A high-precision digital twin deformation simulation method for composite materials

Abstract

The present invention relates to the technical field of material simulation, and provides a high-precision composite material digital twin deformation simulation method and system, comprising obtaining specimen dimensions and specimen layup in advance, and constructing a specimen geometric model; building a finite element model of the specimen according to the specimen geometric model, and generating a specimen twin simulation grid; obtaining specimen attribute parameters, setting material density, and generating an elastic modulus matrix; fusing the elastic modulus matrix with the specimen twin simulation grid, performing equivalent stiffness partitioning, and generating a stiffness matrix; loading the stiffness matrix into an Abaqus program called by a preset script, establishing a specimen target model, and generating a specimen displayable file.

Description

Technical Field

[0001] The present invention relates to the field of material simulation, and in particular to a high-precision composite material digital twin deformation simulation method. Background Art

[0002] At present, composite materials have attracted wide attention in aerospace, automobile, construction and other fields due to their excellent mechanical properties and broad application prospects. However, the deformation behavior of composite materials is complex and is affected by many factors, including material composition, structural form, loading conditions, etc. Traditional experimental testing methods are time-consuming, costly, and difficult to fully cover various working conditions. Therefore, it is of great significance to develop an efficient and accurate numerical simulation method for composite deformation.

[0003] The upstream industries of the digital twin industry are mainly chips, sensors, monitoring equipment and other industries. The upstream industry market is in a state of perfect competition, and product prices will fluctuate with market changes. The downstream industries of the digital twin industry include aerospace, electricity, shipping, urban management and other industries. The downstream industries are large in scale and have great potential demand. Driven by the sustained development of the domestic economy, China's digital twin industry is facing unprecedented development opportunities.

[0004] However, some technologies may not fully consider factors such as the multi-scale details and interlayer interfaces of composite materials, resulting in a large deviation between the simulation results and the actual situation. The definition of material properties may be too simplified and cannot accurately reflect the nonlinear deformation and damage evolution of composite materials. Some technologies may not fully consider factors such as the multi-scale details and interlayer interfaces of composite materials, resulting in a large deviation between the simulation results and the actual situation. The definition of material properties may be too simplified and cannot accurately reflect the nonlinear deformation and damage evolution of composite materials. Inhomogeneity of material properties: Composite materials are composed of two or more materials with different and incompatible properties combined through a certain process, and their properties are unevenly distributed in space. This inhomogeneity makes it difficult to accurately describe the mechanical behavior of composite materials using a simple uniform material model. Anisotropy of material properties: The properties of composite materials often vary with direction, for example. The performance of fiber-reinforced composites in the fiber direction is usually better than that in the perpendicular fiber direction. This anisotropy increases the complexity of mechanical analysis and simulation.

[0005] Large discreteness of material properties: Due to the influence of factors such as preparation process and raw material quality, the properties of composite materials may have large discreteness. This discreteness may cause the same batch of composite materials to show different properties in mechanical tests.

[0006] Difficulty in material quality control: Due to the complexity of the composite material preparation process, its quality control is relatively difficult. Slight process changes may lead to significant changes in material properties.

[0007] High material cost: The preparation of composite materials requires the use of high-performance raw materials such as fibers and resins, as well as high-precision equipment and processes. These factors lead to high manufacturing costs for composite materials, especially when using high-end materials such as carbon fiber and boron fiber.

[0008] Large dispersion of material properties: As mentioned above, the properties of composite materials may be highly dispersed due to factors such as preparation process and raw material quality. This dispersion not only increases the difficulty of mechanical analysis, but also brings challenges to material performance testing.

[0009] Material damage and failure mechanism: When composite materials are subjected to external forces, their damage and failure mechanisms are often more complex than those of traditional materials. For example, when composite materials are subjected to impact loads, multiple damage modes such as matrix cracking, fiber breakage, and interlayer debonding may occur simultaneously. The interaction between these damage modes makes it difficult to accurately describe the failure mechanism of composite materials with simple mechanical models. Complexity of material simulation analysis: In order to accurately simulate the mechanical behavior of composite materials, simulation models need to consider multiple factors such as material heterogeneity, anisotropy, damage and failure mechanisms. The existing technology may have traditional meshing methods that cannot be optimized according to the geometric characteristics and analysis requirements of composite materials, resulting in huge calculations and low simulation efficiency. The solution algorithm may not be efficient enough and cannot quickly converge to an accurate solution, further affecting the simulation efficiency. The existing technology may lack a friendly user interface and easy-to-use operation process, causing users to encounter many difficulties during use, reducing the ease of use and flexibility of simulation analysis. Users may not be able to customize parameters such as material properties, geometric models, boundary conditions, etc., and cannot meet the needs of different application scenarios, limiting the versatility and practicality of the existing technology. With the continuous development of composite materials technology, existing technologies may not be able to keep up with the emergence of new materials and the development of new technologies, resulting in a large gap between simulation results and actual conditions. Existing technologies may lack in-depth research and understanding of the mechanical behavior of new composite materials and cannot accurately simulate and predict their deformation and performance changes.

