Complex component crystal plasticity finite element cross-scale modeling method based on topological decoupling
By using topological decoupling, cross-scale modeling of crystal plasticity using finite element methods was achieved, solving the problems of geometric accuracy and microstructure realism of complex components, reducing computational costs and improving modeling efficiency and accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NORTHWESTERN POLYTECHNICAL UNIV
- Filing Date
- 2026-04-01
- Publication Date
- 2026-05-15
AI Technical Summary
Existing crystal plasticity finite element methods struggle to accurately represent macroscopic geometric features and physically replicate microstructures when dealing with complex components. They also suffer from high computational costs, and commercial finite element software can easily lead to misalignment between grain IDs and material properties.
By employing a topological decoupling method, a cross-scale simulation model is generated through the decoupling mapping of macroscopic finite element meshes and microscopic voxel meshes. This avoids directly importing microstructure data, ensures a one-to-one correspondence between grain IDs and spatial locations, and achieves efficient attribute mapping.
It achieves high accuracy in geometric representation and fidelity in microstructure of complex components, reduces computational costs, avoids erroneous association between grain ID and attributes, and improves modeling efficiency and data accuracy.
Smart Images
Figure CN122050656A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computational materials technology, and in particular to a cross-scale modeling method for the plasticity of complex component crystals based on topological decoupling using the finite element method. Background Technology
[0002] Crystal Plasticity Finite Element (CPFE) is a numerical simulation technique capable of revealing microscopic deformation mechanisms such as slip and twinning in metallic materials. It has become a key tool for studying the evolution of microstructures in metallic materials during fatigue, damage, and processing. By incorporating microcrystalline information, this method can effectively establish the connection between macroscopic mechanical responses and microscopic physical mechanisms, playing a crucial role in predicting material properties in fields such as aerospace, nuclear energy equipment, and precision manufacturing.
[0003] Currently, CPFE modeling typically involves first generating representative volumetric elements (RVEs) in mainstream microstructure generation software such as Neper and Dream3D to represent the material's microstructure. These RVEs are then directly imported into commercial finite element software like Abaqus and Ansys for calculation. However, the representative volumetric elements generated by existing microstructure modeling software are mostly limited to regular cubes or cylinders, making it difficult to achieve CPFE simulation of actual components with complex geometries. Furthermore, typical engineering components are usually in the centimeter to decimeter range, while grain sizes are only in the micrometer range. If CPFE modeling is directly applied across the entire component scale, the number of finite element meshes would reach tens of billions, with computational costs far exceeding the capabilities of existing supercomputing resources. Therefore, the core challenge in applying the CPFE method to complex components lies in how to construct an effective cross-scale model that ensures both the accuracy of macroscopic and microscopic geometric features and the physical realism at the grain scale, while also maintaining computational efficiency at the component scale.
[0004] Existing cross-scale modeling methods for CPFE (Content-Cut Element Frame) are generally limited by the consistency between microstructure and macroscopic finite element mesh topology. When dealing with complex geometric features such as aero-engine blade tenons, notched specimens, and welded joints, they face the following challenges: First, to ensure the geometric accuracy of complex boundaries, macroscopic models typically require high-resolution unstructured mesh discretization, making it difficult to directly support regular voxelized microstructure data. Second, prioritizing the integrity of the microstructure often introduces significant geometric distortion in areas of complex geometric abrupt changes and near rough surfaces. Furthermore, in commercial finite element software workflows, when importing geometry containing thousands of grains, the software kernel typically renumbers the geometry and mesh. This process causes a loss of correspondence between the grain IDs in the original material crystal orientation distribution data and the IDs generated in the finite element model, leading to incorrect material orientation assignments. This necessitates manually associating the material properties and section definitions of thousands of grains, which is not only labor-intensive but also highly error-prone. These problems cause existing methods to fail in cross-scale CPFE modeling of complex components. Summary of the Invention
[0005] Therefore, it is necessary to provide a cross-scale modeling method for the crystal plasticity of complex components based on topological decoupling to address the above-mentioned technical problems. By topologically decoupling and mapping macroscopic finite element meshes and microscopic voxel meshes, the physical properties of microstructures can be embedded into the finite element model of complex components with high fidelity, ensuring both the geometric expression accuracy of complex components and the fidelity of microstructures.
