A simulation method and device of a multi-scale coupling model, equipment and a storage medium

Abstract

The application relates to a simulation method, device and equipment of a multiscale coupling model and a storage medium, the method comprising the following steps: establishing a three-dimensional part model according to actual part information, and determining a mesoscopic analysis region and a macroscopic analysis region in the three-dimensional part model; generating a preset number of Voronoi polygons in the mesoscopic analysis region, and generating a grid according to a preset grid rule; determining mesoscopic grains according to the Voronoi polygons and the grid, and exporting mesoscopic grain information; and coupling the macroscopic analysis region and the mesoscopic grain information according to a preset coupling program to establish a multiscale coupling model. The simulation method, device and equipment of the multiscale coupling model and the storage medium provided by the application realize the construction of macroscopic and mesoscopic multiscale synchronous simulation, and solve the problems that a macroscopic empirical model cannot reflect mesoscopic structure changes and a mesoscopic model is too complex, has a large calculation amount, is difficult to converge and is not suitable for macroscopic component analysis.

Description

Technical Field

[0001] This invention relates to the field of crystal modeling technology, and in particular to a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. Background Technology

[0002] The deformation and failure processes of materials involve coupling effects across multiple scales. Methods based solely on the macroscopic scale are insufficient to accurately describe the deformation and failure mechanisms of materials; therefore, collaborative research across various scales is necessary. Traditional experimental simulation methods are no longer adequate for current material manufacturing processes. New simulation tools are urgently needed to accurately predict and describe the mechanical behavior of materials at different temporal and spatial scales, thereby facilitating the safety assessment of material design and service performance.

[0003] When solving models at different scales, the constitutive model of isotropic materials in existing technologies can be directly measured experimentally. However, simulating nonlinear anisotropic materials requires proposing empirical mathematical constitutive functions to capture experimental responses. These functions are called phenomenological models. Through experiments, macroscopic models can be obtained, which can macroscopically predict and describe the mechanical behavior of materials at different time and space scales. Alternatively, mesoscopic analysis methods, such as cellular automata, phase-field methods, and crystal plasticity finite element methods, can be used to study mesoscopic physical phenomena.

[0004] However, the macroscopic models obtained from experiments neglect mesoscopic structural changes and cannot adequately reflect the influence of the material's mesoscopic structure (such as grain morphology and orientation) on macroscopic plastic anisotropy. Although many scholars have studied the field of mesoscopic analysis, it is mostly used for the study of mesoscopic physical phenomena. Its complex models, large computational load, and difficulty in convergence make it unsuitable for simulating and analyzing large macroscopic model components and unsuitable for practical engineering applications. Summary of the Invention

[0005] In view of this, it is necessary to provide a simulation method, device, equipment and storage medium for a multi-scale coupled model to solve the problems that existing macroscopic models obtained through experiments ignore mesoscopic structural changes and cannot reflect the influence of material mesoscopic structure on macroscopic plastic anisotropy, and that models obtained by mesoscopic analysis methods are complex, computationally intensive and difficult to converge, and are not suitable for simulating and analyzing large macroscopic model components.

[0006] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a simulation method for a multi-scale coupled model, comprising:

[0008] A three-dimensional part model is established based on the actual part information, and the mesoscopic analysis region and macroscopic analysis region in the three-dimensional part model are determined.

[0009] Generate a preset number of Vino polygons within the mesoscopic analysis region, and generate a mesh according to a preset mesh rule;

[0010] Mesoscopic grains are determined based on Vino polygons and meshes, and mesoscopic grain information is derived.

[0011] The macroscopic analysis region and mesoscopic grain information are coupled according to the preset coupling procedure to establish a multi-scale coupling model.

[0012] In some possible implementations, a three-dimensional component model is established based on actual component information, and the mesoscopic and macroscopic analysis regions within the three-dimensional component model are determined, including:

[0013] Scan the actual parts to determine their dimensions and materials.

[0014] Three-dimensional component models are created based on dimensional and material information;

[0015] Based on the analysis requirements, the 3D component model is divided into a mesoscopic analysis area and a macroscopic analysis area.

