A method and device for automatic design of multi-dimensional gradient structure

Abstract

The present invention proposes a multidimensional gradient structure automatic design method and device, which relates to the technical field related to digital design. The method comprises: constructing a multidimensional gradient structure model, taking the bottom center of the multidimensional gradient structure model as the coordinate origin, dividing the multidimensional gradient structure model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks satisfies the multidimensional gradient distribution conditions in the axial, radial and circumferential directions; importing the multidimensional gradient structure model after the distribution block division into a finite element processing module to generate a finite element input file with different density gradient distributions; inputting all the finite element input files into an Ls‑dyna solver for batch calculation, obtaining a structural response data file of each multidimensional gradient structure model during the loading process, so as to regulate the side waveform of the multidimensional gradient structure model. The present invention is helpful to control the controllable loading of the density distribution of the multidimensional gradient structure.

Description

Technical Field

[0001] The present invention relates to the technical field related to digital design, and in particular to a multi-dimensional gradient structure automatic design method and device. Background Art

[0002] Functional gradient materials are a new type of composite material whose composition and structure change continuously from one end to the other, so that the performance of the material also changes gradually. Functional gradient materials are widely used in aerospace, energy and power, biomedicine and other fields due to their excellent special properties. With the improvement of the service reliability and safety of key materials in the fields of national defense security, aerospace and high-end manufacturing, there is an urgent need for dynamic physical property data of gradient materials under different stresses and strain rates. The main method for obtaining such dynamic physical property data of materials at home and abroad is multi-stage light gas gun loading technology. One of the core of this loading technology is the controllable loading of gradient materials. In the field of dynamic high pressure, by loading a disk with a density gradient structure, the internal wave impedance (the product of material density and sound speed) gradient can be achieved to control the propagation of shock waves and achieve the purpose of controllable loading.

[0003] The Chinese patent with the announcement number CN114756934B discloses a three-dimensional multi-scale metamaterial structure optimization design method, including the following steps: constructing a parametric metamaterial lattice structure according to the design requirements, extracting control parameters as design variables, performing macroscopic prediction on them, completing the establishment of a parametric interpolation model, establishing a solid model, dividing the structural design domain, applying boundary conditions and external force loads, completing the establishment of a finite element model, obtaining the displacement field of the macrostructure and microunits based on finite element analysis, and by constructing a three-dimensional multi-scale metamaterial structure collaborative optimization model, performing sensitivity analysis on the design variables in the macroscale and microscale, and iteratively updating the design variables in the macroscale and microscale, thereby determining the optimal layout of the three-dimensional multi-scale metamaterial structure. The above scheme does not fully solve the problem of mechanical response stability of the structure, and it is also impossible to adjust the structure through changes in structural parameters. It is difficult to intuitively obtain changes in impedance. Therefore, it is very necessary to provide a multi-dimensional gradient structure automatic design method and device to control the controllable loading of the density distribution of the multi-dimensional gradient structure. Summary of the invention

[0004] In view of this, the present invention proposes a multi-dimensional gradient structure automatic design method and device. By constructing a multi-dimensional gradient structure model and dividing it into equal volume distribution blocks that meet the multi-dimensional gradient distribution conditions in the axial, radial and circumferential directions, and accurately simulating the behavior of the multi-dimensional gradient structure during loading in finite element analysis, controllable loading is achieved by controlling the density distribution of the multi-dimensional gradient structure.

[0005] The present invention provides a multi-dimensional gradient structure automatic design method, the method comprising:

[0006] Constructing a multidimensional gradient structure model, taking the center of the bottom surface of the multidimensional gradient structure model as the coordinate origin, dividing the multidimensional gradient structure model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks satisfies the multidimensional gradient distribution conditions in the axial, radial and circumferential directions;

[0007] Importing the multi-dimensional gradient structure model after distribution block division into a finite element processing module to generate a finite element input file with different density gradient distributions;

[0008] All finite element input files are input into the Ls-dyna solver for batch calculation, and the structural response data file of each multidimensional gradient structure model during the loading process is obtained. The side waveform of the multidimensional gradient structure model is regulated to realize the automatic design of the multidimensional gradient structure, wherein the structural response data file includes the particle velocity curve and the strain rate curve of the grid node.