[0006] This invention provides a cross-scale modeling method for the plastic finite element method of complex components based on topological decoupling, comprising the following steps: Establish the geometric model of the component to be analyzed and perform macroscopic finite element mesh generation, then export an isolated mesh file containing only node coordinates and element topology information; An RVE voxel mesh based on the microstructure source data of the component material to be analyzed is established, and the geometric centroid coordinates of each element after the macroscopic finite element mesh of the component to be analyzed are calculated. Determine the grain ID to which each geometric centroid coordinate belongs in the RVE voxel mesh, and generate a cell set mapping file containing the cell set partitioned based on the grain ID; Based on the material crystal orientation distribution data of the component to be analyzed, a rotation matrix is calculated for each grain ID, and each rotation matrix is combined with the parameters of the crystal plastic constitutive model to generate a physical property library file containing material definition and section definition. Semantic parsing and reorganization are performed on isolated mesh files. Physical property library files and element set mapping files are injected into the global domain and component domain of the isolated mesh files, respectively. Cross-sectional associations are established to generate a CPFE cross-scale simulation model of the component to be analyzed.
[0007] In one embodiment, the geometric model of the component to be analyzed is divided into macroscopic finite element meshes, and the elements are three-dimensional solid elements, and the mesh types of the elements and the microstructure data are independent of each other.
[0008] In one embodiment, a point-volume inclusion algorithm or a minimum distance algorithm is used to determine the grain ID to which each geometric centroid coordinate belongs in the material microstructure source data, and units with the same grain ID are grouped together to generate a unit set mapping file.
[0009] In one embodiment, the cross-section association is established by generating cross-section attribute statements that map the grain IDs in the unit set name and the material name based on the grain ID identifiers in the unit set mapping file and the physical property library file.
[0010] In one embodiment, the CPFE cross-scale simulation model of the component to be analyzed is in an isolated mesh format.
[0011] In one embodiment, a geometric model of the component to be analyzed is created in Abaqus and a macroscopic finite element mesh is generated.
[0012] The beneficial effects of this invention are: (1) In the construction process of the CPFE cross-scale simulation model of the present invention, the macroscopic mesh is divided by finite element software, and the microscopic RVE voxel mesh is generated independently. The elements after the macroscopic finite element mesh division do not directly contain microscopic information, but the RVE voxel mesh association is established by calculating the centroid coordinates and querying the grain ID in the RVE voxel mesh. The method of the present invention realizes the topological decoupling of the macroscopic mesh and the microscopic mesh. The generation of the macroscopic finite element mesh is not limited by the regular shape of the microscopic voxel mesh, and the generation of the microscopic voxel mesh does not need to be cut or deformed to adapt to complex boundaries, thus avoiding geometric and structural distortion.
[0013] (2) This invention automatically injects material properties by directly manipulating the text stream of the finite element input file, avoiding the operation of automatically renumbering meshes and geometries when importing geometric entities by commercial finite element software. This fundamentally ensures a strict one-to-one correspondence between grain IDs and spatial locations, eliminating the need for manual association of material properties of thousands of grains, and significantly improving modeling efficiency and data accuracy. Attached Figure Description
[0014] Figure 1 This is a flowchart illustrating a cross-scale modeling method for the crystal plasticity of complex components based on topological decoupling, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of cross-scale modeling of a target complex component with irregular holes using different types of CPFE units, as shown in another embodiment of the present invention. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0016] In one embodiment, such as Figure 1 As shown in this embodiment, the method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling includes the following steps: S101. Establish the geometric model of the component to be analyzed and perform macroscopic finite element mesh generation, then export an isolated mesh file containing only node coordinates and element topology information.
[0017] Specifically, a geometric model of the component to be analyzed is established in the general simulation software Abaqus, and macroscopic finite element mesh generation is performed.
[0018] The geometric model of the component to be analyzed is divided into macroscopic finite element meshes, and the elements are three-dimensional solid elements such as C3D8 or C3D4. The mesh types of the elements and the microstructure data are independent of each other and do not contain any material property information.
[0019] S102. Establish an RVE voxel mesh based on the source data of the microstructure of the material of the component to be analyzed, and calculate the geometric centroid coordinates of each element after the macroscopic finite element mesh of the component to be analyzed.