[0010] In summary, the existing technologies in the field of digital twin simulation and analysis of composite materials may have shortcomings such as insufficient simulation accuracy, low simulation efficiency, insufficient multi-field coupling analysis capabilities, poor user experience, and lagging technology updates. Summary of the invention

[0011] The present invention proposes a high-precision composite material digital twin deformation simulation method and a control method thereof, which are used to solve the situation in the above-mentioned background technology.

[0012] The present invention proposes a high-precision composite material digital twin deformation simulation method, wherein: Obtain the specimen size and specimen layup in advance and build the specimen geometry model; According to the specimen geometry model, build the finite element model of the specimen and generate the specimen twin simulation mesh; Obtain specimen property parameters, set material density, and generate elastic modulus matrix; The elastic modulus matrix is ​​integrated with the specimen twin simulation mesh, and the equivalent stiffness partition is performed to generate the stiffness matrix; The stiffness matrix is ​​loaded into the Abaqus program called by the preset script, the specimen target model is established, and the specimen display file is generated.

[0013] Preferably, the twin simulation grid is also used to receive configuration conditions; Among them, the configuration conditions include load configuration conditions and cycle number configuration conditions; The load configuration conditions and the number of cycles determine the boundary conditions of the specimen; The load configuration conditions include a first configuration method and a second configuration method; wherein the first configuration method is based on direct top selection based on the relative position of the table in the twin simulation grid, and the second configuration method is based on the position function of the twin simulation grid for area selection.

[0014] Preferably, the stiffness matrix is ​​based on a stiffness matrix degradation algorithm; Among them, the stiffness matrix degradation algorithm solves the load in the twin simulation grid by calling the solver in the Abaqus program to generate prediction data, which is the prediction data of the specimen simulation; The solver is used to solve and determine the load stress, load strain and residual stiffness after N load cycles; The file generated by the solver after solving the problem is an .odb file.

[0015] Preferably, the step of generating a testable and displayable file further comprises: According to the .odb file, the finite element model of the specimen after N cycles is determined; wherein the finite element model includes a stress cloud map, a strain cloud map and a residual stiffness cloud map, and the finite element model includes a finite element fatigue evolution model.

[0016] Preferably, the generating of the testable and displayable file further comprises: The specimen target model is connected to the VTK function library to generate a three-dimensional display diagram.

[0017] Preferably, the VTK function library includes a graphics model and a visualization model; The graphic model is based on a graphical user interface, and the specimen target model performs rendering mapping processing through the graphic model; The visualization model is based on the coordinate system, and the specimen target model performs three-dimensional stereo transformation processing through the coordinate system.

[0018] Preferably, the graphics model includes: a rendering controller, a rendering window, a renderer, lights, a camera, roles, attributes, transformation operations and mappings.

[0019] Preferably, the coordinate system includes a model coordinate system, a world coordinate system, a display coordinate system and a view coordinate system.

[0020] Preferably, the step of generating a testable and displayable file further comprises: Predetermine the original data class of the specimen target model; Receive the original data class through the filter, filter the data, and determine the mappable data; Mapping mappable data into geometric data through a preset data form; By collecting data, the scene is drawn, and the corresponding specimen collection image is displayed after the drawing is successful.

[0021] A high-precision composite material digital twin deformation simulation system, comprising: Collection construction module: obtain the specimen size and specimen ply in advance and build the specimen geometry model; Twin simulation module: build the finite element model of the specimen according to the specimen geometry model, and generate the specimen twin simulation mesh; Modulus matrix building module: obtain specimen attribute parameters, set material density, and generate elastic modulus matrix; Stiffness matrix building module: integrates the elastic modulus matrix with the specimen twin simulation grid, performs equivalent stiffness partitioning, and generates a stiffness matrix; Display processing module: load the stiffness matrix into the Abaqus program called by the preset script, establish the specimen target model, and generate the specimen display file.

