Heterogeneous bim model cae pre-processing conversion method based on civil structure semantic understanding

Abstract

The application discloses a heterogeneous BIM model CAE pretreatment conversion method based on civil structure semantic understanding, and belongs to the field of computer-aided engineering, and the method comprises the following steps: analyzing a heterogeneous BIM file, and extracting geometric topology and component attributes; intelligently identifying and labeling civil structure component semantics based on geometric features, BIM attributes and topological relations; performing geometric dimension reduction, detail elimination and topological optimization on the identified components, and constructing a CAE intermediate model with enhanced structure semantics; and finally automatically mapping and loading the required attributes for CAE analysis, and outputting an analysis model file that can be recognized by a target CAE analysis software. The method provided by the application can significantly improve the automation level and efficiency of BIM-CAE collaboration, effectively solve the problems of BIM data heterogeneity, semantic mismatch and geometric redundancy, and provide key technical support for the digital transformation of civil engineering.

Description

Technical Field

[0001] This invention belongs to the field of Computer Aided Engineering (CAE), and more specifically, relates to a CAE preprocessing conversion method for heterogeneous BIM models based on semantic understanding of civil structures. Background Technology

[0002] The civil engineering industry is currently accelerating its digital and information-based development, and Building Information Modeling (BIM) technology has become a core tool for project construction lifecycle management. BIM models, such as RVT and DGN format files generated by mainstream BIM software like Autodesk Revit and Bentley OpenBuildings Designer, as well as the industry-standard IFC format files defined by the International Organization for Standardization (ISO) 16739-1, carry richer three-dimensional geometric information, component attributes, and potential semantics compared to traditional CAD models.

[0003] However, directly applying these BIM model data to computer-aided analysis (CAE) in structural engineering faces numerous challenges and technical bottlenecks:

[0004] 1. Currently, most BIM-CAE interface tools on the market focus on geometric data export or simple attribute mapping. However, critical aspects such as component identification, geometric simplification, structural semantic loading, and topology optimization still rely heavily on manual intervention and operation. This approach is time-consuming, labor-intensive, inefficient, and prone to human error, becoming a major bottleneck in the BIM-CAE workflow.

[0005] 2. In order to meet the needs of visualization, rendering and detailing, BIM models often contain a large number of fine geometric details that are unrelated to structural mechanics analysis, such as chamfers, openings, grooves, decorative components, pipe wiring holes, and unnecessary local patches. This results in a huge analysis model size and high geometric complexity. Directly performing finite element meshing will generate a massive number of mesh elements, reduce computational efficiency, and even cause meshing failure.

[0006] 3. During the modeling process, BIM models may produce minor geometric gaps, overlaps, patch damage, non-manifold geometry, or inaccurate component connections due to modeling habits, software accuracy, or improper export. For example, there may be tiny gaps or overlaps between beams and columns. These defects are fatal in CAE preprocessing and can lead to mesh generation failure, abnormal mechanical transfer, or distorted analysis results.

[0007] 4. Different BIM software programs exhibit significant differences in data structure, component classification, attribute definition, and semantic expression. For example, Revit's family component system and IFC's IfcRoot derived class system have different emphases in granularity and inheritance relationships, making it difficult for different formats to interoperate seamlessly and efficiently.

[0008] 5. The component semantics contained in the original BIM model mainly serve architectural design, visualization, or construction purposes, such as "building walls," "decorative surfaces," and "furniture." CAE analysis, however, requires explicit structural functional semantics such as "load-bearing shear walls," "frame beams," "truss components," and "floor slab units," which typically need to be simplified to one-dimensional "beams / columns," two-dimensional "slabs / walls," or zero-dimensional "nodes" analysis units. This semantic gap is the biggest obstacle to BIM-CAE collaboration.

[0009] Therefore, there is an urgent need for a method that can intelligently understand the semantics of civil structures in BIM models and automatically complete model simplification, optimization and transformation, so as to bridge the gap between BIM and CAE and improve the efficiency and quality of structural engineering design and analysis. Summary of the Invention

[0010] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a CAE preprocessing conversion method for heterogeneous BIM models based on semantic understanding of civil structures. This solves the problems of BIM data heterogeneity, semantic mismatch, geometric redundancy, topological defects, and low automation in the conversion process from BIM models to CAE analysis models in existing technologies.