[0020] This embodiment completely decouples the macroscopic finite element mesh from the microscopic RVE voxel mesh. The macroscopic mesh generation is entirely generated by general-purpose simulation software, allowing the direct use of high-resolution unstructured tetrahedral or hexahedral meshes in Abaqus to accurately characterize boundary curvature and fine features without considering how to accommodate microscopic organizational data. The RVE voxel mesh is generated independently, without needing to be cut or deformed to accommodate complex boundaries. Regardless of the complexity of the macroscopic shape or the roughness of the surface, the microscopic grain data always maintains a neat hexahedral voxel structure, with grain morphology, size, and orientation distribution fully preserving the original physical properties, completely eliminating distortions introduced in geometrically abrupt regions due to prioritizing the integrity of the microstructure.
[0021] Specifically, the microscopic source data of the component material to be analyzed is voxelized into RVE (Real Value Extraction). Let the k-th element in the finite element macroscopic mesh be... The set of node coordinates is Calculate its geometric centroid. : In the formula, Represents the k-th unit The nth node, where N represents the kth unit. The total number of nodes in the system.
[0022] S103. Determine the grain ID to which each geometric centroid coordinate belongs in the RVE voxel mesh, and generate a cell set mapping file containing the cell set partitioned based on the grain ID.
[0023] In this embodiment, a centroid mapping algorithm is used. The point-volume inclusion algorithm or the minimum distance algorithm is used to determine the grain ID to which each geometric centroid coordinate belongs in the material microstructure source data. Units with the same grain ID are classified to generate a unit set mapping file.
[0024] For example, suppose the domain of i grains in the material microstructure source data is... .
[0025] Using the point-volume inclusion algorithm to determine the unit Grain The basis for judgment is: If the microscopic source data is derived from Voronoi seed points By definition, the criterion for judgment is transformed into a minimum Euclidean distance search: By traversing all macroscopic units, those with the same The units are categorized, and a unit set mapping file 'Mapped_Sets.inp' is generated.
[0026] It should be noted that the above centroid mapping algorithm is applicable regardless of whether the target mesh is sparse or dense, tetrahedral or hexahedral, thus achieving decoupling between the micro-mesh and the macro-mesh.
[0027] This embodiment calculates the geometric centroid coordinates of the macroscopic finite element unit and directly queries the grain region where the centroid point is located in the microscopic RVE voxel mesh, thereby determining the grain ID of the macroscopic unit and associating the macroscopic finite element unit with the microscopic voxel mesh. This method breaks the topological constraints between the macroscopic and microscopic meshes, achieving decoupling between them. The entire mapping process does not require complex shape function interpolation or mesh remapping; it can efficiently complete cross-scale attribute transfer solely through spatial coordinate queries, significantly simplifying the data flow process.
[0028] S104. Calculate the rotation matrix for each grain ID based on the material crystal orientation distribution data of the component to be analyzed, and combine each rotation matrix with the parameters of the crystal plastic constitutive model to generate a physical property library file containing material definitions and section definitions.
[0029] Specifically, this step involves first obtaining the first... Euler angles of individual grains Calculate the rotation matrix from the global coordinate system to the crystal's local coordinate system. : A rate-dependent crystal plastic constitutive model is used to describe the material behavior. The crystal plastic constitutive parameters and rotation matrix are written into the 'User Material' field of the 'Material.inp' file to obtain the physical property library file.
[0030] S105. Perform semantic parsing and reorganization on the isolated mesh file, inject the physical property library file and the element set mapping file into the global domain and component domain of the isolated mesh file respectively, establish cross-section association, and generate the CPFE cross-scale simulation model file of the component to be analyzed.
[0031] The establishment of cross-section association involves generating cross-section attribute statements that map the grain IDs in the element set mapping file and the physical property library file to the element set name and the grain IDs in the material name.
[0032] In this embodiment, the following Python script is specifically used to perform semantic parsing and reorganization on isolated grid files: 1. Parsing and caching: Read the physical property library file 'Material.inp', extract all 'Material' blocks and store them in buffer A; extract all 'Solid Section' blocks and store them in buffer B.
[0033] Read the unit set mapping file 'Mapped_Sets.inp' and store it in buffer C.
[0034] 2. Intelligent Injection: Read the isolated mesh file 'Component.inp'.
[0035] Anchor point 1 (Global Domain): When the keyword 'Part' is detected, insert buffer A before this line. Ensure the material is globally visible.
[0036] Anchor point 2 (Part Domain): When the 'End Part' keyword is encountered, insert buffers C and B before this line. That is, inject the set and section respectively.
