A method and system for 3D reconstruction and simulation of the mesoscopic electrode structure of SOFC single cells using 1DFeature edge-enhanced mesh generation.

Abstract

This invention relates to the field of SOFC battery technology, specifically a method and system for 3D reconstruction and simulation of the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh generation. The method includes discretizing and identifying multiphase materials in a realistic 3D reconstruction model of the mesoscopic electrode structure to obtain a corresponding multiphase voxel matrix image; and then using a 1D Feature edge-enhanced mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model. This invention discretizes and identifies multiphase materials in the realistic 3D reconstruction model of the mesoscopic electrode structure, ensuring accurate separation and identification of material entities and porous phases at the data level, laying a clear domain definition foundation for subsequent multiphase mesh generation. The use of 1D Feature edge-enhanced mesh generation captures the geometric boundary features of the mesoscopic electrodes, providing a basis for high-fidelity multiphysics simulations.

Description

Technical Field

[0001] This invention relates to the field of battery technology, specifically a method and system for 3D reconstruction and simulation of the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh partitioning. Background Technology

[0002] SOFCs can utilize hydrogen-rich fuels generated during oil extraction and processing without combustion, such as natural gas or low-pressure waste gas produced during crude oil extraction or refining. SOFC stands for Solid Oxide Fuel Cell, a high-efficiency energy conversion device that directly converts the chemical energy of fuels (such as hydrogen, natural gas, or biomass gas) into electrical and thermal energy through electrochemical reactions. Its core feature is the use of solid oxide ceramic electrolytes, which offer advantages such as high energy conversion efficiency and strong fuel adaptability.

[0003] The electrochemical performance and long-term operational stability of SOFCs fundamentally depend on their true, heterogeneous, and interconnected mesoscopic electrode structure. This true mesoscopic electrode structure specifically refers to the three-dimensional, interconnected, multiphase topology within the electrodes (such as the Ni-YSZ fuel electrode and the LSM-YSZ air electrode). Multiphysics simulations based on this true mesoscopic electrode structure help reveal the mesoscopic origin of battery performance, guide electrode material and structure design, optimize fabrication processes, and predict long-term performance degradation and failure mechanisms. Furthermore, it promotes the realization of "digital twin"-assisted battery design and lifetime management, possessing significant scientific research value and promising engineering applications.

[0004] SOFC, as a typical heterogeneous single cell, comprises auxiliary key components and three core functional layers: a dense electrolyte layer, a porous anode layer, and a porous cathode layer. The auxiliary key components include connectors (for connecting cells in series and distributing gas) and sealing materials (to prevent gas leakage), collectively ensuring the cell's integrity and operational reliability. In SOFC, materials determine its intrinsic physicochemical properties, while the structure directly affects the cell's macroscopic performance. The actual mesoscopic electrode structure of SOFC serves as a crucial bridge between material properties and macroscopic cell behavior, thus becoming a key research object for in-depth understanding of electrode performance through 3D reconstruction and simulation of the actual mesoscopic electrode structure of SOFC.

[0005] In the 3D reconstruction of the real mesoscopic electrode structure of SOFC, X-ray computed tomography (X-ray CT) is commonly used for reconstruction characterization. However, this method is suitable for imaging with a large field of view and low resolution (usually submicron to micron). For the fine features in SOFC electrodes, it lacks the ability to image local details. Furthermore, X-ray CT relies on the material's absorption difference of X-rays for imaging. For phases with similar atomic numbers (such as many ceramic materials) or low-density phases (such as pores), the gray-scale contrast of the image may be extremely low, making it impossible to distinguish them.

