Modeling method and system for composite material structure with automatic fiber placement gap and lap joint defect
By generating defect models in the wire lay trajectory design software and utilizing the Python interface of the finite element software to automatically process mesh element properties, the problem of accurate identification and efficient assignment of gap and lap defects in the automatic wire lay process is solved, improving simulation accuracy and efficiency, and is suitable for high-precision simulation of composite material structures.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING UNIV
- Filing Date
- 2026-02-03
- Publication Date
- 2026-05-19
AI Technical Summary
Existing technologies struggle to accurately identify gaps and overlap defects in automated wire placement processes during finite element analysis, and fail to efficiently and automatically assign material properties in large-scale mesh models, resulting in low simulation efficiency and an inability to meet actual engineering needs.
By generating a defect model in the fiber placement trajectory design software, and utilizing the Python interface and efficient algorithms of the finite element software, the material, fiber orientation angle, and defect properties of the mesh elements are automatically processed to achieve high-precision simulation results.
It enables accurate identification and efficient attribute assignment of defects in automated fiber placement processes, significantly improving simulation accuracy and efficiency, and is suitable for the design and analysis of complex composite material structures.
Smart Images
Figure CN122067671A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of composite material structure simulation technology, and relates to a composite material structure modeling method and system that includes automatic fiber placement gaps and lap defects. Background Technology
[0002] Composite materials are widely used in aerospace, automotive, wind power, and other industrial fields due to their excellent specific strength, specific stiffness, and designability. Their mechanical properties are highly dependent on the fiber layup direction, sequence, and properties of each layer. When performing performance simulations of composite material structures using the Abaqus finite element method, establishing a model that accurately reflects these layup details is crucial. Traditional Abaqus composite material modeling methods are mostly based on uniform layup or simplification assumptions, reducing the layup direction to a few fixed angles, or using macroscopic homogeneous models. These methods cannot accurately reflect the spatial distribution of fiber angles caused by the continuous changes in fiber trajectory during automated fiber placement, as well as process defects such as local gaps and overlaps caused by fiber bundle placement, making it difficult to meet the requirements of high-precision simulation. To meet the refined modeling requirements of automated fiber placement, a very fine independent mesh setting must be used in finite element analysis, assigning material properties and fiber orientation angles to each fine element to achieve accurate simulation of structural mechanical behavior.
[0003] However, existing methods are significantly insufficient for the precise and efficient simulation of changing trajectories and defects in practical engineering applications of automated wire placement. Firstly, in engineering practice, there is a lack of effective and automated methods to accurately identify millimeter-level gaps and overlap defects from complex automated wire placement trajectories and map them to the finite element model. Secondly, when the model mesh size reaches hundreds of thousands or even millions, manually assigning attributes to each element in the finite element software interface, or interactively assigning attributes using conventional algorithms, incurs enormous computational and data processing overhead, is time-consuming, and may even be impossible to complete due to memory or interactive limitations, severely restricting the efficiency of refined simulations for practical engineering applications.
[0004] A search revealed shortcomings in existing technologies. For example, the Chinese patent application number 201711167029.9, "Simulation Analysis Method for Mechanical Properties of Automatic Fiber Placement Composite Materials," did not extract and map the actual fiber placement trajectory angle during calculation. The model only deflected the fiber bundle trajectory at a fixed angle. This method does not match the actual automatic fiber placement conditions in engineering and cannot meet practical engineering needs.
[0005] The Chinese patent application number 202010238110.7, entitled "A Simulation Modeling Method for Composite Curing Deformation Based on Fiber Placement Trajectory", maps all layup information to the same mesh model, stretches the two-dimensional mesh into a three-dimensional solid mesh, ignores the influence of the thickness of the structure and the difference in the fiber trajectory on different layup layers, and does not identify or analyze the gaps and overlap defects introduced by automatic fiber placement.