[0011] To achieve the above objectives, according to a first aspect of the present invention, a method for CAE preprocessing and conversion of heterogeneous BIM models based on semantic understanding of civil structures is provided, comprising:

[0012] S100: Extract the 3D topology information, geometric parameters, parametric attributes, spatial relationships, connection relationships, and nesting relationships between all components in the BIM model file to be converted and store them in the Unified Data Model (UDM).

[0013] The UDM adopts an object-oriented data structure and has the following attributes: storing the three-dimensional topological information, geometric parameters, and spatial, connection, and nesting relationships between each component; each component has an attribute dictionary or list to store the parameterized attributes of the component; each component has predefined fields to store the civil structure semantics of the component; and it has a mapping from component ID to UDM object, as well as an index of topological and logical relationships between UDM objects.

[0014] S200: Calculate the dimensions of each component in the UDM to determine its geometric shape. If its geometric shape is linear, extract its cross-sectional profile along the minor axis. If its geometric shape is planar, extract its thickness information. Extract the spatial information of each component. Determine whether each component is a non-structural component based on its parametric attributes. If so, delete it from the UDM; otherwise, treat it as a potential structural component. Delete potential structural components that have no mechanical connection or interaction with the civil structure from the UDM. For the remaining potential structural components, determine their component type based on their spatial information and spatial, connection, and nesting relationships with other potential structural components, combined with knowledge of civil engineering, and save them to the corresponding predefined fields.

[0015] S300 performs geometric dimensionality reduction, detail removal, geometric tolerance elimination, automatic topology optimization, and connection repair on each component in the UDM after S200 processing.

[0016] S400 stores all component entities and their civil structure semantics after being processed by S300 into the CAE intermediate model;

[0017] The CAE intermediate model adopts a hierarchical data structure and is used to store the cross-sectional shape, size parameters, material properties, local coordinate system and release conditions of each linear component; the thickness, material properties, element type and local coordinate system of each surface component; and the load type and boundary condition type of each component.

[0018] S500 converts intermediate CAE models into a format recognizable by the target CAE software.

[0019] According to a second aspect of the present invention, an electronic device is provided, comprising: a computer-readable storage medium and a processor;

[0020] The computer-readable storage medium is used to store executable instructions;

[0021] The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in the first aspect.

[0022] According to a third aspect of the invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to perform the method as described in the first aspect.

[0023] According to a fourth aspect of the invention, a computer program product is provided, comprising a computer program or instructions that, when executed by a processor, implement the method described in the first aspect.

[0024] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0025] The method provided by this invention offers a unified parsing and processing mechanism for mainstream BIM formats such as RVT, DGN, and IFC, achieving efficient and reliable interoperability of structural CAE data across different BIM software platforms and breaking down data silos. It ensures the accuracy and reliability of the analysis model: based on precise understanding of civil structural semantics, it ensures that the CAE analysis model meets the stringent requirements of structural mechanics analysis in terms of geometry, topology, component type, and material properties. Refined geometric simplification and topology optimization effectively address redundant details and geometric defects in the original BIM model, thus avoiding calculation failures or result distortions caused by errors in the analysis model. Through comprehensive structural semantic understanding and automated geometric processing, it minimizes the manual intervention required for converting traditional BIM models to CAE analysis models, significantly overcoming the automation bottleneck of the BIM-CAE workflow. Experimental verification shows that the conversion efficiency of the method provided by this invention is more than 50% higher than existing methods. It eliminates tedious and time-consuming tasks such as manual geometry cleanup, component type judgment, and manual attribute input, allowing engineers to devote more valuable energy to structural scheme optimization and analysis result interpretation, thereby improving design quality and efficiency. It can adapt to the specific needs of different projects and modeling habits, and is easy to update and expand to support new BIM standards or CAE software. It provides key technical support for the seamless data flow of BIM models in the design, analysis, construction and even operation and maintenance phases, which is conducive to promoting the digital transformation and intelligent development of the civil engineering industry. Attached Figure Description

[0026] Figure 1 The flowchart illustrates the CAE preprocessing and conversion method for heterogeneous BIM models based on semantic understanding of civil structures, as provided in this embodiment of the invention.