[0006] Furthermore, in existing technologies, when simulating the 3D reconstruction of the real mesoscopic electrode structure of SOFC, the existing technologies mostly use the Iso2Mesh meshing method to perform multiphase mesh generation on the 3D reconstruction results of the real mesoscopic electrode structure of SOFC. Under the same mesh quality conditions, this method often has a small number of elements, a large error in the characterization of internal geometric boundaries, and relatively limited computational accuracy. Therefore, it is more suitable for large-scale models or scenarios with high requirements for mesh generation efficiency, and is not suitable for the 3D reconstruction results of the real mesoscopic electrode structure of SOFC. Summary of the Invention

[0007] This invention provides a method and system for 3D reconstruction and simulation of the mesoscopic electrode structure of SOFC single cells by combining 1D Feature edge-enhanced mesh generation, which overcomes the shortcomings of the prior art. It can effectively solve the problem of insufficient geometric boundary capture accuracy when using Iso2Mesh meshing for multiphase mesh generation in the 3D reconstruction and simulation of the mesoscopic electrode structure of existing solid oxide fuel cells.

[0008] One of the technical solutions of this invention is achieved through the following measures: a 3D reconstruction and simulation method for the mesoscopic electrode structure of a SOFC single cell combining 1D Feature edge-enhanced mesh generation, comprising: Ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. Discretize and identify multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples to obtain the corresponding multiphase voxel matrix image. By calling the 3D Mesh Generation module in CGAL and using the 1D Feature edge enhancement mesh generation method, the multiphase voxel matrix image is divided into multiphase meshes to generate a multiphase tetrahedral mesh model.

[0009] The following are further optimizations and / or improvements to the above-mentioned technical solution: The above-mentioned 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples is discretized and multiphase material identified to obtain the corresponding multiphase voxel matrix image, including: By setting the voxel resolution, the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is discretized, and the material phase is identified for each voxel to obtain the discretized digital spatial matrix. By using a set linear combination rule, the material type of each voxel in the digital spatial matrix is ​​encoded into a different integer value, forming a multiphase voxel matrix image; Call the saveinr function to save the multiphase voxel matrix image as an .inr format file.

[0010] The aforementioned material phases include GDC, YSZ, and Ni, and the linear combination rule is AFL = G + 2 * Y + 3 * N, where G is GDC, Y is YSZ, and N is Ni.

[0011] The above-mentioned ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the true mesoscopic electrode structure of SOFC single cell samples, including: High-resolution two-dimensional cross-sectional images of SOFC single cell samples were acquired layer by layer using ion beam stripping and electron beam scanning imaging techniques, and stripping and imaging operations were performed alternately to generate a continuous two-dimensional cross-sectional sequence. ImageJ software was used to filter and register the images. The built-in code was used to reconstruct the real mesoscopic electrode structure of the SOFC single cell sample in 3D, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample.

[0012] The above also includes using the 1D Feature edge enhancement mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model, and then using the open-source toolbox Iso2Mesh to read the mesh data of the multiphase tetrahedral mesh model in the COMSOL with MATLAB interactive environment. The mesh data is then imported into the COMSOL model using built-in functions, and TPBs and DPBs are identified through a custom script. The identification results are then automatically written into the current COMSOL model, completing the import and reconstruction of the custom multiphase mesh.

[0013] The second technical solution of the present invention is achieved through the following measures: a 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell combined with 1D Feature edge enhancement mesh generation, comprising: In the initial reconstruction unit, ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. The voxel recognition unit discretizes and identifies multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples to obtain the corresponding multiphase voxel matrix image. The mesh generation unit uses the 3D Mesh Generation module in CGAL to perform multiphase mesh generation on the multiphase voxel matrix image using the 1D Feature edge enhancement mesh generation method, generating a multiphase tetrahedral mesh model.

[0014] The following are further optimizations and / or improvements to the above-mentioned technical solution: The aforementioned voxel recognition unit includes: The discrete transformation module sets the voxel resolution, discretizes the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples, and identifies the material phase of each voxel to obtain the discretized digital spatial matrix. The material type encoding module encodes the material type of each voxel in the digital spatial matrix into different integer values ​​through a set linear combination rule, forming a multiphase voxel matrix image; The output module calls the saveinr function to save the multiphase voxel matrix image as an .inr format file.