[0016] In some possible implementations, the 3D component model is divided into a mesoscopic analysis region and a macroscopic analysis region according to the analysis requirements, including:

[0017] Establish a three-dimensional coordinate system and determine the coordinate information of the three-dimensional component model;

[0018] Based on the coordinate information of the 3D component model, the coordinate information of the mesoscopic analysis region is determined, and the model file of the macroscopic analysis region is exported.

[0019] In some possible implementations, a predetermined number of Vino polygons are generated within the mesoscopic analysis region, and a mesh is generated according to a predetermined mesh rule, including:

[0020] Based on the coordinate information of the mesoscopic analysis region, a preset number of Vino polygons are generated within the mesoscopic analysis region, and the center coordinates of the Vino polygons are determined.

[0021] Generate a mesh within the 3D component model according to the preset mesh rules, and determine the mesh number and mesh vertex coordinates.

[0022] In some possible implementations, mesoscopic grains are determined based on Vino polygons and meshes, and mesoscopic grain information is derived, including:

[0023] Based on a pre-defined method, the Vino polygons are divided according to the grid vertex coordinates and center coordinates to determine the mesoscopic grains;

[0024] The material information is associated with the mesoscopic grains based on the grid number, and the mesoscopic grain information is obtained and exported.

[0025] In some possible implementations, macroscopic analysis region and mesoscopic grain information are coupled according to a pre-defined coupling procedure to establish a multi-scale coupled model, including:

[0026] By integrating the model file of the macroscopic analysis region and the mesoscopic grain information, a multi-scale coupled file is obtained;

[0027] A multi-scale coupling model is established based on the preset coupling procedure and multi-scale coupling file.

[0028] In some possible implementations, a multi-scale coupling model is established based on a pre-defined coupling procedure and a multi-scale coupling file, including:

[0029] Import the multi-scale coupling file into the preset simulation tool and set the boundary conditions;

[0030] Obtain the preset coupling program and introduce intermediate variables to run the preset simulation tool to establish a multi-scale coupling model.

[0031] Secondly, the present invention also provides a simulation device for a multi-scale coupled model, comprising:

[0032] The 3D modeling module is used to create 3D component models based on actual component information and to determine the mesoscopic and macroscopic analysis regions in the 3D component models.

[0033] The generation module is used to generate a preset number of Vino polygons within the mesoscopic analysis region and generate a mesh according to preset mesh rules;

[0034] The mesoscopic module is used to determine mesoscopic grains based on Vino polygons and meshes, and to export mesoscopic grain information;

[0035] The simulation module is used to couple macroscopic analysis region and mesoscopic grain information according to a preset coupling program to establish a multi-scale coupled model.

[0036] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein,

[0037] Memory, used to store programs;

[0038] The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the simulation method of the multi-scale coupled model in any of the above implementations.

[0039] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps in the simulation method of the multi-scale coupled model in any of the above implementations.

[0040] The beneficial effects of the above embodiments are as follows: The present invention relates to a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. The method includes: establishing a three-dimensional component model based on actual component information, and determining a mesoscopic analysis region and a macroscopic analysis region in the three-dimensional component model; generating a preset number of Vino polygons in the mesoscopic analysis region, and generating a mesh according to a preset mesh rule; determining mesoscopic grains based on the Vino polygons and the mesh, and deriving mesoscopic grain information; and coupling the macroscopic analysis region and the mesoscopic grain information according to a preset coupling program to establish a multi-scale coupled model. This invention provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. It establishes a three-dimensional component model, constructs a macroscopic analysis region and a mesoscopic analysis region within the same three-dimensional component model, and divides the mesoscopic analysis region into Vino polygons to gradually determine the area to be analyzed, obtaining mesoscopic grains and exporting the information of the mesoscopic grains. A program is written that couples the macroscopic metal elastoplastic constitutive model with the mesoscopic crystal plastic constitutive model. Combining the mesoscopic grain information and the macroscopic analysis region, a multi-scale coupled model is established, realizing the construction of simultaneous multi-scale simulation of macroscopic and mesoscopic dimensions. This solves the problems that macroscopic empirical models cannot reflect mesoscopic structural changes and that mesoscopic models are too complex, computationally intensive, difficult to converge, and unsuitable for macroscopic component analysis. Attached Figure Description