[0022] The beneficial effects of the present invention are: By modeling composite materials with high precision and taking into account factors such as multi-scale details and interlayer interfaces, the present invention can accurately simulate the actual structure and deformation characteristics of composite materials. This significantly improves the accuracy of the simulation results, making design optimization and performance evaluation more reliable. The refined definition of material serpentine and the introduction of advanced constitutive relations support the input of parameters such as material anisotropy, so that the present invention can more deeply reveal the deformation and damage evolution process of composite materials under complex loading conditions. This helps researchers to understand the mechanical behavior of composite materials more comprehensively and provide strong support for the development and application of new materials. Intelligent network partitioning technology and key area automatic encryption method enable the present invention to significantly improve simulation efficiency while ensuring accuracy. This reduces computing time and resource consumption, making simulation analysis faster and more convenient. Multi-field coupling analysis models and solution methods enable the present invention to more comprehensively simulate the deformation behavior and performance changes of composite materials in practical applications. This helps to comprehensively evaluate the comprehensive performance of composite materials and provide a scientific basis for material selection and design optimization. System integration and user interface design enable the present invention to have a good user interface and easy-to-use operation process. This lowers the user's threshold for use and improves the ease of use and flexibility of simulation analysis. At the same time, it supports user-defined parameters, meets the needs of different application scenarios, and enhances the practicality and versatility of the present invention. The obvious effect of the technology of the present invention is also reflected in promoting the application and development of composite materials. By providing a high-precision and high-efficiency simulation analysis method, the present invention helps to accelerate the research and development of new materials and promote the widespread application of composite materials in aerospace, automobiles, construction and other fields. This will have a positive impact on enhancing the competitiveness and innovation capabilities of related industries.

[0023] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0024] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a method flow chart of a high-precision composite material digital twin deformation simulation method in an embodiment of the present invention; Figure 2 It is a schematic diagram of the VTK framework structure in an embodiment of the present invention; Figure 3A schematic diagram of the structure of the VTK graphics model in an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a visual graphics model in an embodiment of the present invention; Figure 5 This is a schematic diagram of camera focus movement in an embodiment of the present invention; Figure 6 A schematic diagram of the relationship of the coordinate system in an embodiment of the present invention; Figure 7 It is a schematic diagram of the operation of the VTK operation mechanism in an embodiment of the present invention; Figure 8 A schematic diagram of a contour map of radiation heat transfer simulation results developed by VTK in an embodiment of the present invention; Fig. 9 A schematic diagram of a radiation heat transfer simulation result cloud map developed by VTK in an embodiment of the present invention; Fig.10 This is a system composition diagram of a high-precision composite material digital twin deformation simulation system in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0027] like Figure 1 As shown, this embodiment provides a high-precision composite material digital twin deformation simulation method, the method comprising: Obtain the specimen size and specimen layup in advance and build the specimen geometry model; According to the specimen geometry model, build the finite element model of the specimen and generate the specimen twin simulation mesh; Obtain specimen property parameters, set material density, and generate elastic modulus matrix; The elastic modulus matrix is ​​integrated with the specimen twin simulation mesh, and the equivalent stiffness partition is performed to generate the stiffness matrix; The stiffness matrix is ​​loaded into the Abaqus program called by the preset script, the specimen target model is established, and the specimen display file is generated.

[0028] In the specific implementation, the specimen geometry model is constructed by obtaining the specimen size and the specimen ply, that is, the geometric parameters of the specimen are determined according to the geometric shape and requirements of the specimen. The geometric parameters of the specimen are imported into the simulation software to construct the three-dimensional geometric model of the specimen.

[0029] Then, according to the specimen geometry model, the finite element model of the specimen is built, and the specimen twin simulation mesh is generated. That is, according to the design requirements of the specimen, the appropriate mesh type and size are selected, imported into the simulation software, and meshing is performed. Through the software algorithm, the coordinates and unit mass of each mesh node are calculated to generate mesh data. As needed, the generated mesh data is processed and optimized to improve the accuracy and reliability of the model.

[0030] Then, the elastic modulus matrix is ​​generated by obtaining the specimen property parameters and setting the material density. That is, the physical property parameters of the specimen, such as density and elastic modulus, are obtained from the specimen design file or laboratory test report. The physical property parameters of the specimen are imported into the simulation software, and the corresponding material density is set. According to the physical property parameters of the specimen, the corresponding elastic modulus matrix is ​​generated.