[0027] Figure 2 A flowchart illustrating the heterogeneous BIM data parsing and unified data model construction provided in this embodiment of the invention.

[0028] Figure 3 A flowchart illustrating the BIM model geometric simplification and CAE analysis model creation process provided in this embodiment of the invention.

[0029] Figure 4 This is a simplified flowchart of a linear component provided in an embodiment of the present invention.

[0030] Figure 5 This is a simplified flowchart of a surface component provided in an embodiment of the present invention.

[0031] Figure 6 This is a schematic diagram of the component detail removal process provided in an embodiment of the present invention.

[0032] Figure 7 This is a schematic diagram illustrating the process of component geometry tolerance removal, automatic topology optimization, and connection repair provided in an embodiment of the present invention.

[0033] Figure 8 A schematic diagram of a CAE intermediate model for structural semantic enhancement provided in an embodiment of the present invention.

[0034] Figure 9 This is a schematic diagram of the CAE attribute preloading and interface output process provided in an embodiment of the present invention. Detailed Implementation

[0035] 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. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0036] This invention provides a method for CAE preprocessing and conversion of heterogeneous BIM models based on semantic understanding of civil structures, including:

[0037] S100: Extract the 3D topology information, parametric attributes, spatial relationships, connection relationships, and nesting relationships of all components in the BIM model file to be converted and store them in the Unified Data Model (UDM).

[0038] The UDM adopts an object-oriented data structure with the following attributes: storing the three-dimensional topology information of each component; each component has an attribute dictionary or list to store the parameterized attributes of the component; each component has predefined fields to store the civil structure semantics of the component; and it has a mapping from component ID to UDM object, as well as an index of topological and logical relationships between UDM objects.

[0039] In step S1, the heterogeneous BIM data parsing and the construction of the unified data model are completed, such as... Figure 2 As shown, it specifically includes:

[0040] S101, First, the user selects the BIM model file to be converted; preferably, the BIM model file to be converted is any one or more of the following: Revit RVT format, Bentley MicroStation or OpenBuildings Designer DGN format, or IFC format; then, depending on the file type, the corresponding software development kit (SDK) or application programming interface (API) is called, such as Autodesk Revit API for RVT, Bentley MicroStation SDK, or OpenBuildingsSDK for DGN, or an open-source / commercial IFC parsing library, such as IfcOpenShell for IFC, is used to read the BIM model file data.

[0041] S102, comprehensively extract the original data from the BIM model file to be converted, including:

[0042] (1) Extract the three-dimensional topological information (such as vertices, edges, faces, solids) and their geometric parameters (such as coordinates, normals, curve / surface equations, dimensions) of all components;

[0043] (2) Extract various parametric attributes of the component, such as Category / IfcClass, Family / Type, Name, Length, Width, Height, Thickness, Material Name, StructureRole, Material_FEA, Level, and Unique GlobalID / ElementId.

[0044] (3) Extract the spatial relationships, connection relationships, and nesting relationships between components, such as the holes contained in the components, as well as information related to the attributes of the elements, such as line width and color.

[0045] S103 normalizes and maps heterogeneous data extracted from different BIM formats into an internally defined, BIM semantically enhanced unified data model (UDM). This UDM adopts an object-oriented data structure and has the following attributes:

[0046] (1) It can contain a precise mathematical description of the component geometry in the reconfigurable original BIM model file (i.e., it can store the three-dimensional topological information and geometric parameters of each component).

[0047] (2) It can assign an attribute dictionary or list to each component object and store its original BIM attributes (i.e., it can store the parametric attributes of the components in the original BIM model file).

[0048] (3) It can predefine fields in each component object for subsequent storage and association of the identified civil structure semantics, including at least: StructureRole (component function), FE_Type (component type), and Material_FEA (component material properties); wherein, StructureRole and Material_FEA (component material properties) are directly loaded from the constructed BIM properties, and FE_Type is identified by the subsequent step S200.

[0049] (4) It can establish a mapping from component ID to UDM object, as well as an index of topological and logical relationships between UDM objects, so as to efficiently query and traverse.