[0041] Figure 1 A flowchart illustrating an embodiment of the simulation method for the multi-scale coupled model provided by the present invention;

[0042] Figure 2 Provided by the present invention Figure 1 A schematic flowchart of an embodiment of step S101;

[0043] Figure 3 A schematic diagram of a model of an embodiment of the tensile test provided by the present invention;

[0044] Figure 4 A schematic diagram of the structure of an embodiment of the simulation device for the multi-scale coupled model provided by the present invention;

[0045] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0046] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0047] In the description of this application, "multiple" means two or more, unless otherwise expressly and specifically defined.

[0048] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0049] This invention provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model, which will be described below.

[0050] Please see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the simulation method for a multi-scale coupled model provided by the present invention. A specific embodiment of the present invention discloses a simulation method for a multi-scale coupled model, comprising:

[0051] S101. Establish a three-dimensional component model based on the actual component information, and determine the mesoscopic analysis region and macroscopic analysis region in the three-dimensional component model;

[0052] S102. Generate a preset number of Vino polygons within the mesoscopic analysis region, and generate a mesh according to a preset mesh rule;

[0053] S103. Determine the mesoscopic grains based on the Vino polygons and mesh, and derive the mesoscopic grain information;

[0054] S104. According to the preset coupling procedure, the macroscopic analysis region and mesoscopic grain information are coupled to establish a multi-scale coupling model.

[0055] In the above embodiments, the three-dimensional component model is established using ABAQUS software. Before establishing the three-dimensional component model, it is necessary to obtain information about the actual component. It can be understood that the established three-dimensional component model is a model of a specific component that can be seen in ABAQUS software. This three-dimensional component model is divided into a macroscopic part and a mesoscopic part.

[0056] Vino polygons, also known as Thiessen polygons or Dirichlet graphs, are continuous polygons formed by the perpendicular bisectors of the lines connecting two adjacent points. Each Vino polygon contains one generator; the distance from a point within a Vino polygon to its generator is shorter than its distance to other generators; points on the boundary of a Vino polygon are equidistant from the generators that generated that boundary; the Vino polygon boundaries of adjacent graphs are subsets of the original adjacent boundaries.

[0057] It is understandable that once a multi-scale coupling model is established, simulation can be performed using that model.

[0058] Compared with the prior art, this embodiment provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. The method includes: establishing a three-dimensional component model based on actual component information, and determining the mesoscopic analysis region and macroscopic analysis region in the three-dimensional component model; generating a preset number of Vino polygons in the mesoscopic analysis region, and generating a mesh according to a preset mesh rule; determining mesoscopic grains based on the Vino polygons and the mesh, and deriving mesoscopic grain information; determining a coupling program, and establishing a multi-scale coupled model based on the macroscopic analysis region and the mesoscopic grain information. This invention provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. It establishes a three-dimensional component model, constructs a macroscopic analysis region and a mesoscopic analysis region within the same three-dimensional component model, and divides the mesoscopic analysis region into Vino polygons to gradually determine the area to be analyzed, obtaining mesoscopic grains and exporting the information of the mesoscopic grains. A program is written that couples the macroscopic metal elastoplastic constitutive model with the mesoscopic crystal plastic constitutive model. Combining the mesoscopic grain information and the macroscopic analysis region, a multi-scale coupled model is established, realizing the construction of simultaneous multi-scale simulation of macroscopic and mesoscopic dimensions. This solves the problems that macroscopic empirical models cannot reflect mesoscopic structural changes and that mesoscopic models are too complex, computationally intensive, difficult to converge, and unsuitable for macroscopic component analysis.

[0059] Please see Figure 2 , Figure 2 Provided by the present invention Figure 1 A flowchart illustrating an embodiment of step S101. In some embodiments of the present invention, a three-dimensional component model is established based on actual component information, and the mesoscopic analysis region and macroscopic analysis region in the three-dimensional component model are determined, including:

[0060] S201. Scan the actual parts to determine their size and material information.