[0015] The aforementioned initial reconstruction unit includes: The sequence generation module uses ion beam stripping and electron beam scanning imaging technology to acquire high-resolution two-dimensional cross-sectional images of SOFC single cell samples layer by layer, and alternates stripping and imaging operations to generate a continuous two-dimensional cross-sectional sequence. The reconstruction module uses ImageJ software to filter and register images, and uses built-in code to perform 3D reconstruction of the real mesoscopic electrode structure of SOFC single cell samples, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples.

[0016] The above also includes a simulation unit, which uses the 1D Feature edge enhancement mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image, and generates a multiphase tetrahedral mesh model. In the COMSOL with MATLAB interactive environment, the mesh data of the multiphase tetrahedral mesh model is read through the open-source toolbox Iso2Mesh. The mesh data is imported into the COMSOL model with the help of built-in functions. A custom script is used to identify TPBs and DPBs, and the identification results are automatically written into the current COMSOL model to complete the import and reconstruction of the custom multiphase mesh.

[0017] The beneficial effects of this invention include: A customized voxel recognition method was developed to achieve digital discretization and multiphase material identification of the 3D reconstruction model of the real mesoscopic electrode structure. This ensures the accurate separation and identification of the material entity and the porous phase at the data level, laying a clear domain definition foundation for subsequent multiphase mesh generation.

[0018] By calling the CGAL library to enable 1D feature edge enhancement mesh generation technology, it can automatically identify and protect key one-dimensional geometric features (such as three-phase point lines (TPBs) and two-phase boundary lines (DPBs)). Compared with the built-in "v2m" method of Iso2Mesh, it can more accurately capture mesoscopic interfaces that affect electrochemical activity, significantly improving the geometric fidelity and computational accuracy of small-scale models.

[0019] By using the collaborative workflow of Iso2Mesh and COMSOL with MATLAB, the high-quality mesh generated by CGAL was efficiently and non-destructively imported into a commercial finite element platform. The node coordinate mapping, element index conversion and material property allocation were completed, ensuring the topological integrity and consistent inheritance of physical properties of the complex multiphase mesh, and providing a directly calculable mesh model for high-fidelity multiphysics simulation. Attached Figure Description

[0020] Appendix Figure 1 This is a schematic diagram of a 3D reconstruction and simulation method for the mesoscopic electrode structure of a SOFC single cell provided in an embodiment of the present invention.

[0021] Appendix Figure 2 This is a schematic diagram of the multiphase voxel matrix image generation method provided in an embodiment of the present invention.

[0022] Appendix Figure 3 This is a schematic diagram of a multiphase voxel matrix image provided in an embodiment of the present invention.

[0023] Appendix Figure 4 This is a schematic diagram of the process for generating a multiphase tetrahedral mesh model according to an embodiment of the present invention.

[0024] Appendix Figure 5 This is a schematic diagram comparing the mesh division results of v2m technology and 1D feature edge enhancement mesh division technology provided in the embodiments of the present invention.

[0025] Appendix Figure 6 This is a schematic diagram of a 3D reconstruction and simulation method for the mesoscopic electrode structure of another SOFC single cell provided in an embodiment of the present invention.

[0026] Appendix Figure 7 This is a schematic diagram illustrating the process of constructing a 3D reconstruction model of the real mesoscopic electrode structure of an SOFC single-cell sample provided in an embodiment of the present invention.

[0027] Appendix Figure 8 This is a schematic diagram of a 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell provided in an embodiment of the present invention.

[0028] Appendix Figure 9 This is a schematic diagram of a 3D reconstruction and simulation system for the mesoscopic electrode structure of another SOFC single cell provided in an embodiment of the present invention. Detailed Implementation

[0029] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0030] Those skilled in the art will understand that, unless specifically stated otherwise, in the embodiments of the present invention, a "module" or "unit" refers to a computer program or part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0031] In addition, in the embodiments of the present invention, "multiple" refers to two or more, and "first" and "second" are used to distinguish descriptions and should not be construed as implying relative importance.