[0050] S200: Calculate the dimensions of each component in the UDM to determine its geometric shape. If its geometric shape is linear, extract its cross-sectional profile along the minor axis. If its geometric shape is planar, extract its thickness information. Extract the spatial information of each component. Determine whether each component is a non-structural component based on its parametric attributes. If so, delete it from the UDM; otherwise, treat it as a potential structural component. Delete potential structural components that have no mechanical connection or interaction with the civil structure from the UDM. For the remaining potential structural components (i.e., effective structural components), determine their component type based on their spatial information and spatial, connection, and nesting relationships with other potential structural components, combined with knowledge of civil engineering, and save them to the corresponding predefined fields.

[0051] In step S200, geometric feature analysis is performed on the component geometric data in the unified data model to determine the preliminary shape of the component; BIM attribute-structural semantic mapping is performed on the component attribute information in the unified data model to obtain preliminary structural semantic clues of the component; based on the geometric feature analysis results of the component, the BIM attribute-structural semantic mapping results, and combined with the topological connection relationship between components and the context environment, the civil structure components related to structural analysis are identified and screened through intelligent reasoning of rule engine and domain knowledge base, and their precise civil structure semantics are labeled.

[0052] In step S200, the identification and semantic mapping of civil structural components are completed. This step is the core of the present invention, which aims to intelligently identify components related to structural analysis from the complex information extracted from UDM and assign them accurate civil structural semantics.

[0053] Step S200 specifically includes:

[0054] S201, Perform preliminary geometric feature analysis on all solid components in the UDM, including:

[0055] (1) Calculate the axial bounding box AABB of the component to obtain the overall length, width and height of the component;

[0056] (2) Based on the dimensions of the component, determine whether the geometric shape of the component is more linear (slenderness ratio greater than the threshold), surface (e.g., thickness much smaller than length and width), or volumetric (if the geometric shape of the component is neither linear nor surface, then its geometric shape is considered to be volumetric).

[0057] (3) For linear components (such as beams and columns), extract their cross-sectional profiles along their minor axis; for surface components (such as slabs and walls), extract their thickness information.

[0058] (4) Analyze the global spatial location (i.e., spatial information) of the component, such as whether it is in a certain floor plan, and whether its orientation is horizontal or vertical, and save it.

[0059] S202, combining the original BIM attribute information (i.e., parametric attributes) of the components in the UDM, preliminary structural semantic filtering and mapping are performed through the following strategies:

[0060] The system matches text attributes such as "name," "category," and "family type" of components. For example, components whose names contain keywords such as "beam," "column," "slab," "wall-structure," "foundation," or "footing" are prioritized as potential structural components. Meanwhile, components containing keywords such as "door," "window," "furniture," "pipe," or "decoration" are marked as non-structural components and removed from the UDM.

[0061] For IFC format, the component type is primarily determined by its IfcRoot derived classes, such as IfcBeam, IfcColumn, IfcSlab, and IfcWallStandardCase. For Revit format, the component type is determined using its built-in Categories, such as "Structural Frame," "Structural Column," "Floor Slab," and "Wall," as well as the BuiltInParameter property.

[0062] In addition, users can configure personalized mapping rules, such as specifying that a particular Revit family name or IFC ObjectType should be recognized as a certain structural component type.

[0063] S203, combining the preliminary identification results of S201 and S202, utilizes the topological relationships between components (i.e., spatial relationships, connection relationships, and nesting relationships between components) and spatial layout (i.e., spatial information) to perform multi-level reasoning, in order to improve the accuracy of identification and compensate for the shortcomings of a single information source:

[0064] (1) Analyze whether there are shared edges, shared surfaces or geometric contacts between the components. For example, a vertical slender member supporting a floor slab or roof is more likely to be a structural column; a horizontal slender member connecting columns is more likely to be a beam.

[0065] (2) Identify the inclusion relationship between openings, such as holes, and boards or walls to better reconstruct components and prevent these openings from being lost. For example, record what openings are in the board or wall.

[0066] (3) Introduce a knowledge base in the field of civil engineering, which includes typical connection modes and force transmission paths of structural components such as beams, columns, slabs, walls, and foundations. For example, if a component is located between multiple "structural columns" or "structural beams" and its size is appropriate, it can be further identified as a "floor slab".