[0061] S202. Establish three-dimensional component models based on dimensional and material information;

[0062] S203. Based on the analysis requirements, the three-dimensional component model is divided into a mesoscopic analysis area and a macroscopic analysis area.

[0063] In the above embodiments, scanning the actual parts can be achieved using existing technologies. There are multiple ways to achieve this using existing technologies, and detailed explanations are provided on how to do so. Therefore, this invention does not need to elaborate further. It is sufficient to accurately obtain the size and material information of the actual parts.

[0064] After determining the size and material information of the actual parts, a three-dimensional model of the parts is built in ABAQUS software. Since the actual parts are generally very large, many parts are not the focus of the study. Only the part of the mesoscopic model that needs to be studied is divided into mesoscopic regions according to the actual research needs. In the subsequent simulation, only this mesoscopic part can be simulated.

[0065] It should be noted that the analysis requirements can be adjusted according to actual needs. When it is necessary to study a certain part, the 3D component model can be divided into mesoscopic analysis area and macroscopic analysis area according to the analysis requirements.

[0066] In some embodiments of the present invention, the three-dimensional component model is divided into a mesoscopic analysis region and a macroscopic analysis region according to analysis requirements, including:

[0067] Establish a three-dimensional coordinate system and determine the coordinate information of the three-dimensional component model;

[0068] Based on the coordinate information of the 3D component model, the coordinate information of the mesoscopic analysis region is determined, and the model file of the macroscopic analysis region is exported.

[0069] In the above embodiments, a three-dimensional coordinate system is established within the spatial range of the three-dimensional component model. The coordinates can be used to accurately divide the mesoscopic analysis region and the macroscopic analysis region. After the division, the coordinates can be used to more conveniently describe each part in the mesoscopic analysis region, which is convenient for subsequent analysis.

[0070] The model file is an inp file, or you can export an inp file containing the entire 3D component model. This inp file has macroscopic attributes and can be used to describe the macroscopic state.

[0071] In some embodiments of the present invention, a predetermined number of Vino polygons are generated within the mesoscopic analysis region, and a mesh is generated according to a predetermined mesh rule, including:

[0072] Based on the coordinate information of the mesoscopic analysis region, a preset number of Vino polygons are generated within the mesoscopic analysis region, and the center coordinates of the Vino polygons are determined.

[0073] Generate a mesh within the 3D component model according to the preset mesh rules, and determine the mesh number and mesh vertex coordinates.

[0074] In the above embodiments, after drawing the mesoscopic analysis region, in order to simulate the mesoscopic analysis region, it is necessary to separately divide the mesoscopic analysis region into mesoscopic grains, and the mesoscopic grain division requires the coordinates of the mesoscopic analysis region.

[0075] The preset number can be set according to actual needs. This invention does not impose further restrictions on the preset number; the main purpose is to obtain a certain number of Vino polygons and to determine the relevant information of mesoscopic grains in subsequent determinations using the Vino polygons. The preset number of three-dimensional Vino polygons within the mesoscopic analysis region of the three-dimensional part model is generated using the MATLAB `voronoi3` function, and the center coordinates of each polygon are exported.

[0076] Preset mesh rules refer to dividing the mesoscopic analysis area into multiple meshes. The size of the mesh can also be set as needed. After dividing the mesh, the meshes need to be numbered to determine the number of all meshes and the coordinates of the mesh vertices in the three-dimensional coordinate system, which is convenient for subsequent determination of mesoscopic grain information.

[0077] It should be noted that the mesh module is used to control and divide the mesh, including the division of the local mesoscopic analysis region, and the vertex coordinates and cell numbers of the region are exported using the query module of tools.

[0078] In some embodiments of the present invention, mesoscopic grains are determined based on Vino polygons and meshes, and mesoscopic grain information is derived, including:

[0079] Based on a pre-defined method, the Vino polygons are divided according to the grid vertex coordinates and center coordinates to determine the mesoscopic grains;

[0080] The material information is associated with the mesoscopic grains based on the grid number, and the mesoscopic grain information is obtained and exported.