[0031] Finally, it will be responsible for integrating the elastic modulus matrix and the specimen twin simulation mesh with each other, performing equivalent stiffness partitioning, and generating a stiffness matrix. That is, the elastic modulus matrix and the specimen twin simulation mesh are imported into the simulation software, and Boolean operations are performed to obtain the equivalent stiffness matrix of the specimen. As needed, the generated equivalent stiffness matrix is ​​processed and optimized to improve the accuracy and reliability of the model.

[0032] In the process of generating the specimen display file, firstly, the specimen parameters corresponding to the stiffness matrix are input into the simulation software to generate the corresponding script program, and then, according to the script program, the Abaqus program is called to establish the specimen target model and generate the specimen display file. Specifically, the generated stiffness matrix is ​​imported into the simulation software, the script program is generated, and then the set Abaqus program script is called to perform analysis and processing, and the generated target model is processed and optimized to improve the accuracy and reliability of the model. The generated target model is exported as an interactive or visual file for users to view and use.

[0033] The beneficial effect of the present invention is that by high-precision composite material modeling, considering factors such as multi-scale details and interlayer interfaces, the present invention can accurately simulate the actual structure and deformation characteristics of composite materials. This significantly improves the accuracy of simulation results, making design optimization and performance evaluation more reliable. Refined definition of material serpentine and introduction of advanced constitutive relations, support for the input of parameters such as material anisotropy, so that the present invention can more deeply reveal the deformation and damage evolution process of composite materials under complex loading conditions. This helps researchers to understand the mechanical behavior of composite materials more comprehensively and provide strong support for the development and application of new materials. Intelligent network partitioning technology and key area automatic encryption method enable the present invention to significantly improve simulation efficiency while ensuring accuracy. This reduces computing time and resource consumption, making simulation analysis faster and more convenient. Multi-field coupling analysis model and solution method enable the present invention to more comprehensively simulate the deformation behavior and performance changes of composite materials in practical applications. This helps to comprehensively evaluate the comprehensive performance of composite materials and provide a scientific basis for material selection and design optimization. System integration and user interface design enable the present invention to have a good user interface and easy-to-use operation process. This lowers the user's threshold for use and improves the ease of use and flexibility of simulation analysis. At the same time, it supports user-defined parameters, meets the needs of different application scenarios, and enhances the practicality and versatility of the present invention. The obvious effect of the technology of the present invention is also reflected in promoting the application and development of composite materials. By providing a high-precision and high-efficiency simulation analysis method, the present invention helps to accelerate the research and development of new materials and promote the widespread application of composite materials in aerospace, automobiles, construction and other fields. This will have a positive impact on enhancing the competitiveness and innovation capabilities of related industries.

[0034] As an embodiment of the present invention: the twin simulation grid is also used to receive configuration conditions; Among them, the configuration conditions include load configuration conditions and cycle number configuration conditions; The load configuration conditions and the number of cycles determine the boundary conditions of the specimen; The load configuration conditions include a first configuration method and a second configuration method; wherein the first configuration method is based on direct top selection based on the relative position of the table in the twin simulation grid, and the second configuration method is based on the position function of the twin simulation grid for area selection.

[0035] In the specific implementation, in the boundary condition setting of the specimen, the boundary condition setting is completed by selecting the corresponding area to set the load and the number of cycles. There are two ways to set the load data corresponding to the spatial position in a table; the second is to select the area to input the load data by writing the corresponding function. After completing the load definition, set the number of load cycles n.

[0036] As an embodiment of the present invention:, the stiffness matrix is ​​based on a stiffness matrix degradation algorithm; Among them, the stiffness matrix degradation algorithm solves the load in the twin simulation grid by calling the solver in the Abaqus program to generate prediction data, which is the prediction data of the specimen simulation; The solver is used to solve and determine the load stress, load strain and residual stiffness after N load cycles; The file generated by the solver after solving the problem is an .odb file.

[0037] In specific implementation, the present invention uses the stiffness matrix degradation algorithm (.for file) to call the ABAQUS explicit solver to solve the stress, strain, and residual stiffness after n loads, and predicts the residual stiffness to generate a corresponding .odb file.

[0038] As an embodiment of the present invention: the generating of the testable and displayable file further comprises: According to the .odb file, the finite element model of the specimen after N cycles is determined; wherein the finite element model includes a stress cloud map, a strain cloud map and a residual stiffness cloud map, and the finite element model includes a finite element fatigue evolution model.