[0067] (4) Identify components that have no mechanical connection or function with the civil structure according to their category as non-structural components and remove them from the UDM. Such as lightweight partition walls, ceilings, floor surfaces, etc., which are only used for separation.

[0068] S204, integrating all the above identification and reasoning results, assigns precise civil structural semantics to the identified valid structural components. The civil structural semantics of a component includes its StructureRole (component function), FE_Type (component type), and Material_FEA (component material properties). Component classifications (i.e., component types) may include, but are not limited to: frame beams, frame columns, shear walls, floor slabs, foundation beams, isolated foundations, pile caps, pile foundations, etc. Each structural component possesses explicit StructureRole and Material_FEA attributes mapped from BIM properties.

[0069] S300 performs geometric dimensionality reduction, detail removal, geometric tolerance elimination, automatic topology optimization, and connection repair on each component in the UDM after S200 processing.

[0070] The geometric dimensionality reduction process includes:

[0071] For linear components, they are abstracted as one-dimensional line elements, and these one-dimensional line elements carry the cross-sectional and material properties of the linear components; wherein, the cross-sectional profile of the linear components is used to characterize their cross-sectional properties.

[0072] For surface components, they are abstracted as two-dimensional surface elements, and these two-dimensional surface elements carry the thickness and material properties of the surface components, and their boundaries and topological connections are consistent with those of the surface components; wherein, the thickness information of the surface components is used to characterize their thickness properties.

[0073] Components smaller than the first size threshold are geometrically reduced to zero-dimensional points with mass or specific properties.

[0074] The detailed removal includes:

[0075] Determine whether a component smaller than the second size threshold has a micro-hole. If so, fill or remove the micro-hole. Otherwise, determine whether the component has a chamfer, fillet, R-corner, slot, or bolt hole. If so, remove the chamfer, fillet, R-corner, slot, or bolt hole.

[0076] The geometric tolerance removal includes:

[0077] If the end distance between two components is less than the preset connection tolerance, the connection will be automatically extended until the end distance between the two components is not less than the preset connection tolerance.

[0078] If two components overlap, a Boolean operation is performed to merge or cut them to eliminate the overlapping area.

[0079] The automatic topology optimization and connection repair includes:

[0080] For linear and surface components that were originally connected, confirm whether the corresponding line and surface elements after dimensionality reduction share common geometric points or lines at the connection point. If so, perform surface normalization; otherwise, correct the dangling nodes.

[0081] like Figure 3 As shown, in step S300, the components with labeled civil structure semantics are subjected to geometric dimensionality reduction processing, abstracting solid beam and column components into one-dimensional line elements, and solid slab and wall components into two-dimensional surface elements; the dimensionality-reduced geometric components are subjected to detail culling and geometric tolerance removal processing to remove minor features and redundant details that are irrelevant to structural analysis; the processed geometry is subjected to automatic topology optimization and connection repair to ensure that all structural components achieve accurate topological connections in geometry.

[0082] Step S300 completes the geometric simplification of the BIM model and the creation of the CAE analysis model. This step aims to geometrically abstract and optimize the identified structural components based on the characteristics of CAE analysis, thereby improving analysis efficiency and avoiding unnecessary complexity.

[0083] Step S300 specifically includes:

[0084] S301, geometric dimensionality reduction processing, includes:

[0085] (1) For certain special scenarios or very small components, such as certain supports or nodes, they can be abstracted as zero-dimensional points with mass or specific properties.

[0086] (2) For example Figure 4 As shown, for linear members identified as frame beams, frame columns, foundation beams, etc., their geometric centroids or central axes are calculated, and they are abstracted into one-dimensional line elements. The line elements will carry the cross-sectional properties (e.g., rectangle 200x400mm, circle D500mm) and material properties of the original members, and ensure that their length and position are consistent with the original members.

[0087] (3) such as Figure 5 As shown, for surface components identified as floor slabs, shear walls, etc., specific geometric algorithms, such as those based on thickness shrinkage and mid-axis surface extraction, are used to abstract them into two-dimensional mid-surfaces, i.e., two-dimensional surface elements. The mid-surfaces carry the thickness and material properties of the original components and ensure that their boundaries and topological connections are consistent with the original components.