[0032] The technical solution of the present invention will be described and explained below with reference to several examples.

[0033] Example 1: As shown in the attached document Figure 1 As shown, this invention discloses a 3D reconstruction and simulation method for the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh generation, comprising: Step S110: Using ion beam stripping and electron beam scanning imaging technology, a 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is obtained. Step S120: Discretize and identify multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample to obtain the corresponding multiphase voxel matrix image. Step S130: By calling the 3D Mesh Generation module in CGAL, the multiphase voxel matrix image is divided into multiphase meshes using the 1D Feature edge enhancement mesh division method to generate a multiphase tetrahedral mesh model.

[0034] This invention discloses a 3D reconstruction and simulation method for the mesoscopic electrode structure of SOFC single cells using 1D Feature edge-enhanced mesh generation. The method discretizes and identifies multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples, ensuring accurate separation and identification of material entities (Ni, YSZ) and porous phases at the data level. This lays a clear domain definition foundation for subsequent multiphase mesh generation. Furthermore, the 1D Feature edge-enhanced mesh generation method is used to perform multiphase mesh generation on the multiphase voxel matrix image to accurately capture the geometric boundary features of the mesoscopic electrodes. This allows for more precise capture of the mesoscopic interfaces affecting electrochemical activity, providing an accurate and effective basis for establishing a finite element model reflecting the real mesoscopic structure of SOFC cells for simulation.

[0035] Example 2: As shown in the attached document Figure 2 , 3 As shown, this embodiment of the invention is a further optimization of the above embodiment, wherein the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is discretized and multiphase material identified to obtain the corresponding multiphase voxel matrix image, including: Step S210: Set the voxel resolution, discretize the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample, and identify the material phase for each voxel to obtain the discretized digital spatial matrix. In this embodiment, the voxel resolution can be set as needed, and can be set to 39nm, but is not limited to. Then, the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is discretized based on the voxel resolution.

[0036] In this embodiment, the material phase category of the voxel may include GDC, YSZ, and Ni. The material phases are mutually exclusive in space, and a voxel cannot belong to two material phases at the same time. Therefore, for each voxel, a material phase is identified. If the voxel belongs to the material phase, the material phase is 1; otherwise, it is 0.

[0037] In this embodiment, the digital spatial matrix is ​​a three-dimensional integer matrix. If the material phase category includes GDC, YSZ, and Ni, each voxel category can be (G:GDC, Y:YSZ, N:Ni). If the voxel is GDC, the corresponding material phase identification result is (1,0,0).

[0038] Step S220: By using the set linear combination rules, the material type of each voxel in the digital spatial matrix is ​​encoded into different integer values ​​to form a multiphase voxel matrix image; In this embodiment, the linear combination rule is set according to the material phase category. If the material phase category includes GDC, YSZ, and Ni, then the linear combination rule is AFL=G+2*Y+3*N. By using the set linear combination rule, the material type of each voxel in the digitized spatial matrix is ​​encoded into a different integer value, thus completing the material domain identification of the voxel, as shown below: If the voxel is GDC, G=1, Y=0, N=0, then AFL=1; If the voxel is YSZ, G=0, Y=1, N=0, then AFL=2; If the voxel is Ni, G=0, Y=0, N=1, then AFL=3.

[0039] This step can be as follows: AFL = G + 2 * Y + 3 * N file='.AFL.inr' Furthermore, each integer value can be represented by a different color, and after forming a multiphase voxel matrix image, the output file path and name are defined and saved as an .AFL.inr format file.

[0040] Step S230: Call the saveinr function to save the multiphase voxel matrix image as an .inr format file.

[0041] This step can be as follows: saveinr(AFL,file); / / Uses the saveinr function in the Iso2mesh toolbox to save the material domain identifier matrix as a .inr file for later import into CGAL for high-quality mesh generation.