[0039] In the specific implementation, by processing the odb file, the stress, strain, and residual stiffness cloud maps of the finite element model under n loads can be generated. The stress, strain, and residual stiffness cloud maps under different loads can be viewed by dragging the progress bar, and it supports viewing the stress, strain, and residual stiffness cloud maps in the fatigue evolution of the future finite element model.

[0040] As an embodiment of the present invention, the generating of the testable and displayable file further includes: The specimen target model is connected to the VTK function library to generate a three-dimensional display diagram.

[0041] In actual implementation, the present invention adopts an object-oriented approach based on the 3D function library OpenGL, which can shield the details that are often encountered in the visualization development process and encapsulate some commonly used algorithms. It contains a C++ class library and an interpretation encapsulation layer, including Java, Tcl, Python, etc. The advantage of using this architecture is that we can use C++ language to establish efficient algorithms, and other languages ​​(such as Tcl, Python) can be used for rapid development. Through the powerful 3D graphics functions of the VTK function library (such as Figure 2 In actual implementation, the VTK function library contains abstract base classes and basic classes to perform data processing. In this process, Figure 2The calling sequence of functions is disclosed. In the figure: vtkobject: vtk object, which belongs to the basic class, is used to process the file that needs to be displayed after simulation in the present invention, realize visualization, and determine the corresponding object; vtkSource: vtk source, which belongs to the abstract base class, is used to generate and provide data for realizing visualization; vtkFilter: vtk filter, which belongs to the abstract base class, is used to process and convert data, and generate output data that can be visualized. vtkMapper: vtk drawer, which belongs to a class, is used for data mapping and graphic representation, that is, to determine how to convert input data into graphic elements that can be drawn on the screen. vtkActor: vtk mapper, which belongs to a class, is used to represent an entity in the scene, such as a collection object, which is used to combine attribute information so that the data can be rendered and displayed in three-dimensional space. vtkRender, vtkR renderer, belongs to a class, is used to render the scene, and in the visualization process, the processed data and the mapping results are displayed on the screen.

[0042] VTK supports both voxel-based volume rendering and traditional surface rendering, thus greatly improving visualization while making full use of existing graphics libraries and graphics hardware. VTK's architecture gives it excellent streaming and caching capabilities, so it does not have to consider memory resource limitations when processing large amounts of data. VTK can better support network-based tools, such as Java and Vrml. With the development of Web and Internet technologies, VTK has a good development prospect. VTK can support a variety of shading, such as OpenGL. VTK is device-independent, making its code highly portable. Many macros are defined in VTK, which greatly simplify programming and enforce consistent object behavior. VTK has a rich data type and supports processing of multiple data types.

[0043] As an embodiment of the present invention: the VTK function library includes a graphics model (such as Figure 3 ) and visual models (as shown in Figure 4 shown); The graphic model is based on a graphical user interface, and the specimen target model performs rendering mapping processing through the graphic model; The visualization model is based on the coordinate system, and the specimen target model performs three-dimensional stereo transformation processing through the coordinate system.

[0044] In actual implementation, there are two different ways of object-oriented design, namely, graphic model and visualization model, which take advantage of the simplicity and ease of use of 3D graphics system and also adopt the graphical user interface (GUI) method. Figure 3:Instances of vtkRenderWindow, which represent vtk renderer window instances; instances ofvtkRenderer vtk, which represent renderer instances; One vtkCamera defines view for eachrenderer, which is used to define a vtk camera view for each renderer; One or morevtkLights illuminatethescene, which is used to configure one or more vtk lighting scenes; vtkProperty defines actor surfacepropoerties, which is used to define vtk properties and determine surface properties; vtkMapper defines actorgeometry, which is used to configure the geometry defined by the vtk drawer; Instances of vtkActor vtk is used to generate drawer instances.

[0045] As an embodiment of the present invention: the graphics model includes: a rendering controller, a rendering window, a renderer, lights, a camera, a role, attributes, transformation operations and mapping.