[0088] S302, detail removal, such as Figure 6 As shown, it includes:

[0089] (1) If the size is smaller than the set threshold, automatically identify and remove small geometric features that are not related to the structural analysis, such as chamfers, fillets, R-corners, slots, and bolt holes.

[0090] (2) Automatically fill or remove holes that are too small to reduce the complexity of mesh generation.

[0091] S303, geometric tolerance removal, such as Figure 7 As shown, including;

[0092] For potential geometric defects (i.e., geometric defects in the BIM model file) that may exist in step S100, such as minor gaps or overlaps, a geometric repair algorithm based on local tolerance is applied to detect and eliminate minor gaps or overlaps between components that are smaller than the preset tolerance. For components with inaccurate topological connections, automatic extension, trimming, or Boolean merging operations are performed to ensure that the connection points or lines accurately coincide. For example, if the distance between the ends of two components is less than the preset connection tolerance, they are automatically extended to make them accurately connected; if there is a minor overlap between two components, Boolean operations are performed to merge or trim to eliminate the overlapping area.

[0093] S304 automatically optimizes the topology and repairs connections, such as Figure 7 As shown, it includes:

[0094] (1) Ensure that the line elements and surface elements after dimensionality reduction share common geometric points or lines at the connection points, thereby constructing a CAE analysis model skeleton with correct topology and avoiding dangling nodes or units.

[0095] (2) Perform surface parameterization and patch normalization on the simplified geometry to lay the foundation for the subsequent generation of high-quality finite element meshes.

[0096] S400 stores all component entities and their civil structure semantics after being processed by S300 into the CAE intermediate model;

[0097] The CAE intermediate model adopts a hierarchical data structure and is used to store the cross-sectional shape, size parameters, material properties, local coordinate system and release conditions of each linear component; the thickness, material properties, element type and local coordinate system of each surface component; and the load type and boundary condition type of the component.

[0098] In step S400, the construction of the CAE intermediate model with enhanced structural semantics is completed. The geometric entities (i.e., component entities; for linear components, their entities are represented by their cross-sectional shape, dimensional parameters, material properties, local coordinate system and release conditions, load type, and boundary condition type; for surface components, their entities are represented by their thickness, material properties, element type and local coordinate system, load type, and boundary condition type) after geometric simplification and topology optimization in step S300 are bound to the structural semantics identified in step S200, constructing an intermediate data model with enhanced structural semantics and highly optimized for CAE analysis, such as... Figure 8 As shown. Step S400 specifically includes:

[0099] S401, this intermediate model employs a hierarchical data structure, such as a graph-based representation or XML / JSON format. It includes:

[0100] (1) Store the geometric node information of the analysis model (i.e., the geometric parameters in S102).

[0101] (2) Store component information of the analysis model, such as: reference line geometry of beam / column elements: including cross-sectional shape, size parameters, material properties, local coordinate system, release conditions, etc. Reference surface geometry of plate / wall elements: including thickness, material properties, element type (such as membrane, plate, shell), local coordinate system, etc.

[0102] (3) Definition of parameters required for CAE analysis, such as load type and boundary condition type of storage components.

[0103] S402 associates each component with the GlobalID of the original BIM component to enable the CAE results to be traced back to the BIM model. Simultaneously, the civil structural semantic information of the component is directly integrated into the component definition. For example, a line element not only has a geometric start and end point, but also attributes such as StructureRole=vertical load-bearing and bending resistance, FE_Type=Beam, Material_FEA==C30Concrete, and Section=Rect_200x400.

[0104] S500 converts intermediate CAE models into a format recognizable by the target CAE software.

[0105] In step S500, based on the structural semantics and original BIM attributes in the CAE intermediate model, the corresponding material and section attributes required for CAE analysis are automatically mapped and loaded, and finally converted into an analysis model file that can be recognized by the target CAE analysis software.

[0106] Step S500 completes the CAE attribute preloading and interface output. This step converts the intermediate CAE model into a format recognizable by the target CAE software and automatically loads various analysis attributes.