[0009] On the basis of the above technical solution, preferably, dividing the multi-dimensional structural model into a plurality of distribution blocks of equal volume specifically includes:

[0010] The multi-dimensional gradient structure model is cut multiple times along the horizontal direction, the vertical direction of the center of the circle, and the concentric circle direction to obtain multiple distribution blocks of equal volume.

[0011] On the basis of the above technical solution, preferably, the volume expression of the distribution block is:

[0012]

[0013] in, V 3 represents the volume of the distribution block, r j It means that the multi-dimensional gradient structure model is cut along the concentric circle direction. j The radius of the concentric circles, h represents the height of the multidimensional gradient structure model, n represents the number of times the multidimensional gradient structure model is cut equally along the horizontal direction, m Indicates the number of times the multidimensional gradient structure model is cut along the vertical direction of the center of the circle.

[0014] More preferably, the density expression of the multidimensional gradient structure model is:

[0015]

[0016]

[0017]

[0018]

[0019] in, f 1( x ) represents the power function in the multidimensional gradient distribution condition, ρ 1 represents the density of the first material, Δ ρ represents the difference in density between the first material and the second material, a represents the characteristic scale of the multidimensional gradient distribution condition, f 2( x ) represents the exponential function in the multidimensional gradient distribution condition, c represents a random parameter group, f 3( x ) represents the trigonometric function in the multidimensional gradient distribution condition, F 1( r ) represents any one of a power function, an exponential function and a trigonometric function in the multidimensional gradient distribution condition, F 2( θ ) represents any one of a power function, an exponential function and a trigonometric function in the multidimensional gradient distribution condition, F 3( h ) represents a power function or exponential function in the multidimensional gradient distribution condition, r represents the radius corresponding to any point in the multidimensional gradient structure model, θ represents the rotation angle corresponding to any point in the multidimensional gradient structure model, h Represents the height corresponding to any point in the multidimensional gradient structure model.

[0020] More preferably, the generating of the finite element input file with different density gradient distributions specifically includes:

[0021] Obtaining the spatial coordinates of each distribution block, and calculating the density value of each distribution block according to the multi-dimensional gradient distribution condition, the spatial coordinates and the random parameter group;

[0022] The density value and spatial coordinate of each distribution block are saved in a text file, and the density values ​​in the text file are batch-replaced into the finite element input file to generate a finite element input file with different density gradient distributions.

[0023] More preferably, the generating of the finite element input file with different density gradient distributions specifically includes:

[0024] Obtaining the spatial coordinates of each distribution block, and calculating the density value of each distribution block according to the multi-dimensional gradient distribution condition, the spatial coordinates and the random parameter group;

[0025] The density value and spatial coordinate of each distribution block are saved in a text file, and the density values ​​in the text file are batch-replaced into the finite element input file to generate a finite element input file with different density gradient distributions.

[0026] More preferably, the random parameter group includes a first random seed value in a value range corresponding to a power function in the multidimensional gradient distribution condition and a second random seed value in a value range corresponding to an exponential function and a trigonometric function in the multidimensional gradient distribution condition.

[0027] More preferably, the finite element input file includes mesh nodes, material properties, boundary conditions, loads and analysis control parameters of the multi-dimensional gradient structure model.

[0028] In a second aspect of the present application, a multi-dimensional gradient structure automatic design device is provided, the multi-dimensional gradient structure automatic design device comprises a structure segmentation module, a gradient output module and a model optimization module, wherein:

[0029] The structural segmentation module is used to construct a multidimensional gradient structural model, taking the bottom center of the multidimensional gradient structural model as the coordinate origin, and dividing the multidimensional gradient structural model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks satisfies the multidimensional gradient distribution conditions in the axial, radial and circumferential directions;

[0030] The gradient output module is used to import the multi-dimensional gradient structure model after the distribution block division into the finite element processing module to generate a finite element input file with different density gradient distributions;

[0031] The model optimization module is used to input all finite element input files into the Ls-dyna solver for batch calculation, obtain the structural response data file of each multidimensional gradient structure model during the loading process, and regulate the side waveform of the multidimensional gradient structure model to realize the automatic design of the multidimensional gradient structure, wherein the structural response data file includes the particle velocity curve and strain rate curve of the grid node.