[0081] In the above embodiments, the preset method is the minimum distance method. Using the minimum distance method, the Vino polygon is divided according to the grid vertex coordinates and center coordinates so that the Vino polygon can represent the grains in the mesoscopic analysis region, that is, the mesoscopic grains are determined, and the mesoscopic grain information is determined according to each coordinate and the material information when the three-dimensional component model is built.

[0082] Understandably, after creating a 3D component model using ABAQUS software, coordinate information can be exported, and material information can be set according to actual conditions. ABAQUS software can import .inp files, and it can generate a new model based on the information within the .inp file. Integrating macroscopic and mesoscopic .inp files into one allows for the subsequent creation of multi-scale coupled models.

[0083] Using MATLAB, a certain number of cell center coordinates and corresponding indices are generated within a specified space (mesoscopic analysis region) according to the cell arrangement rules of the ABAQUS software. MATLAB is then used to calculate the distance between the cell center coordinates and the mesoscopic grain coordinates, and the corresponding cell indices are assigned to their respective grains using the minimum distance method. Finally, multiple cell sets (Elsets) in ABAQUS are generated in .inp file format.

[0084] In some embodiments of the present invention, a multi-scale coupling model is established by coupling macroscopic analysis region and mesoscopic grain information according to a preset coupling procedure, including:

[0085] By integrating the model file of the macroscopic analysis region and the mesoscopic grain information, a multi-scale coupled file is obtained;

[0086] A multi-scale coupling model is established based on the preset coupling procedure and multi-scale coupling file.

[0087] In the above embodiments, the generated .inp files containing mesoscopic grain information and macroscopic analysis region information are integrated into a complete .inp file containing both the macroscopic analysis region and the mesoscopic analysis region containing a certain number of grains. This .inp file is then imported into ABAQUS software to set boundary conditions. Finally, MATLAB is used to output the 3D model information and material information containing the mesoscopic analysis region in .inp file format.

[0088] The preset coupling program can select appropriate macroscopic and microscopic constitutive models to write UMAT subroutines. The coupling program is not the focus of this invention. It is only required that macroscopic and mesoscopic coupling can be achieved through existing technology. This invention does not impose further limitations on this.

[0089] In some embodiments of the present invention, a multi-scale coupling model is established based on a preset coupling procedure and a multi-scale coupling file, including:

[0090] Import the multi-scale coupling file into the preset simulation tool and set the boundary conditions;

[0091] Obtain the preset coupling program and introduce intermediate variables to run the preset simulation tool to establish a multi-scale coupling model.

[0092] In the above embodiments, the preset simulation tool is ABAQUS software, and the boundary conditions are the forces applied to the material during the forming process, as well as the constraint conditions. Please refer to... Figure 3 , Figure 3 This is a schematic diagram of a model of an embodiment of the tensile test provided by the present invention. Figure 3A standard specimen for a tensile test requires fixing one side while applying a force or a tensile speed to the other side to cause the model to stretch and deform. This is the boundary condition.

[0093] It is understood that the tensile conditions in this invention can also be adjusted according to actual needs and are not limited to tensile tests. This invention does not impose further limitations in this regard.

[0094] A multi-scale coupled model is established by using a macro-constitutive model and a meso-constitutive model. The macro-constitutive model is used to calculate the entire 3D model, while the meso-constitutive model is used to calculate the meso-scale region of the 3D model. Originally, the two constitutive models were independent, but now they are coupled together. The premise of coupling them together is to find a quantity used by both models, which is the intermediate variable.

[0095] Intermediate variables (nodal variables) without any physical meaning are introduced to facilitate information exchange between the two models. If different solution models yield the same or approximate nodal variables, such as stress or strain, at the same element nodes, then the two models can be considered to have the same control over the nodes and are substitutable. Therefore, in addition to the macroscopic region, macroscopic constitutive models are still used for calculations in the mesoscopic region. The two different constitutive models are computed in parallel without affecting each other, and the final result variables (including those with physical and non-physical meanings) all use the mesoscopic model. The macroscopic model results are only used as a condition for determining the iteration; if the nodal stresses of both models are the same, the calculation is successful; otherwise, another iteration is required.