[0042] This embodiment can be executed using MATLAB. Before execution, add the Iso2mesh toolbox to the MATLAB working directory to ensure subsequent calls to the saveinr function, as shown below: addpath('.iso2mesh-1.9.6'); / / Adds the Iso2mesh toolbox to the MATLAB working directory to ensure subsequent function calls.

[0043] This embodiment sets up the voxel recognition method shown in steps S210 to S230, which realizes the digital discretization and multiphase material identification of the 3D reconstruction model of the real mesoscopic electrode structure, ensuring the accurate separation and identification of the solid phase (GDC, YSZ, Ni) and the porous phase at the data level, and laying a clear domain definition foundation for subsequent multiphase mesh generation.

[0044] Example 3: As shown in the attached document Figure 4As shown, this embodiment of the invention is a further optimization of the above embodiment. The 1DFeature edge enhancement mesh generation method is used to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model. Specifically, the 3D Mesh Generation module in CGAL is called to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model, including: Step S310: Reconstruct the multiphase voxel matrix image into a multiphase three-dimensional volume region, and introduce one-dimensional feature lines to define the mesh generation domain, as shown below: typedef CGAL::Labeled_mesh_domain_3 <k>Image_domain; / / Reconstruct a multiphase 3D volume region based on an .inr image; typedef CGAL::Mesh_domain_with_polyline_features_3<Image_domain> Mesh_domain; / / Introduces and protects critical one-dimensional feature lines to form the mesh generation domain; Image_domain transforms a multiphase voxel matrix image (each voxel has an integer label representing a different material / region) into a continuous geometric domain. CGAL reconstructs the interface (zero isosurface) between different materials through interpolation, forming a multiphase three-dimensional volume domain.

[0045] Mesh_domain_with_polyline_features_3 introduces one-dimensional feature lines on top of the image domain. These one-dimensional feature lines are forcibly retained in the final mesh to ensure the geometric accuracy of the critical path in subsequent simulations.

[0046] Step S320, store the grid generation domain, as shown below: typedef CGAL::Mesh_complex_3_in_triangulation_3C3t3; / / C3t3: stores the final 3D mesh complex structure.

[0047] Step S330: Based on the multiphase voxel matrix image, the boundary edges are automatically detected and fused with user-defined internal feature lines to construct a mesh generation domain that forcibly preserves all geometric constraints, as shown below: Mesh_domain domain=Mesh_domain::create_labeled_image_mesh_domain(image,params::features_detector=CGAL::Mesh_3::Detect_features_on_image_bbox(),params::input_features=std::cref(features_inside)) In this embodiment, user-defined internal feature lines include three-phase point lines (TPBs) and two-phase boundary lines (DPBs).

[0048] Step S340: Set the size field and mesh standard for the mesh generation domain, generate a multiphase tetrahedral mesh model, and save it as a .mesh file. The specific settings for the size field and mesh standard for the mesh generation domain are shown below: Sizing_field size(); / / Defines the field size of the grid. size.set_size(electrode_size,volume_dimension,domain.index_from_subdomain_index ()); Sets the mesh size parameters for the electrode subdomain; Mesh_criteria criteria(params::facet_angle().edge_size().facet_size(.facet_distance().ce ll_radius_edge_ratio().cell_size()); / / Sets the face angle, boundary size, face size, maximum distance between the face and the real geometry, maximum ratio of tetrahedral cell to edge length, and tetrahedral cell size; This embodiment calls the CGAL library to enable 1D feature edge enhancement mesh generation technology, as shown in the attached figure. Figure 5 As shown, compared with the built-in "v2m" method of Iso2Mesh, the multiphase tetrahedral mesh model generated by the 1D feature edge enhancement mesh generation technology shows significant advantages in terms of the smoothness of the interface edges, the regularity of the unit shape, and the overall mesh quality. Therefore, this embodiment calls the CGAL library to enable the 1D feature edge enhancement mesh generation technology, which can automatically identify and protect key one-dimensional geometric features (such as three-phase point lines (TPBs) and two-phase boundary lines (DPBs)), and can more accurately capture the mesoscopic interfaces that affect electrochemical activity, significantly improving the geometric fidelity and computational accuracy of small-scale models.