[0006] The Chinese patent application number 202111537058.6, entitled "An Automatic Wire Laying Trajectory Layered Simulation Modeling Method Applicable to Complex Rotating Bodies", projects the center point of the grid onto the nearest trajectory curve, calculates the tangent vector of the projection point on the trajectory line, and calculates the grid angle. However, this method cannot identify gaps and overlap defects introduced by automatic wire laying and perform structural analysis for these defects.
[0007] The Chinese patent application number 202211634395.1, entitled "An Automatic Fiber Laying Trajectory Projection Simulation Modeling Method for Composite Materials", describes a method where the shell unit size is set to an integer multiple of the fiber bundle width. This method cannot achieve more refined structural simulation, especially for structures with fiber bundle gaps and lap defects that are significantly smaller than the fiber bundle size, which cannot be accurately modeled and analyzed.
[0008] The Chinese patent application number 202210096986.1, entitled "A Design Method for Bistable Curve Fiber Laminates", only applies to the automatic placement of fiber bundles with specific formula trajectories. It lacks versatility and cannot meet the structural analysis requirements of different structures in engineering, including variations in automatic fiber placement trajectories and the introduction of defects.
[0009] The Chinese patent application number 202511296471.6, entitled "A Simulation Modeling Method and System for Fiber Direction of Composite Materials", first obtains data through equipment and then obtains fiber-laying related data through reverse fitting. However, it is not feasible to obtain actual product data during the design stage and is therefore not practical. Summary of the Invention
[0010] In view of this, the purpose of this invention is to provide a composite material simulation modeling method and system that can accurately identify defects in the automatic fiber placement process and efficiently and automatically assign attributes to ultra-large-scale mesh models, so as to significantly improve the feasibility and efficiency of high-precision simulation.
[0011] To achieve the above objectives, the present invention provides the following technical solution:
[0012] On one hand, the present invention provides a method for modeling composite material structures containing automatic fiber placement gaps and lap defects, comprising the following steps: S1: Design the wire laying trajectory and generate defects to obtain a geometric model of the wire laying component containing defect information; S2: Mesh the geometric model of the wire-laying component to generate a finite element model, and read the coordinate information of all element nodes and the mesh element order information from the finite element model; S3: Calculate the coordinate information of the center point of the corresponding grid cell using the unit node extracted in S2, and determine whether the corresponding grid cell belongs to a defect and its defect type, until the defect judgment of all grid cells is completed, and output the judgment results of all grid cells. S4: Store the material identifier, layup number, fiber orientation angle, and defect attributes of all mesh elements; S5: Using the stored mesh element information, complete the material assignment, fiber direction angle and defect attribute assignment for all mesh elements in the finite element model; S6: Perform finite element calculations on the assigned finite element model to obtain simulation results that reflect the actual wire laying trajectory and the influence of defects.
[0013] Furthermore, step S1 specifically includes: designing the filament laying trajectory in professional filament laying trajectory software based on the component surface geometry, generating or defining possible gaps and overlap defects in the trajectory based on process rules, and outputting initial filament laying structure data containing defect information.
[0014] Furthermore, step S2 specifically includes: importing the component geometric model obtained in S1 into the finite element analysis software, performing mesh generation to generate the finite element model; exporting the INP file of the finite element model, and reading the coordinate information of all element nodes and the order information of mesh elements from it; The coordinate information of the unit node is obtained by parsing the unit node list from the INP file and calculating the average value of the node coordinates to obtain the coordinates of the unit center point.
[0015] Furthermore, step S3 specifically includes the following steps: S31: Calculate the coordinate information of the center point of the corresponding grid element using the Node extracted in S2, and generate a grid coordinate .csv data file; S32: Import the grid coordinates .csv data file into the fiber placement software for analysis. For each imported coordinate point, calculate its coordinate position and fiber orientation angle. At the same time, based on the position of the coordinate point in the fiber placement structure, compare it with the defect area generated in S1 to determine whether the unit to which the point belongs is located in the defect area and record its defect type. S33: Export the result file .csv containing the fiber orientation angle, the ply to which it belongs, and the defect type marker for each coordinate point.