[0032] In a third aspect of the present application, an electronic device is provided, comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory.

[0033] The multi-dimensional gradient structure automatic design method and device provided by the present invention have the following beneficial effects compared with the prior art:

[0034] (1) By constructing a multidimensional gradient structure model and dividing it into equal-volume distribution blocks that satisfy the multidimensional gradient distribution conditions in the axial, radial and circumferential directions, the internal density of the gradient structure is precisely controlled so that the gradient structure has specific mechanical properties in different directions. At the same time, the finite element input file with different density gradient distributions is generated by the finite element processing module. The behavior of the gradient structure during loading can be accurately simulated in the finite element analysis, and controllable loading is achieved by controlling the density distribution of the multidimensional gradient structure, thereby improving the accuracy and reliability of the simulation results, and obtaining the response data of the gradient structure during loading, thereby regulating the side waveform of the gradient structure, and realizing the automatic design and optimization of the multidimensional gradient structure, so as to achieve the purpose of improving the controllable stress-strain rate loading range of the multidimensional gradient structure.

[0035] (2) By obtaining the spatial coordinates of each distribution block and calculating the density value of each distribution block according to the multi-dimensional gradient distribution conditions, spatial coordinates and random parameter groups, the internal density gradient of the model can be precisely controlled, so that the finite element model can more accurately reflect the density changes in the actual structure, and improve the authenticity and accuracy of the simulation results. The calculated density value and spatial coordinates of each distribution block are saved in a text file and replaced in batches into the finite element input file to generate finite element models with different density gradient distributions. This can more carefully simulate the heterogeneity and gradient characteristics of the material in finite element analysis, improve the simulation accuracy and the credibility of the results. At the same time, the batch replacement method is used to automatically insert the density value into the finite element input file, which improves the efficiency of data processing. By introducing a random parameter group, multiple finite element models with different density gradient distributions can be quickly generated, which provides convenience for parametric research and optimization design.

[0036] (3) The meshing unit assigns corresponding values ​​to the distribution blocks and material parameters, and accurately meshes the multidimensional gradient structure model according to the spatial position of each distribution block and the Lagrangian grid, so as to ensure the spatial accuracy of the model and help improve the accuracy of finite element analysis. Through the coordinated work of parameter addition and meshing units, the structural model with multidimensional gradient density distribution can be accurately modeled. At the same time, the generated finite element input file can accurately simulate the response of the multidimensional gradient structure under various working conditions, thereby improving the reliability of the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 A schematic diagram of a process flow of a multi-dimensional gradient structure automated design method provided by the present invention;

[0039] Figure 2 A three-dimensional schematic diagram of the multi-dimensional gradient structure model provided by the present invention;

[0040] Figure 3 A schematic diagram of the distribution of the power function, exponential function and three-part function provided by the present invention;

[0041] Figure 4 A schematic diagram of a multidimensional gradient structure model under different density gradients provided by the present invention;

[0042] Figure 5 Schematic diagram of density distribution of two different combinations of gradient structures provided by the present invention;

[0043] Figure 6 Part of the simulation result diagram of the multi-dimensional gradient structure model provided by the present invention;

[0044] Figure 7 A schematic diagram of the structure of the multi-dimensional gradient structure automatic design device provided by the present invention;

[0045] Figure 8 This is a schematic structural diagram of an electronic device provided by the present invention.