[0049] Example 4: As shown in the appendix Figure 6 As shown, this invention discloses a 3D reconstruction and simulation method for the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh generation, comprising: Step S410: Using ion beam stripping and electron beam scanning imaging technology, a 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is obtained. In this embodiment, as shown in the appendix Figure 7 As shown, this step specifically includes: High-resolution two-dimensional cross-sectional images of SOFC single cell samples were acquired layer by layer using ion beam stripping and electron beam scanning imaging (FIB-SEM) technology, and stripping and imaging operations were performed alternately to generate a continuous two-dimensional cross-sectional sequence. ImageJ software was used to filter and register the images. The built-in code was used to reconstruct the real mesoscopic electrode structure of the SOFC single cell sample in 3D, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample.

[0050] Step S420: Discretize and identify multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample to obtain the corresponding multiphase voxel matrix image. Step S430: The multiphase voxel matrix image is divided into multiphase meshes using the 1D Feature edge enhancement meshing method to generate a multiphase tetrahedral mesh model. Step S440: In the COMSOL with MATLAB interactive environment, the mesh data of the multiphase tetrahedral mesh model is read through the open-source toolbox Iso2Mesh. The mesh data is imported into the COMSOL model using built-in functions. A custom script is used to identify TPBs and DPBs, and the identification results are automatically written into the current COMSOL model, thus completing the import and reconstruction of the custom multiphase mesh.

[0051] Specifically: The "readmedit" function in the Iso2mesh tool library is called to read the .mesh file (i.e., multiphase tetrahedral mesh model) generated by CGAL, extract the mesh data, and filter out the valid volume elements with non-zero material numbers. The mesh data includes mesh nodes, elements, and surface information. Further preprocessing of the mesh data is also possible. In the COMSOL with MATLAB interactive environment, grid data can be imported into a COMSOL model using built-in functions. The main commands of these built-in functions include: mesh.data.setVertex(vertex, array) / / Sets the coordinates of the mesh vertex; mesh.data.setElem('tet',elem.array) / / Sets the connection relationship of tetrahedral elements; mesh.data.ElemEntity('tet', phase array) / / Appends an entity number (phase number) to each tetrahedral element; mesh.data.createMesh / / Encapsulates the above data into a COMSOL mesh object; The imported mesh data is statistically analyzed using the mphmeshstats function, and TPBs (three-phase boundaries) and DPBs (two-phase boundaries) are identified through a custom script. The identification results are then automatically written into the current COMSOL model. The imported mesh data includes cell statistics, quality indices, node statistics, boundary statistics, etc.

[0052] By setting up the physical field, allocating materials, and applying boundary conditions, the corresponding finite element analysis is carried out in the COMSOL environment to perform the simulation operation of the mesoscopic electrode structure of the SOFC single cell.

[0053] Step S440 in this embodiment completes the entire process from generating a custom multiphase mesh to integrating the COMSOL model, providing a foundation for conducting corresponding finite element analysis in the COMSOL environment.

[0054] Therefore, this embodiment achieves efficient and lossless import of high-quality meshes generated by CGAL into a commercial finite element platform through the collaborative workflow of Iso2Mesh and COMSOL with MATLAB. Node coordinate mapping, element index transformation (1-based to 0-based), and material property allocation were completed, ensuring the topological integrity and consistent inheritance of physical properties of the complex multiphase mesh, providing a directly computable mesh model for high-fidelity multiphysics simulations.