[0016] Furthermore, in step S32, if the coordinate point falls within the preset gap polygon area, it is marked as a gap defect; if the coordinate point is covered by multiple filament trajectories, it is marked as an overlap defect; otherwise, it is marked as intact.
[0017] Furthermore, step S4 specifically includes: establishing a structured mapping file based on the result file .csv exported from S33; this file uses the unit number as an index to fully store the material identifier, layup number, fiber orientation angle, and defect attribute code of each unit.
[0018] Furthermore, in step S5, the following algorithm is used to automatically assign values to all grids: S51: First, read the attribute CSV file and automatically iterate through all cells; S52: Obtain the model and parts; S53: Batch processing by cross-section; S54: Batch allocation section; S55: Batch processing of materials; S56: Calculate the total program execution time; By combining looping and vectorization operations, the material assignment, orientation angle setting, and defect attribute marking of the entire model unit are completed based on the attribute information recorded in the file.
[0019] Furthermore, step S6 specifically includes: in the finite element analysis software, on the model with completed attribute assignment, setting boundary conditions, loads and analysis steps, defining the field variables to be output, submitting for finite element calculation, and obtaining simulation results that reflect the actual wire laying trajectory and the influence of defects.
[0020] On the other hand, the present invention provides a composite material structure modeling system that includes automatic fiber placement gap and lap defect detection, comprising: The trajectory design defect generation module is used to design trajectories and generate defects in wire placement software; The finite element preprocessing module is used for geometry import, mesh generation, and node information export. The coordinate interaction and defect judgment module is used to import the mesh coordinates back to the wire laying software for angle calculation and defect judgment, and output the attribute results; The attribute mapping file generation module is used to organize attribute results into structured data files; The automated assignment algorithm engine is an algorithm embedded in the finite element software, used to read mapping files and set element properties in batches; The simulation calculation and analysis module is used to set boundary conditions and perform finite element solutions.
[0021] The beneficial effects of this invention are as follows: High precision: Through the interactive strategy of "grid coordinates back to fiber placement software", the fiber orientation angle of each unit is directly calculated using high-fidelity fiber placement trajectory data, and the spatial relationship is accurately judged based on the defect area defined in the design stage, realizing the physical and realistic mapping of continuous changes in fiber angle and micro-process defects.
[0022] High Efficiency: The core of this invention lies in its highly efficient "mesh element-layout attribute mapping" algorithm and optimized batch data writing mechanism. It generates structured CSV mapping files and utilizes the kernel-level Python API of the finite element software for batch attribute assignment. Through optimization strategies such as spatial indexing and parallel processing, the algorithm reduces the time complexity of attribute calculation and assignment to an extremely low level. This reduces the time required to complete complex attribute assignment for models with millions of elements on a typical personal computer from tens of hours or even infeasible to tens of minutes or even a few minutes, breaking through the efficiency bottleneck of large-scale simulation modeling.
[0023] High versatility and operability: The entire process is based on the data interface of general-purpose CAE software (Abaqus) and fiber placement design software, without relying on specific equipment or physical placement. The system's modules have clear divisions of labor, making them easy to integrate and automate. It can be directly used for subsequent static, dynamic, instability, fatigue, and curing deformation analyses of composite materials. The method has low requirements for computer hardware and is easy to promote and use in engineering practice.
[0024] In summary, this invention provides an efficient, accurate, and automated solution for refining the modeling results of composite material automatic fiber placement trajectories and defects. It is particularly suitable for complex composite material structure design and analysis where both simulation accuracy and efficiency are highly demanding.