[0046] In actual implementation, Render master defines device-independent coordinate calculation methods and creates rendering windows; render window manages windows on display devices, and one or more drawing methods can create a scene on the rendering window; the rendering window is a user graphical interface, which includes methods such as setting the size of the rendering window and producing stereoscopic display effects; Renderer manages the position and properties of light sources, cameras, and drawing objects, and provides conversion between world coordinate systems, observation coordinate systems, and display coordinate systems; Lights can illuminate drawing objects in the scene, and can change the state, illumination angle, illumination intensity, color, etc. of the light by calling parameters, and supports point light sources and parallel light sources; Camera defines the position, focus point and other related properties of the observer, and the parameters can be set by the caller as needed; Actor represents the drawing object entity in the rendering scene, and the position, direction, rendering characteristics, references, texture mapping and other properties of the character can be set by adjusting parameters, and the character can be scaled; Property describes some characteristics of geometric objects to achieve the realism of three-dimensional graphics; Transform It is a stack of 4×4 transformation matrices, which can perform various operations. The graphics model supports 3D geometric data drawing, 3D volume data drawing, 2D geometric text, and image drawing; Mapper specifies the connection between rendering data and basic primitives in the graphics library. One or more roles can use the same mapping, and there are multiple parameters to control it.

[0047] As an embodiment of the present invention: the coordinate system includes a model coordinate system, a world coordinate system, a display coordinate system and a view coordinate system.

[0048] In actual implementation, the visualization model is based on the properties of the camera, and there are many ways to move around the focus (such as Figure 5 As shown, in Figure 5 In Chinese: Roll means scroll; Elevation means elevation; Azimuth means azimuth. ); various methods are around the model coordinate system, world coordinates, display coordinates, view coordinates (such as Figure 6 ). The view coordinate system represents the visible part of the camera. The display coordinate system uses the same base as the View coordinate system, but there is no limit from -1 to 1, and the coordinates represent the actual x and y pixel positions. The world coordinate system is the position coordinates of the Actor. The model coordinate system is the Cartesian coordinate defined by the model. In specific implementation, VTK uses the Pipeline operation mechanism, which can process almost any type of data, and provides many corresponding classes to convert or process various types of data.

[0049] As an embodiment of the present invention: the generating of the testable and displayable file further comprises: Predetermine the original data class of the specimen target model; Receive the original data class through the filter, filter the data, and determine the mappable data; Mapping mappable data into geometric data through a preset data form; By collecting data, the scene is drawn, and the corresponding specimen collection image is displayed after the drawing is successful.

[0050] In the specific implementation, VTK visualizes the volume data in the following steps: select different classes according to the type of original data to be processed; vtkObiect is the base class of the Visualization Toolkit class library, which provides basic methods for the entire visualization process; vtkSource is a derived class of vtkObiect and the parent class of vtkFilter, which defines specific behaviors and interfaces for the beginning of the entire visualization process, such as reading data.

[0051] The filter receives data from the data source and performs various filtering operations; vtkFilter is a derived class of vtkSource. It performs various processing on data. After the original data is processed by various filters, it is converted into a form that can be directly processed by a certain algorithm module.

[0052] Mapping is to map the processed appropriate data form into geometric data; vtkMapper is also a derived class of vtkObiect. It maps the application data processed by various filters into geometric data and defines the interface between the original data and the image data.

[0053] The character displays the visualized data in the window; the vtkActor class is used to represent an entity in the rendering scene, and it tells the character the properties of the geometric data through the SetMappe() method. The Actor displays the result in the window through the vtkRender class; The converted VTK data can be visualized by extracting its corresponding objects and then calling its object visualization method through Java. In this project, Java is mainly used to call VTK to extract simulation results and display simulation results (such as Figure 7 As shown, in Figure 7 In the VTK dataset, vtkDataSet represents the VTK dataset; Props represents the property; Actor represents the object; and Volume represents the quantity).

[0054] The extraction of simulation results mainly includes the extraction of heat transfer data of the radiation heating virtual test system, such as temperature, heat transfer coefficient and other parameters (such as Figure 8 As shown); structural parameter extraction, such as equivalent stress, strain, etc. Among them, vtkTypeArray is used for the simulation result object to store the index number of the currently selected unit, and vtkExtractSelection implements the data extraction function. Its first input is the extracted vtkPolyData, and the second input is the vtkSelection object, which marks the data type to be extracted. After the extraction, the extracted result can be saved to a vtkActor object and added to the current vtkRenderer for display. The contour line display of the simulation result uses the VTK method to write the contour line algorithm into the vtkContourFilter class. This class passes the data object to be processed through the SetInputData interface, draws a single contour line through the SetValue function, and draws multiple contour lines through the GenerateValues ​​function.