[0107] like Figure 9 As shown, step S500 specifically includes:

[0108] S501: Based on the material properties of the components in the CAE intermediate model, match and load the mechanical parameters of the corresponding materials from the predefined CAE material library.

[0109] Specifically, based on the Material_FEA attribute of the components in the CAE intermediate model, the system automatically matches and loads the corresponding mechanical parameters of the material, such as elastic modulus, Poisson's ratio, and yield strength, from a predefined CAE material library. If no match is found, the user is prompted to manually define or select the material.

[0110] S502. Based on the cross-sectional shape and size parameters of linear components (e.g., beams / columns) in the CAE intermediate model, select or create corresponding cross-sectional attributes from the cross-section library of the CAE software; based on the size parameters and thickness of surface components (e.g., plates / walls) in the CAE intermediate model, select or create corresponding thickness attributes from the attribute library of the CAE software.

[0111] S503, load the corresponding load type according to the component type of the component in the CAE intermediate model.

[0112] Specifically, based on information such as the type, location, and usage scenario of structural components in the CAE intermediate model, the system automatically identifies and loads the corresponding load types. For example, for a building structure model, it can automatically identify floor slab components and preload their self-weight loads, calculating the total self-weight based on the floor slab area and the preset unit area load value.

[0113] S504, load the corresponding boundary conditions based on the component type of the component in the CAE intermediate model.

[0114] Specifically, based on the connection relationships of structural components, the structural system, and the stress characteristics in the CAE intermediate model, the corresponding boundary conditions are automatically determined and applied. For example, for the connection between the beam at the top of the frame and the roof, if it is a hinged connection, the boundary conditions are set to restrict only vertical displacement.

[0115] It is worth noting that if the load type or boundary conditions are not preloaded in step S503 or S504, preliminary boundary condition suggestions (such as fixed constraints at the connection between the foundation component and the ground) or load application point suggestions will be automatically generated based on the StructureRole of the structural component and the topological connection relationship in the overall model, for the user to confirm or modify.

[0116] S505 converts the intermediate CAE model into a specific file format that can be directly imported or read by the target CAE analysis software selected by the user.

[0117] Specifically, based on the target CAE analysis software selected by the user, such as ANSYS, Abaqus, SAP2000, ETABS, Midas Gen, etc., the CAE intermediate model is converted into a specific file format that the software can directly import or read, such as APDL script files, INP files, .sdb files, .xls files, etc. During the conversion process, the relevant attributes (i.e., parametric attributes) of all components in the unified data model are mapped to the corresponding fields or commands in the target software.

[0118] In summary, the method provided by this invention employs a phased, multi-level conversion strategy. Its core lies in "understanding" and "extracting" the precise semantic information required for structural analysis from complex heterogeneous BIM data, performing geometric simplification optimization and topological correction, and ultimately constructing a structural model that meets the requirements of CAE analysis. This method can efficiently and accurately identify and extract effective civil structural information from model data in mainstream BIM formats such as RVT, DGN, and IFC, transforming it into an intermediate expression model that includes standard structural semantics and is highly optimized for CAE analysis. Finally, it generates an analysis model that can be directly used for CAE analysis, thereby significantly improving the automation level, efficiency, and accuracy of BIM-CAE collaboration.

[0119] This invention provides an electronic device, including: a computer-readable storage medium and a processor;

[0120] The computer-readable storage medium is used to store executable instructions;

[0121] The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in any of the above embodiments.

[0122] This invention provides a computer-readable storage medium storing computer instructions that cause a processor to perform the method described in any of the above embodiments.

[0123] This invention provides a computer program product, including a computer program or instructions, which, when executed by a processor, implement the method described in any of the above embodiments.