[0025] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description
[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 Flowchart of a method for modeling composite material structures with automatic fiber placement gaps and lap defects; Figure 2 A schematic diagram of the shape of the film applied to the curved surface structure; Figure 3 A schematic diagram showing the planning of the filament laying path and filament bundle; Figure 4A schematic diagram of assigning values to a finite element model; Figure 5 This is a schematic diagram of the simulation results. Detailed Implementation
[0027] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.
[0028] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.
[0029] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.
[0030] Example 1: This invention provides an efficient and accurate modeling method for composite material structures containing automatic fiber placement gaps and lap defects, such as... Figure 1 As shown, it includes the following steps: S1. Trajectory Design and Defect Generation: In professional wire layup trajectory design software, the wire layup trajectory is designed according to the surface geometry of the component, and possible gaps and overlap defects are generated or defined in the trajectory based on process rules, and the initial wire layup structure data containing defect information is output.
[0031] S2. Finite Element Mesh Generation and Node Information Extraction: Import the component geometric model obtained in S1 into finite element analysis software (such as Abaqus) to generate a finite element model through mesh generation; export the INP file of this model, and read the coordinate information of all element nodes and the order information of the mesh elements from it. In this embodiment, the method for calculating the coordinates of the element center is to parse the list of element nodes from the INP file and calculate the average value of the node coordinates using Python to obtain the coordinates of the element center point.
[0032] S3. Grid-trajectory coordinate interaction and defect judgment: S31. Using the element nodes extracted in S2, calculate the coordinate information of the center point of the corresponding grid element using Python, and generate a grid coordinate .csv data file.
[0033] S32. Import the grid coordinates .csv data file into the fiber placement software for analysis. For each imported coordinate point, calculate its fiber orientation angle relative to the underlying fiber placement trajectory. Simultaneously, based on the position of this coordinate point in the fiber placement structure, compare it with the defect areas (gap, overlap) generated in S1 to determine whether the unit to which the point belongs is located in a defect area and record its defect type. In this embodiment, the defect judgment rule is: if the coordinate point falls within a preset gap polygon area, it is marked as a "gap" defect; if the coordinate point is covered by multiple fiber bundle trajectories, it is marked as an "overlap" defect; otherwise, it is marked as "intact".
[0034] S33. Export the result file .csv containing the fiber orientation angle, layup, and defect type marker for each coordinate point (corresponding to a grid cell).
[0035] S4. Efficient Attribute Mapping File Generation: Based on the .csv file exported from S33, a structured mapping file is created. This file uses the cell number as an index and fully stores the material identifier, layup number, fiber orientation angle, and defect attribute code for each cell.
[0036] S5. Python Algorithm Design: Building Efficient Algorithms with Python.
[0037] S51. According to this algorithm, the attribute CSV file is first read, and all cells are automatically traversed. The algorithm is as follows:
[0038] S52. Obtain the model and components, the algorithm is as follows:
[0039] S53. Batch processing by cross-section, the algorithm is as follows:
[0040] S54. Batch allocation of sections, the algorithm is as follows:
[0041] S55. For batch processing of materials, the algorithm is as follows:
[0042] S56. Calculate the total program running time using the following algorithm:
[0043] Based on the attribute information recorded in the file, and combined with loop and vectorization operations, the material assignment, orientation angle setting and defect attribute marking of the entire model unit are completed efficiently and in batches. This process avoids the interactive design requirements of the graphical user interface (GUI).
[0044] S6. Automated Batch Attribute Assignment: In the finite element analysis software, a Python interface is used to read the CSV mapping file generated by S4 using the algorithm in S5, and complete the material assignment, fiber direction angle and defect attribute assignment for all mesh elements efficiently.
[0045] S7. Simulation Model Completion and Calculation: On the model with completed attribute assignment, set boundary conditions, loads and analysis steps, define the field variables to be output, submit for finite element calculation, and obtain simulation results that reflect the actual wire laying trajectory and the influence of defects.