[0055] The cloud diagram of the simulation results (such as Fig. 9 As shown in the figure), when mapping the temperature field, stress field and other attribute data into cloud map color bands based on VTK, you need to define the color band lookup table first. The color band lookup table can be defined as RGB type and HSV type; then pass the color band lookup table to the mapper, and select the scalar attribute for color band mapping and the numerical range corresponding to the color band lookup table in the mapper.

[0056] The present invention also proposes a high-precision composite material digital twin deformation simulation system, wherein: Collection construction module: obtain the specimen size and specimen ply in advance and build the specimen geometry model; Twin simulation module: build the finite element model of the specimen according to the specimen geometry model, and generate the specimen twin simulation mesh; Modulus matrix building module: obtain specimen attribute parameters, set material density, and generate elastic modulus matrix; Stiffness matrix building module: integrates the elastic modulus matrix with the specimen twin simulation grid, performs equivalent stiffness partitioning, and generates a stiffness matrix; Display processing module: load the stiffness matrix into the Abaqus program called by the preset script, establish the specimen target model, and generate the specimen display file.

[0057] In specific implementation, Fig.10 As shown, the assembly construction module constructs the specimen geometric model by acquiring the specimen size and the specimen ply, that is, determines the specimen geometric parameters according to the specimen geometric shape and requirements. The specimen geometric parameters are imported into the simulation software to construct the specimen's three-dimensional geometric model.

[0058] Then, the twin simulation module builds the finite element model of the specimen according to the specimen geometry model and generates the specimen twin simulation mesh. That is, according to the design requirements of the specimen, select the appropriate mesh type and size, import it into the simulation software, and perform mesh division. Through the software algorithm, calculate the coordinates and unit mass of each mesh node and generate mesh data. As needed, process and optimize the generated mesh data to improve the accuracy and reliability of the model.

[0059] The modulus matrix building module generates the elastic modulus matrix by obtaining the specimen property parameters and setting the material density. That is, the physical property parameters of the specimen, such as density and elastic modulus, are obtained from the specimen design file or laboratory test report. The physical property parameters of the specimen are imported into the simulation software, and the corresponding material density is set. According to the physical property parameters of the specimen, the corresponding elastic modulus matrix is ​​generated.

[0060] Finally, the stiffness matrix building module is responsible for integrating the elastic modulus matrix and the specimen twin simulation mesh with each other, performing equivalent stiffness partitioning, and generating a stiffness matrix. That is, the elastic modulus matrix and the specimen twin simulation mesh are imported into the simulation software, and Boolean operations are performed to obtain the equivalent stiffness matrix of the specimen. As needed, the generated equivalent stiffness matrix is ​​processed and optimized to improve the accuracy and reliability of the model.

[0061] In the process of generating the specimen display file, the display processing module first inputs the specimen parameters corresponding to the stiffness matrix into the simulation software, generates the corresponding script program, and then, according to the script program, calls the Abaqus program to establish the specimen target model and generate the specimen display file. Specifically, the generated stiffness matrix is ​​imported into the simulation software, a script program is generated, and then the set Abaqus program script is called to perform analysis and processing, and the generated target model is processed and optimized to improve the accuracy and reliability of the model. The generated target model is exported as an interactive or visual file for users to view and use.

[0062] The beneficial effects of the present invention are: By modeling composite materials with high precision and taking into account factors such as multi-scale details and interlayer interfaces, the present invention can accurately simulate the actual structure and deformation characteristics of composite materials. This significantly improves the accuracy of the simulation results, making design optimization and performance evaluation more reliable. The refined definition of material serpentine and the introduction of advanced constitutive relations support the input of parameters such as material anisotropy, so that the present invention can more deeply reveal the deformation and damage evolution process of composite materials under complex loading conditions. This helps researchers to understand the mechanical behavior of composite materials more comprehensively and provide strong support for the development and application of new materials. Intelligent network partitioning technology and key area automatic encryption method enable the present invention to significantly improve simulation efficiency while ensuring accuracy. This reduces computing time and resource consumption, making simulation analysis faster and more convenient. Multi-field coupling analysis models and solution methods enable the present invention to more comprehensively simulate the deformation behavior and performance changes of composite materials in practical applications. This helps to comprehensively evaluate the comprehensive performance of composite materials and provide a scientific basis for material selection and design optimization. System integration and user interface design enable the present invention to have a good user interface and easy-to-use operation process. This lowers the user's threshold for use and improves the ease of use and flexibility of simulation analysis. At the same time, it supports user-defined parameters, meets the needs of different application scenarios, and enhances the practicality and versatility of the present invention. The obvious effect of the technology of the present invention is also reflected in promoting the application and development of composite materials. By providing a high-precision and high-efficiency simulation analysis method, the present invention helps to accelerate the research and development of new materials and promote the widespread application of composite materials in aerospace, automobiles, construction and other fields. This will have a positive impact on enhancing the competitiveness and innovation capabilities of related industries.

