user's mouse scrolling and dragging behavior, the changes in the camera's position, forward direction, upward direction and field of view angle are calculated in real time according to the preset response sensitivity), the virtual camera parameters include position, orientation, upward direction and field of view angle; construct the projection view matrix based on the virtual camera parameters; Specifically, this step of caching the vertex-related attribute data after visualization mapping in the graphics card includes the following methods: after considering the removal of duplicate elements, extracting the vertex coordinate data of all mesh cells, the mesh cell topology data described by the vertex number, and the mesh cell attribute data that matches the mesh cell topology data, and organizing these data into cache data suitable for graphics card processing.

[0031] S42, use the projection view matrix to perform coordinate transformation on the coordinates of each vertex.

[0032] In this solution, the visualization mapping process and spatial transformation tasks are all handled by the graphics card, making full use of the graphics processing resources of the graphics card, reducing CPU resource consumption, and improving the smoothness of the interaction of the 3D mesh rendering scene of the reactor core. Step 5: After occlusion culling of the target scene, the space is divided into multiple sub-regions. After parallel rendering of each sub-region, the sub-regions are merged to obtain the complete rendering scene.

[0033] like Figure 5 As shown, the methods for parallel rendering of each sub-region include: S51, decompose the target scene into multiple sub-regions according to the arrangement of fuel components, and ensure that the fuel components in different sub-regions are independent of each other; S52, draw the target scene background and organize it into a hierarchical structure tree. Starting from the root, construct a list of child elements for the target scene, treating each sub-region as a child element. Iterate through and render the list of child elements for the target scene. a) Determine if the list of child elements in the current target scene is empty; if yes, end rendering; otherwise, proceed to step b. b. Determine if the number of child elements at index i is less than the number of child elements of the root node. If yes, proceed to step c; otherwise, end the rendering. c. Update the vertex information of the i-th child element and render the scene of the i-th child element, then proceed to step d. d, i = i + 1, return to step b.

[0034] A complete reactor core contains dozens to hundreds of fuel assemblies. Using the method described above, the 3D rendering scene containing the complete reactor core is decomposed into several sub-regions using the mesh cells contained in the fuel assemblies. Then, parallel technology is used to render each sub-region separately. After all sub-regions are rendered, the rendering results of each sub-region are merged into a complete rendering scene, thereby achieving high-efficiency rendering of the entire reactor core's large-scale mesh.

[0035] During rendering, the rendering precision level is dynamically adjusted based on the hardware resource consumption during the rendering process. Specifically, for real-time interactive rendering, it is usually necessary to ensure that the screen updates at a rate of 20 frames per second (i.e., the rendering of one frame is completed within 50 milliseconds) to guarantee the smoothness of the interactive operation. The system automatically records the rendering time of each frame. If the rendering time exceeds 50 milliseconds, a more simplified model is automatically used to replace the previous precise model. In this way, smooth interactive operation can be ensured on computers with different hardware.

[0036] This solution manages rendering scene elements based on a core mesh data model structure tree. It dynamically adjusts the rendering precision level of the entire core mesh data according to current hardware resource consumption. Spatially, the physical field is decomposed into regions, and a parallel rendering method is employed to achieve smooth rendering of the entire core's fine-grained mesh at the rod grid level. The solution organizes the complete rendering scene into a hierarchical structure tree. The root node represents the entire core rendering scene, storing the coarsest-grained mesh unit set obtained by merging and simplifying fine-grained mesh units from all fuel assemblies. It also contains fine-grained mesh units organized in the form of fuel assemblies, with fuel assembly containers storing various levels of fine-grained mesh unit sets. The rendering process uses this multi-level model data storage structure with different levels of fineness, refining it level by level from the root, and dynamically adjusting the rendering precision level based on hardware resource consumption.

[0037] Example 2: This example provides a rendering system for a fine 3D mesh of a reactor core, used to implement the rendering method for a fine 3D mesh of a reactor core described in Example 1; the system includes: The preprocessing module is used to collect the calculation results data of the reactor core and preprocess the calculation results data to obtain standardized grid data; The reconstruction module is used to reconstruct a visual grid model based on the standardized grid data, and to perform occlusion removal processing on the visual grid model to obtain a lightweight grid model. The mapping module is used to extract vertex association attribute data from the lightweight mesh model and to visualize and map the vertex association attribute data. The view transformation module is used to construct the projection view matrix and perform spatial transformation on the vertex association attribute data after visualization mapping based on the projection view matrix to obtain the target scene; The rendering module is used to perform occlusion culling on the target scene, divide the space into multiple sub-regions, render each sub-region in parallel, and then merge the sub-regions to obtain the complete rendering scene.

[0038] Example 3: This example provides a computer-readable medium storing a computer program, which, when executed by a processor, can implement a method for rendering a fine three-dimensional mesh of a reactor core as described in Example 1; specifically, the following steps are performed: Step 1: Collect the calculation results data of the reactor core and preprocess the calculation results data to obtain standardized grid data; Step 2: Reconstruct a visual grid model based on the standardized grid data, and perform occlusion removal processing on the visual grid model to obtain a lightweight grid model; Step 3: Extract vertex association attribute data from the lightweight mesh model and visualize and map the vertex association attribute data. Step 4: Construct the projection view matrix, and perform spatial transformation on the visualized vertex association attribute data based on the projection view matrix to obtain the target scene; Step five involves performing occlusion culling on the target scene, then dividing the space into multiple sub-regions. These sub-regions are rendered in parallel, and finally merged to obtain the complete rendered scene. This embodiment renders a single scene character; the specific process is as follows: Figure 6 First, vertex cache data is built in the graphics card. With the vertex cache data already built, a projection view transformation matrix is ​​constructed. Based on this matrix, the vertex coordinates are transformed, and primitive clipping and culling are performed. Figure 7 As shown, during rendering, the entire core background is decomposed into regions according to the fuel components, each sub-region is rendered in parallel, and then the rendering results are merged to draw the scene background. Finally, a projection view transformation is performed to map the rendered image onto the screen space.