[0037] 3. Automatic compensation mechanism: If buffer B is empty (i.e., no section is defined in 'Component.inp'), the script triggers automatic generation logic: iterates through the Set names (such as 'Grain_X') in buffer C and automatically generates statements: 'Solid Section, Elset=Grain_X, Material=MATERIAL-GRAIN_X'.
[0038] After the isolated mesh file has been traversed, the CPFE cross-scale simulation model of the component to be analyzed is obtained. The cross-scale simulation model file of the component to be analyzed is in isolated mesh format, which avoids the element renumbering problem that occurs when importing geometric entities in finite element preprocessing software, and ensures the spatial uniqueness of microscopic property mapping.
[0039] In a specific embodiment, such as Figure 2 As shown, a complex target component with irregular holes is modeled using CPFE across scales. The geometric model of the complex target component is built and meshed using Abaqus. To highlight the non-restrictive nature of the method in this invention regarding the type of meshing element, Figure 2 In this invention, hexahedral mesh C3D8 and tetrahedral mesh C3D4 are used to perform macroscopic finite element mesh generation on the target component, respectively. The microscopic source data of the target component's material is an RVE hexahedral voxel mesh constructed by Dream3D. After processing in steps S102-S105, such as centroid mapping and direct manipulation of the text stream of the finite element input file, both types of macroscopic meshes can generate CPFE cross-scale models of the complex target component with irregular holes, and are successfully used for simulation calculations of component deformation. It is evident that the method of this invention achieves topological decoupling between macroscopic and microscopic meshes. The element type of the macroscopic mesh does not need to consider the microscopic RVE voxel mesh. Furthermore, the mesh in the irregular hole region can accurately fit the true geometric boundary of the complex component, eliminating geometric errors caused by stepped boundaries and deformed elements. Without renumbering the geometry and mesh in general software, the method of this invention can generate effective CPFE cross-scale models using both types of macroscopic meshes, proving that the method of this invention overcomes the bottleneck of mesh topological coupling and can achieve accurate construction of CPFE models of complex components while avoiding the risk of attribute misalignment caused by renumbering in commercial software.
[0040] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.
Claims
1. A multi-scale modeling method for the plastic finite element method of complex components based on topological decoupling, characterized in that, Includes the following steps: Establish the geometric model of the component to be analyzed and perform macroscopic finite element mesh generation, then export an isolated mesh file containing only node coordinates and element topology information; An RVE voxel mesh based on the microstructure source data of the component material to be analyzed is established, and the geometric centroid coordinates of each element after the macroscopic finite element mesh of the component to be analyzed are calculated. Determine the grain ID to which each geometric centroid coordinate belongs in the RVE voxel mesh, and generate a cell set mapping file containing the cell set partitioned based on the grain ID; Based on the material crystal orientation distribution data of the component to be analyzed, a rotation matrix is calculated for each grain ID, and each rotation matrix is combined with the parameters of the crystal plastic constitutive model to generate a physical property library file containing material definition and section definition. The isolated mesh file is semantically parsed and reorganized. The physical property library file and the element set mapping file are injected into the global domain and component domain of the isolated mesh file, respectively. Cross-sectional associations are established to generate a CPFE cross-scale simulation model of the component to be analyzed.
2. The method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling according to claim 1, characterized in that, The geometric model of the component to be analyzed is divided into three-dimensional solid elements after macroscopic finite element meshing, and the elements are independent of the mesh type of the microstructure data.
3. The method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling according to claim 2, characterized in that, Using the point-volume inclusion algorithm or the minimum distance algorithm, the grain ID to which each geometric centroid coordinate belongs in the material microstructure source data is determined, and units with the same grain ID are classified to generate a unit set mapping file.
4. The method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling according to claim 3, characterized in that, Establishing cross-section association involves generating cross-section attribute statements that map the grain IDs in the element set mapping file and the physical property library file to the element set name and the grain ID in the material name.
5. The method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling according to claim 4, characterized in that, The CPFE cross-scale simulation model of the component to be analyzed is in isolated mesh format.
6. The method for cross-scale modeling of complex component crystal plasticity using finite element method based on topological decoupling according to claim 5, characterized in that, In Abaqus software, a geometric model of the component to be analyzed is created and a macroscopic finite element mesh is generated.