[0055] Example 5: As shown in the attached document Figure 8 As shown, this embodiment of the invention discloses a 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell combined with 1D Feature edge-enhanced mesh generation, comprising: In the initial reconstruction unit, ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. The voxel recognition unit discretizes and identifies multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples to obtain the corresponding multiphase voxel matrix image. The mesh generation unit uses the 3D Mesh Generation module in CGAL to perform multiphase mesh generation on the multiphase voxel matrix image using the 1D Feature edge enhancement mesh generation method, generating a multiphase tetrahedral mesh model.

[0056] The voxel recognition unit includes: The discrete transformation module sets the voxel resolution, discretizes the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples, and identifies the material phase of each voxel to obtain the discretized digital spatial matrix. The material type encoding module encodes the material type of each voxel in the digital spatial matrix into different integer values ​​through a set linear combination rule, forming a multiphase voxel matrix image; The output module calls the saveinr function to save the multiphase voxel matrix image as an .inr format file.

[0057] Example 6: As shown in the appendix Figure 9 As shown, this embodiment of the invention discloses a 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell combined with 1D Feature edge-enhanced mesh generation, comprising: The initial reconstruction unit includes: The sequence generation module uses ion beam stripping and electron beam scanning imaging technology to acquire high-resolution two-dimensional cross-sectional images of SOFC single cell samples layer by layer, and alternates stripping and imaging operations to generate a continuous two-dimensional cross-sectional sequence. The reconstruction module uses ImageJ software for image filtering and registration, and uses built-in code to perform 3D reconstruction of the real mesoscopic electrode structure of SOFC single cell samples, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. The voxel recognition unit discretizes and identifies multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples to obtain the corresponding multiphase voxel matrix image. The mesh generation unit uses the 3D Mesh Generation module in CGAL to perform multiphase mesh generation on the multiphase voxel matrix image using the 1D Feature edge enhancement mesh generation method, generating a multiphase tetrahedral mesh model. The simulation unit uses a 1D Feature edge enhancement mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model. In the COMSOL with MATLAB interactive environment, the mesh data of the multiphase tetrahedral mesh model is read through the open-source toolbox Iso2Mesh. The mesh data is imported into the COMSOL model using built-in functions. A custom script is used to identify TPBs and DPBs, and the identification results are automatically written into the current COMSOL model, completing the import and reconstruction of the custom multiphase mesh.

[0058] The above content is only a specific embodiment of the present invention, which has strong adaptability and implementation effect. However, the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention. Therefore, equivalent changes made in accordance with the claims of the present invention are still within the scope of the present invention.< / k>

Claims

1. A method for 3D reconstruction and simulation of the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh generation, characterized in that, include: Ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. Discretization and multiphase material identification were performed on the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single-cell samples to obtain the corresponding multiphase voxel matrix image, including: By setting the voxel resolution, the 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample is discretized, and the material phase is identified for each voxel to obtain the discretized digital spatial matrix. By setting linear combination rules, the material type of each voxel in the digital spatial matrix is ​​encoded into different integer values ​​to form a multiphase voxel matrix image. The material phase categories include GDC, YSZ, and Ni. The linear combination rule is AFL=G+2*Y+3*N, where G is GDC, Y is YSZ, and N is Ni. Call the saveinr function to save the multiphase voxel matrix image as an .inr format file; By calling the 3D Mesh Generation module in CGAL and employing the 1D Feature edge enhancement mesh generation method, a multiphase voxel matrix image is divided into multiphase meshes to generate a multiphase tetrahedral mesh model, including: The multiphase voxel matrix image is reconstructed into a multiphase three-dimensional volume region, and one-dimensional feature lines are introduced to define the mesh generation domain, where the one-dimensional feature lines include three-phase point lines (TPBs) and two-phase boundary lines (DPBs). Storage grid generation domain; Based on the multiphase voxel matrix image, the boundary edges are automatically detected and fused with user-defined internal feature lines to construct a mesh generation domain that forcibly preserves all geometric constraints. Set the size field and mesh criterion for the mesh generation domain, generate a multiphase tetrahedral mesh model, and save it as a .mesh file.