[0063] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A high-precision composite material digital twin deformation simulation method, characterized in that: Said: Obtain the specimen size and specimen layup in advance and build the specimen geometry model; According to the specimen geometry model, build the finite element model of the specimen and generate the specimen twin simulation mesh; Obtain specimen property parameters, set material density, and generate elastic modulus matrix; The elastic modulus matrix is ​​integrated with the specimen twin simulation mesh, and the equivalent stiffness partition is performed to generate the stiffness matrix; The stiffness matrix is ​​loaded into the Abaqus program called by the preset script, the specimen target model is established, and the specimen displayable file is generated.

2. A high-precision composite material digital twin deformation simulation method according to claim 1, characterized in that: The twin simulation grid is also used to receive configuration conditions; Among them, the configuration conditions include load configuration conditions and cycle number configuration conditions; The load configuration conditions and the number of cycles determine the boundary conditions of the specimen; The load configuration conditions include a first configuration method and a second configuration method; wherein the first configuration method is based on direct top selection based on the relative position of the table in the twin simulation grid, and the second configuration method is based on the position function of the twin simulation grid for area selection.

3. A high-precision composite material digital twin deformation simulation method as claimed in claim 2, characterized in that: The stiffness matrix is ​​based on a stiffness matrix degradation algorithm; Among them, the stiffness matrix degradation algorithm solves the load in the twin simulation grid by calling the solver in the Abaqus program to generate prediction data, which is the prediction data of the specimen simulation; The solver is used to solve and determine the load stress, load strain and residual stiffness after N load cycles; The file generated by the solver after solving the problem is an .odb file.

4. A high-precision composite material digital twin deformation simulation method as claimed in claim 3, characterized in that: The generating of the testable and displayable file further comprises: According to the .odb file, the finite element model of the specimen after N cycles is determined; wherein the finite element model includes a stress cloud map, a strain cloud map and a residual stiffness cloud map, and the finite element model includes a finite element fatigue evolution model.

5. A high-precision composite material digital twin deformation simulation method according to claim 1, characterized in that: The generating of the testable and displayable file further includes: The specimen target model is connected to the VTK function library to generate a three-dimensional display diagram.

6. A high-precision composite material digital twin deformation simulation method as claimed in claim 5, characterized in that: The VTK function library includes a graphics model and a visualization model; The graphic model is based on a graphical user interface, and the specimen target model performs rendering mapping processing through the graphic model; The visualization model is based on the coordinate system, and the specimen target model performs three-dimensional stereo transformation processing through the coordinate system.

7. A high-precision composite material digital twin deformation simulation method as claimed in claim 6, characterized in that: The graphics model includes: rendering controller, rendering window, renderer, light, camera, role, attribute, transformation operation and mapping.

8. A high-precision composite material digital twin deformation simulation method as claimed in claim 6, characterized in that: The coordinate system includes a model coordinate system, a world coordinate system, a display coordinate system and a view coordinate system.

9. A high-precision composite material digital twin deformation simulation method according to claim 1, characterized in that: The generating of the testable and displayable file further comprises: Predetermine the original data class of the specimen target model; Receive the original data class through the filter, filter the data, and determine the mappable data; Mapping mappable data into geometric data through a preset data form; By collecting data, the scene is drawn, and the corresponding specimen collection image is displayed after the drawing is successful.

10. A high-precision composite material digital twin deformation simulation system, characterized in that: Said: Collection construction module: obtain the specimen size and specimen ply in advance and build the specimen geometry model; Twin simulation module: build the finite element model of the specimen according to the specimen geometry model, and generate the specimen twin simulation mesh; Modulus matrix building module: obtain specimen attribute parameters, set material density, and generate elastic modulus matrix; Stiffness matrix building module: integrates the elastic modulus matrix with the specimen twin simulation grid, performs equivalent stiffness partitioning, and generates a stiffness matrix; Display processing module: load the stiffness matrix into the Abaqus program called by the preset script, establish the specimen target model, and generate a specimen display file.

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