[0046] Example 2: This embodiment uses the automatic fiber placement simulation of a certain aerospace composite curved surface structure as an example to illustrate the modeling method of composite material structures containing automatic fiber placement gaps and lap defects, including the following steps: S1: In the fiber placement design software, the film shape is applied according to the curved surface structure. Figure 2 The diagram shows the planning of the filament laying path and filament bundles, generating the filament bundle trajectory centerline, filament bundles, and filament bundle gaps, triangular areas, or overlaps, as shown. Figure 3 As shown.
[0047] S2: Import the curved surface geometric model into Abaqus, and mesh it using S4R shell elements. The mesh size is fine enough to distinguish preset defects. The mesh size is set to 0.5mm, but can be increased or decreased according to actual needs. Export the job.inp file, write the algorithm parsing file, extract the coordinates of all nodes of each element, calculate its arithmetic mean center coordinates, and save it as centroids.csv.
[0048] S3: Import centroids.csv into the fiber layup software. The software's built-in program reads each coordinate point, finds its layup and fiber path, and calculates the fiber direction at that point. Simultaneously, it compares the coordinates of this point with the boundary of the gap region defined in S1. If it falls within this boundary, the "GAP" attribute is added to the element. After processing, export the file angle_defect.csv, which contains the element ID, mesh, layup, angle, and defect code.
[0049] S4: Rectify the format of angle_defect.csv to ensure it corresponds to the Abaqus cell number order, and generate the final property mapping file property_map.csv.
[0050] S5: Open the model in Abaqus / CAE and run the custom Python algorithm file via the command-line interface. This algorithm reads property_map.csv, iterates through each element in the model, assigns corresponding composite material property parameters based on its layup information, creates and assigns material orientation based on angle information, and assigns pure resin properties to the mesh elements based on defect codes, such as... Figure 4 As shown, the entire process runs in the background and takes about 20 minutes.
[0051] S6: In Abaqus, apply fixed boundary conditions and tensile loads to the model, set up a static general analysis step, and output the displacement, stress, and strain fields. Submit the calculation; the obtained analysis results clearly show the stress concentration phenomenon around the defect region, which is consistent with theoretical expectations, such as... Figure 5 As shown.
[0052] Example 3: This embodiment provides a composite material structure modeling system that includes automatic fiber placement gap and lap defect detection, comprising: The trajectory design defect generation module is used to design trajectories and generate defects in wire placement software; The finite element preprocessing module is used for geometry import, mesh generation, and node information export. The coordinate interaction and defect judgment module is used to import the mesh coordinates back to the wire laying software for angle calculation and defect judgment, and output the attribute results; The attribute mapping file generation module is used to organize attribute results into structured data files; The automated assignment algorithm engine is a Python algorithm embedded in the finite element software, used to read mapping files and set element attributes in batches; The simulation calculation and analysis module is used to set boundary conditions and perform finite element solutions.
[0053] This system is suitable for various static, dynamic, instability, fatigue, and curing deformation analyses of composite materials.
[0054] Example 4: An electronic device, comprising a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the method described in Embodiment 1 when executing the computer program.
[0055] Example 5: A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in Embodiment 1.
[0056] Example 6: A computer program product includes a computer program that, when executed by a processor, implements the method described in Example 1.
[0057] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.
[0058] In the above embodiments, although the invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed. The embodiments of the invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims.
[0059] As will be understood by those skilled in the art, the computer-readable storage medium described in this embodiment allows for the implementation of all or part of the steps in the above method embodiments by computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0060] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic terminal performs the steps of the above method.
[0061] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.
[0062] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0063] This invention can be used in a wide range of general-purpose or special-purpose computing system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.
[0064] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.