[0096] To better implement the simulation method of the multi-scale coupled model in the embodiments of the present invention, based on the simulation method of the multi-scale coupled model, please refer to the corresponding... Figure 4 , Figure 4 This is a schematic diagram of a simulation device for a multi-scale coupled model provided by the present invention. The embodiment of the present invention provides a simulation device 400 for a multi-scale coupled model, comprising:

[0097] The 3D modeling module 410 is used to create a 3D part model based on the actual part information and to determine the mesoscopic analysis region and macroscopic analysis region in the 3D part model.

[0098] The generation module 420 is used to generate a preset number of Vino polygons within the mesoscopic analysis region and generate a mesh according to a preset mesh rule;

[0099] Mesoscopic module 430 is used to determine mesoscopic grains based on the Vino polygons and mesh, and to export mesoscopic grain information;

[0100] Simulation module 440 is used to couple macroscopic analysis region and mesoscopic grain information according to a preset coupling program to establish a multi-scale coupling model.

[0101] It should be noted that the device 400 provided in the above embodiments can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding content in the above method embodiments, and will not be repeated here.

[0102] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Based on the above-described simulation method for a multi-scale coupled model, the present invention also provides a simulation device for a multi-scale coupled model, which can be a computing device such as a mobile terminal, desktop computer, laptop, handheld computer, or server. The simulation device for the multi-scale coupled model includes a processor 510, a memory 520, and a display 530. Figure 5 Only some components of the electronic device are shown; however, it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0103] In some embodiments, memory 520 may be an internal storage unit of a simulation device for a multi-scale coupled model, such as a hard disk or memory of the simulation device. In other embodiments, memory 520 may be an external storage device of the simulation device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., provided on the simulation device. Furthermore, memory 520 may include both internal and external storage units of the simulation device. Memory 520 is used to store application software and various types of data installed on the simulation device for the multi-scale coupled model, such as the program code of the simulation device. Memory 520 may also be used to temporarily store data that has been output or will be output. In one embodiment, memory 520 stores a simulation program 540 for a multi-scale coupled model, which can be executed by processor 510 to implement the simulation method for the multi-scale coupled model of the embodiments of this application.

[0104] In some embodiments, processor 510 may be a central processing unit (CPU), microprocessor or other data processing chip, used to run program code stored in memory 520 or process data, such as executing simulation methods for multi-scale coupled models.

[0105] In some embodiments, display 530 may be an LED display, a liquid crystal display, a touch-screen liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 530 is used to display information from the simulation device of the multi-scale coupled model and to display a user interface for visualization. Components 510-530 of the simulation device of the multi-scale coupled model communicate with each other via a system bus.

[0106] In one embodiment, when the processor 510 executes the simulation program 540 of the multi-scale coupled model in the memory 520, the steps in the simulation method of the multi-scale coupled model as described above are implemented.

[0107] This embodiment also provides a computer-readable storage medium storing a simulation program for a multi-scale coupled model, which, when executed by a processor, performs the following steps:

[0108] A three-dimensional part model is established based on the actual part information, and the mesoscopic analysis region and macroscopic analysis region in the three-dimensional part model are determined.

[0109] Generate a preset number of Vino polygons within the mesoscopic analysis region, and generate a mesh according to a preset mesh rule;

[0110] Mesoscopic grains are determined based on Vino polygons and meshes, and mesoscopic grain information is derived.

[0111] The macroscopic analysis region and mesoscopic grain information are coupled according to the preset coupling procedure to establish a multi-scale coupling model.