2. The method for 3D reconstruction and simulation of the mesoscopic electrode structure of a SOFC single cell using 1D Feature edge-enhanced mesh generation as described in claim 1, characterized in that, The method employs ion beam stripping and electron beam scanning imaging techniques to obtain a 3D reconstruction model of the true mesoscopic electrode structure of SOFC single-cell samples, including: High-resolution two-dimensional cross-sectional images of SOFC single cell samples were acquired layer by layer using ion beam stripping and electron beam scanning imaging techniques, and stripping and imaging operations were performed alternately to generate a continuous two-dimensional cross-sectional sequence. ImageJ software was used to filter and register the images. The built-in code was used to reconstruct the real mesoscopic electrode structure of the SOFC single cell sample in 3D, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of the SOFC single cell sample.

3. The method for 3D reconstruction and simulation of the mesoscopic electrode structure of a SOFC single cell based on 1D Feature edge enhancement mesh generation according to claim 1 or 2, characterized in that, It also includes using the 1D Feature edge enhancement mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image, generating a multiphase tetrahedral mesh model, and then using the open-source toolbox Iso2Mesh to read the mesh data of the multiphase tetrahedral mesh model in the COMSOL with MATLAB interactive environment. The mesh data is then imported into the COMSOL model using built-in functions, and TPBs and DPBs are identified through a custom script. The identification results are then automatically written into the current COMSOL model, completing the import and reconstruction of the custom multiphase mesh.

4. A 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell using the method described in any one of claims 1 to 3, combined with 1D Feature edge enhancement mesh generation, characterized in that, include: In the initial reconstruction unit, ion beam stripping and electron beam scanning imaging techniques were used to obtain a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples. The voxel recognition unit discretizes and identifies multiphase materials in the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples to obtain the corresponding multiphase voxel matrix image. The mesh generation unit uses the 3D Mesh Generation module in CGAL to perform multiphase mesh generation on the multiphase voxel matrix image using the 1D Feature edge enhancement mesh generation method, generating a multiphase tetrahedral mesh model.

5. The 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell based on 1D Feature edge enhancement mesh generation according to claim 4, characterized in that, The voxel recognition unit includes: The discrete transformation module sets the voxel resolution, discretizes the 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples, and identifies the material phase of each voxel to obtain the discretized digital spatial matrix. The material type encoding module encodes the material type of each voxel in the digital spatial matrix into different integer values ​​through a set linear combination rule, forming a multiphase voxel matrix image; The output module calls the saveinr function to save the multiphase voxel matrix image as an .inr format file.

6. The 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell based on 1D Feature edge enhancement mesh generation according to claim 4 or 5, characterized in that, The initial reconstruction unit includes: The sequence generation module uses ion beam stripping and electron beam scanning imaging technology to acquire high-resolution two-dimensional cross-sectional images of SOFC single cell samples layer by layer, and alternates stripping and imaging operations to generate a continuous two-dimensional cross-sectional sequence. The reconstruction module uses ImageJ software to filter and register images, and uses built-in code to perform 3D reconstruction of the real mesoscopic electrode structure of SOFC single cell samples, resulting in a 3D reconstruction model of the real mesoscopic electrode structure of SOFC single cell samples.

7. The 3D reconstruction and simulation system for the mesoscopic electrode structure of a SOFC single cell based on 1D Feature edge-enhanced mesh generation according to claim 4 or 5, characterized in that, It also includes a simulation unit that uses a 1D Feature edge enhancement mesh generation method to perform multiphase mesh generation on the multiphase voxel matrix image. After generating a multiphase tetrahedral mesh model, the mesh data of the multiphase tetrahedral mesh model is read through the open-source toolbox Iso2Mesh in the COMSOLwithMATLAB interactive environment. The mesh data is imported into the COMSOL model using built-in functions, and TPBs and DPBs are identified through a custom script. The identification results are automatically written into the current COMSOL model, completing the import and reconstruction of the custom multiphase mesh.

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