[0124] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements 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 CAE preprocessing and conversion of heterogeneous BIM models based on semantic understanding of civil structures, characterized in that, include: S100: Extract the 3D topology information, geometric parameters, parametric attributes, spatial relationships, connection relationships, and nesting relationships between all components in the BIM model file to be converted and store them in the Unified Data Model (UDM). The UDM adopts an object-oriented data structure and has the following attributes: storing the three-dimensional topological information, geometric parameters, and spatial, connection, and nesting relationships between each component; each component has an attribute dictionary or list to store the parameterized attributes of the component; each component has predefined fields to store the civil structure semantics of the component; and it has a mapping from component ID to UDM object, as well as an index of topological and logical relationships between UDM objects. S200: Calculate the dimensions of each component in the UDM to determine its geometric shape. If its geometric shape is linear, extract its cross-sectional profile along the minor axis. If its geometric shape is planar, extract its thickness information. Extract the spatial information of each component. Determine whether each component is a non-structural component based on its parametric attributes. If so, delete it from the UDM; otherwise, treat it as a potential structural component. Delete potential structural components that have no mechanical connection or interaction with the civil structure from the UDM. For the remaining potential structural components, determine their component type based on their spatial information and spatial, connection, and nesting relationships with other potential structural components, combined with knowledge of civil engineering, and save them to the corresponding predefined fields. S300 performs geometric dimensionality reduction, detail removal, geometric tolerance elimination, automatic topology optimization, and connection repair on each component in the UDM after S200 processing. S400 stores all component entities and their civil structure semantics after being processed by S300 into the CAE intermediate model; The CAE intermediate model adopts a hierarchical data structure and is used to store the cross-sectional shape, size parameters, material properties, local coordinate system and release conditions of each linear component; the thickness, material properties, element type and local coordinate system of each surface component; and the load type and boundary condition type of each component. S500 converts intermediate CAE models into a format recognizable by the target CAE software.

2. The method as described in claim 1, characterized in that, The BIM model file to be converted is one or more of the following formats: RVT, DGN, or IFC.

3. The method as described in claim 2, characterized in that, If the BIM model file to be converted is in IFC format, then the component type is determined directly based on its IfcRoot derived class; If the BIM model file to be converted is in Revit format, its component type can be directly determined using its built-in Category and BuiltInParameter properties.

4. The method as described in claim 1, characterized in that, In step S300, the geometric dimensionality reduction process includes: For linear components, they are abstracted as one-dimensional line elements, and these one-dimensional line elements carry the cross-sectional and material properties of the linear components; wherein, the cross-sectional profile of the linear components is used to characterize their cross-sectional properties. For surface components, they are abstracted as two-dimensional surface elements, and these two-dimensional surface elements carry the thickness and material properties of the surface components, and their boundaries and topological relationships are consistent with those of the surface components; among them, the thickness information of the surface components is used to characterize their thickness properties. Components smaller than the first size threshold are geometrically reduced to zero-dimensional points with mass or specific properties. The detailed removal includes: Determine whether a component smaller than the second size threshold has a micro-hole. If so, fill or remove the micro-hole. Otherwise, determine whether the component has a chamfer, fillet, R-corner, slot, or bolt hole. If so, remove the chamfer, fillet, R-corner, slot, or bolt hole. The geometric tolerance removal includes: If the end distance between two components is less than the preset connection tolerance, the connection will be automatically extended until the end distance between the two components is not less than the preset connection tolerance. If two components overlap, a Boolean operation is performed to merge or cut them to eliminate the overlapping area. The automatic topology optimization and connection repair includes: For linear and surface components that were originally connected, confirm whether the corresponding line and surface elements after dimensionality reduction share common geometric points or lines at the connection point. If so, perform surface normalization; otherwise, correct the dangling nodes.

5. The method as described in claim 1, characterized in that, Step S500 includes: S501, based on the material properties of the components in the CAE intermediate model, matches and loads the mechanical parameters of the corresponding materials from the predefined CAE material library; S502: Based on the cross-sectional shape and size parameters of the linear components in the CAE intermediate model, select or create corresponding cross-sectional attributes from the cross-section library of the CAE software; based on the size parameters and thickness attributes of the surface components in the CAE intermediate model, select or create corresponding thickness attributes from the attribute library of the CAE software. S503, load the corresponding load type according to the component type of the component in the CAE intermediate model; S504, Load the corresponding boundary conditions based on the component type of the component in the CAE intermediate model; S505 converts the intermediate CAE model into a specific file format that can be directly imported or read by the target CAE analysis software selected by the user.

6. An electronic device, characterized in that, include: Computer-readable storage media and processors; The computer-readable storage medium is used to store executable instructions; The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to perform the method as described in any one of claims 1-5.

8. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method as described in any one of claims 1-5.

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