[0112] In summary, this embodiment provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. The method includes: establishing a three-dimensional component model based on actual component information, and determining the mesoscopic analysis region and macroscopic analysis region in the three-dimensional component model; generating a preset number of Vino polygons within the mesoscopic analysis region, and generating a mesh according to a preset mesh rule; determining mesoscopic grains based on the Vino polygons and the mesh, and deriving mesoscopic grain information; and coupling the macroscopic analysis region and the mesoscopic grain information according to a preset coupling program to establish a multi-scale coupled model. This invention provides a simulation method, apparatus, device, and storage medium for a multi-scale coupled model. It establishes a three-dimensional component model, constructs a macroscopic analysis region and a mesoscopic analysis region within the same three-dimensional component model, and divides the mesoscopic analysis region into Vino polygons to gradually determine the area to be analyzed, obtaining mesoscopic grains and exporting the information of the mesoscopic grains. A program is written that couples the macroscopic metal elastoplastic constitutive model with the mesoscopic crystal plastic constitutive model. Combining the mesoscopic grain information and the macroscopic analysis region, a multi-scale coupled model is established, realizing the construction of simultaneous multi-scale simulation of macroscopic and mesoscopic dimensions. This solves the problems that macroscopic empirical models cannot reflect mesoscopic structural changes and that mesoscopic models are too complex, computationally intensive, difficult to converge, and unsuitable for macroscopic component analysis.

[0113] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A simulation method for a multi-scale coupled model, characterized in that, include: The process involves establishing a 3D component model based on actual component information and determining the mesoscopic and macroscopic analysis regions within the 3D component model. This includes: scanning the actual component to determine its size and material information; establishing a 3D component model based on the size and material information; establishing a 3D coordinate system and determining the coordinate information of the 3D component model; determining the coordinate information of the mesoscopic analysis region based on the coordinate information of the 3D component model, and exporting the model file of the macroscopic analysis region. A predetermined number of Vino polygons are generated within the mesoscopic analysis region, and a mesh is generated according to a predetermined mesh rule; Mesoscopic grains are determined based on the Vino polygons and the mesh, and mesoscopic grain information is derived. The model file of the macroscopic analysis region and the mesoscopic grain information are integrated to obtain a multi-scale coupling file; the multi-scale coupling file is imported into a preset simulation tool and boundary conditions are set; a preset coupling program is obtained, and intermediate variables are introduced to run the preset simulation tool to establish a multi-scale coupling model.

2. The simulation method for the multi-scale coupled model according to claim 1, characterized in that, The step of generating a preset number of Vino polygons within the mesoscopic analysis region and generating a mesh according to a preset mesh rule includes: Based on the coordinate information of the mesoscopic analysis region, a preset number of Vino polygons are generated within the mesoscopic analysis region, and the center coordinates of the Vino polygons are determined. A mesh is generated within the 3D component model according to a preset mesh rule, and the mesh number and mesh vertex coordinates are determined.

3. The simulation method for the multi-scale coupled model according to claim 2, characterized in that, The step of determining mesoscopic grains based on the Vino polygons and the mesh, and deriving mesoscopic grain information, includes: Based on a preset method, the Vino polygon is divided into mesoscopic grains according to the grid vertex coordinates and the center coordinates; The material information is associated with the mesoscopic grains based on the grid number to obtain and export the mesoscopic grain information.

4. A simulation device for a multi-scale coupled model, characterized in that, include: The 3D modeling module is used to create a 3D component model based on actual component information and to determine the mesoscopic and macroscopic analysis regions within the 3D component model. This includes: scanning the actual component to determine its size and material information; creating a 3D component model based on the size and material information; establishing a 3D coordinate system and determining the coordinate information of the 3D component model; determining the coordinate information of the mesoscopic analysis region based on the coordinate information of the 3D component model, and exporting the model file of the macroscopic analysis region. The generation module is used to generate a preset number of Vino polygons within the mesoscopic analysis region and generate a mesh according to a preset mesh rule; The mesoscopic module is used to determine mesoscopic grains based on the Vino polygons and the mesh, and to export mesoscopic grain information; The simulation module is used to integrate the model file of the macroscopic analysis region and the mesoscopic grain information to obtain a multi-scale coupling file; import the multi-scale coupling file into a preset simulation tool, set boundary conditions; obtain a preset coupling program, and introduce intermediate variables to run the preset simulation tool to establish a multi-scale coupling model.

5. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the simulation method of the multi-scale coupled model according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, are capable of implementing the steps in the simulation method of the multi-scale coupled model according to any one of claims 1 to 3.

Images