[0039] This solution develops a rendering and display system for fine 3D meshes of reactor cores in the field of numerical computation and analysis of nuclear reactors. Based on a combination of standardized mesh data description format, occlusion culling processing and parallel rendering, it improves the processing capability of large-scale mesh data of reactor cores and enhances the rendering and display efficiency of fine 3D mesh data of reactor cores.

[0040] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for rendering a fine three-dimensional mesh of a reactor core, characterized in that, include: The calculation results data of the reactor core are collected, and the calculation results data are preprocessed to obtain standardized grid data; A visual grid model is reconstructed based on the standardized grid data, and an occlusion removal process is performed on the visual grid model to obtain a lightweight grid model. Vertex association attribute data is extracted from a lightweight mesh model, and the vertex association attribute data is visualized and mapped. Construct a projection view matrix, and perform spatial transformation on the visualized vertex association attribute data based on the projection view matrix to obtain the target scene; After occlusion culling of the target scene, the space is divided into multiple sub-regions. After parallel rendering of each sub-region, the sub-regions are merged to obtain the complete rendering scene.

2. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 1, characterized in that, The preprocessing includes the following methods: Extract geometric mesh data and space physics field data from the calculation results; The geometric mesh data includes geometric structure data and general attribute data; Transform geometric grid data and space physics field data into standardized grid data.

3. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 2, characterized in that, The method for converting geometric grid data and space physics field data into standardized grid data includes: Data state, grid type, and geometric state are extracted from the calculation results to describe the general attribute data; The geometric data set and corresponding time series are extracted from the calculation results data to describe the geometric structure data; The variable array, corresponding node data, and corresponding grid data are extracted from the calculation results data to describe the space physical field data; wherein, the node data and grid data both include variable parameters and corresponding time series.

4. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 1, characterized in that, The method for reconstructing a visual grid model based on the standardized grid data includes: A pre-defined mesh architecture is established, and spatial registration is performed on the mesh architecture to calculate the geometric topology information of each mesh cell. The geometric topology information includes vertex information, face information, and edge information of the mesh cells; Construct a standardized mapping between grid data and grid cells.

5. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 4, characterized in that, The method for occlusion removal includes: Obtain the surface normal vector of each mesh cell and calculate the occlusion relationship of different primitives on each mesh cell; Extract the skin surface of the visualized mesh model, and map the physical field parameters of the associated mesh cells to the skin mesh cells on the skin surface according to the occlusion relationship. The observation vector is calculated based on the camera position and mesh vertices. Invisible primitives are then removed based on the observation vector and the surface normal vector of each mesh cell.

6. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 3, characterized in that, The visualization mapping of vertex-related attribute data includes: Method: Based on the meaning of different variable parameters, vertex-related attribute data is mapped to corresponding display attributes, including transparency and color.

7. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 1, characterized in that, The projected view matrix is ​​constructed, and the target scene is obtained by spatial transformation of the vertex association attribute data after visualization mapping based on the projected view matrix. Including methods: Cache the vertex-related attribute data after visualization mapping in the graphics card and construct the projection view matrix; The method for constructing the projection view matrix includes: acquiring the real-time state of user observation; calculating virtual camera parameters in the rendering scene based on the real-time state of user observation, wherein the virtual camera parameters include position, orientation, upward direction, and field of view angle; and constructing a projection view matrix based on the virtual camera parameters. The coordinates of each vertex are transformed using the projected view matrix.

8. The rendering method for a fine three-dimensional mesh of a reactor core according to claim 1, characterized in that, The method for parallel rendering of each sub-region includes: The target scenario is decomposed into multiple sub-regions according to the arrangement of fuel components, ensuring that the fuel components in different sub-regions are independent of each other; Draw the target scene background and organize it into a hierarchical structure tree. Starting from the root, construct a list of child elements for the target scene, treating each sub-region as a child element. Then, traverse and render the list of child elements for the target scene. a) Determine if the list of child elements in the current target scene is empty; if yes, end rendering; otherwise, proceed to step b. b. Determine if the number of child elements at index i is less than the number of child elements of the root node. If yes, proceed to step c; otherwise, end the rendering. c. Update the vertex information of the i-th child element and render the scene of the i-th child element, then proceed to step d. d, i = i + 1, return to step b.

9. A rendering system for a fine three-dimensional mesh of a reactor core, characterized in that, A rendering method for implementing a fine three-dimensional mesh of a reactor core as described in any one of claims 1-8; the system comprises: The preprocessing module is used to collect the calculation results data of the reactor core and preprocess the calculation results data to obtain standardized grid data; The reconstruction module is used to reconstruct a visual grid model based on the standardized grid data, and to perform occlusion removal processing on the visual grid model to obtain a lightweight grid model. The mapping module is used to extract vertex association attribute data from the lightweight mesh model and to visualize and map the vertex association attribute data. The view transformation module is used to construct the projection view matrix and perform spatial transformation on the vertex association attribute data after visualization mapping based on the projection view matrix to obtain the target scene; The rendering module is used to perform occlusion culling on the target scene, divide the space into multiple sub-regions, render each sub-region in parallel, and then merge the sub-regions to obtain the complete rendering scene.

10. A computer-readable medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, can implement a method for rendering a fine three-dimensional mesh of a reactor core as described in any one of claims 1-8.

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