[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A method for modeling composite material structures including automatic fiber placement gaps and lap defects, characterized in that: Includes the following steps: S1: Design the wire laying trajectory and generate defects to obtain a geometric model of the wire laying component containing defect information; S2: Mesh the geometric model of the wire-laying component to generate a finite element model, and read the coordinate information of all element nodes and the mesh element order information from the finite element model; S3: Calculate the coordinate information of the center point of the corresponding grid cell using the unit node extracted in S2, and determine whether the corresponding grid cell belongs to a defect and its defect type, until the defect judgment of all grid cells is completed, and output the judgment results of all grid cells. S4: Store the material identifier, layup number, fiber orientation angle, and defect attributes of all mesh elements; S5: Using the stored mesh element information, complete the material assignment, fiber direction angle and defect attribute assignment for all mesh elements in the finite element model; S6: Perform finite element calculations on the assigned finite element model to obtain simulation results that reflect the actual wire laying trajectory and the influence of defects.
2. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 1, characterized in that: Step S1 specifically includes: designing the filament laying trajectory in professional filament laying trajectory design software based on the surface geometry of the component, generating or defining possible gaps and overlap defects in the trajectory based on process rules, and outputting initial filament laying structure data containing defect information.
3. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 2, characterized in that: Step S2 specifically includes: importing the component geometric model obtained in S1 into the finite element analysis software, performing mesh generation to generate the finite element model; exporting the finite element model's INP file, and reading the coordinate information of all element nodes and the order information of mesh elements from it; The coordinate information of the unit node is obtained by parsing the unit node list from the INP file and calculating the average value of the node coordinates to obtain the coordinates of the unit center point.
4. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 3, characterized in that: Step S3 specifically includes the following steps: S31: Calculate the coordinate information of the center point of the corresponding grid element using the Node extracted in S2, and generate a grid coordinate .csv data file; S32: Import the grid coordinates .csv data file into the fiber placement software for analysis. For each imported coordinate point, calculate its coordinate position and fiber orientation angle. At the same time, based on the position of the coordinate point in the fiber placement structure, compare it with the defect area generated in S1 to determine whether the unit to which the point belongs is located in the defect area and record its defect type. S33: Export the result file .csv containing the fiber orientation angle, the ply to which it belongs, and the defect type marker for each coordinate point.
5. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 4, characterized in that: In step S32, if the coordinate point falls within the preset gap polygon area, it is marked as a gap defect; if the coordinate point is covered by multiple filament trajectories, it is marked as an overlap defect; otherwise, it is marked as intact.
6. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 5, characterized in that: Step S4 specifically includes: establishing a structured mapping file based on the result file .csv exported from S33; this file uses the unit number as an index to fully store the material identifier, layup number, fiber orientation angle, and defect attribute code of each unit.
7. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 6, characterized in that: In step S5, the following algorithm is used to automatically assign values to all grid cells: S51: First, read the attribute CSV file and automatically iterate through all cells; S52: Obtain the model and parts; S53: Batch processing by cross-section; S54: Batch allocation section; S55: Batch processing of materials; S56: Calculate the total program execution time; By combining looping and vectorization operations, the material assignment, orientation angle setting, and defect attribute marking of the entire model unit are completed based on the attribute information recorded in the file.
8. The method for modeling composite material structures containing automatic fiber placement gaps and lap defects according to claim 7, characterized in that: Step S6 specifically includes: in the finite element analysis software, on the model with completed attribute assignment, setting boundary conditions, loads and analysis steps, defining the field variables to be output, submitting for finite element calculation, and obtaining simulation results that reflect the actual wire laying trajectory and the influence of defects.
9. A composite material structure modeling system that includes automatic fiber placement gap and lap defect detection, characterized in that: include: The trajectory design defect generation module is used to design trajectories and generate defects in wire placement software; The finite element preprocessing module is used for geometry import, mesh generation, and node information export. The coordinate interaction and defect judgment module is used to import the mesh coordinates back to the wire laying software for angle calculation and defect judgment, and output the attribute results; The attribute mapping file generation module is used to organize attribute results into structured data files; The automated assignment algorithm engine is an algorithm embedded in the finite element software, used to read mapping files and set element properties in batches; The simulation calculation and analysis module is used to set boundary conditions and perform finite element solutions.