[0046] Explanation of the accompanying drawings: 1. Multi-dimensional gradient structure automatic design device; 11. Structure segmentation module; 12. Gradient output module; 13. Model optimization module; 2. Electronic device; 21. Processor; 22. Communication bus; 23. User interface; 24. Network interface; 25. Memory. DETAILED DESCRIPTION

[0047] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] The present invention discloses a multi-dimensional gradient structure automatic design method, referring to Figure 1 , the steps of the method include S1~S3.

[0049] Step S1, constructing a multidimensional gradient structure model, taking the bottom center of the multidimensional gradient structure model as the coordinate origin, dividing the multidimensional gradient structure model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks satisfies the multidimensional gradient distribution conditions in the axial, radial and circumferential directions.

[0050] In this step, if Figure 2 As shown, the multi-dimensional gradient structure model is cut multiple times along the horizontal direction, the vertical direction of the center of the circle, and the concentric circle direction to obtain multiple distribution blocks of equal volume.

[0051] Furthermore, a multi-dimensional gradient structure model was constructed using 3D CAD software and divided into several small blocks of equal volume along concentric circles. A cylindrical model was established using CAD software Solidworks, where the cylinder radius is r , Gao Wei h , the volume of the multidimensional gradient structure model is:

[0052]

[0053] In order to obtain several small pieces of equal volume, the cylinder is cut vertically, horizontally and concentrically along the center of the circle. First, cut at equal distances along the horizontal direction. n The volume of each block is:

[0054]

[0055] The spacing between each block is h / m ; Next, cut vertically and equidistantly along the axis m The volume of each block is:

[0056]

[0057] Each piece has an angle of 360° / 2 m ; Finally, cut vertically along the concentric circles k The radius of each concentric circle cut is , the volume of each piece is

[0058]

[0059] in, V 3 represents the volume of the distribution block, r j It means that the multi-dimensional gradient structure model is cut along the concentric circle direction. j The radius of the concentric circles, h Represents the height of the multidimensional gradient structure model, n Represents the number of equally spaced cuts of the multidimensional gradient structure model along the horizontal direction, m It indicates the number of times the multidimensional gradient structure model is cut along the vertical direction of the circle center. It is worth noting that the cutting order in this step has no effect on the block effect.

[0060] In one example, the density of the first material is ρ 1. The density of the second material is ρ 2, ρ 1< ρ 2. The established multi-dimensional gradient structure model has an arbitrary distribution of block density inside ρ 0 Satisfied ρ 1< ρ 0< ρ 2, Δ ρ=ρ 2- ρ 1, with random parameter set c The density expression of the multidimensional gradient structure model is different.

[0061]

[0062]

[0063]

[0064] See also Figure 3 and Figure 4 , Figure 3 This is a distribution diagram of power function, exponential function and three-function function. Figure 4 The figure is a schematic diagram of the multidimensional gradient structure model under different density gradients. In addition to the monotonically increasing density gradient along the impact direction, the power function distribution and exponential distribution can be selected, while the radial and circumferential directions can satisfy the power function, exponential function and three-element function distribution. In summary, there are 18 types of multidimensional gradient structure models. Assume that the coordinates of any point inside ( r 1, θ 1, h 1), respectively represent the radius, rotation angle and height of the point, then the density expression of the multidimensional gradient structure model is:

[0065]

[0066] in, f 1( x ) represents the power function in the multidimensional gradient distribution condition, ρ 1 represents the density of the first material, Δ ρ represents the difference in density between the first material and the second material, a The characteristic scale representing the multidimensional gradient distribution condition, f 2( x ) represents the exponential function in the multidimensional gradient distribution condition, c represents a random parameter group, f 3( x ) represents the trigonometric function in the multidimensional gradient distribution condition, F 1( r) represents any one of the power function, exponential function and trigonometric function in the multidimensional gradient distribution condition, F 2( θ ) represents any one of the power function, exponential function and trigonometric function in the multidimensional gradient distribution condition, F 3( h ) represents the power function or exponential function in the multidimensional gradient distribution condition, r represents the radius corresponding to any point in the multidimensional gradient structure model, θ represents the rotation angle corresponding to any point in the multidimensional gradient structure model, h Represents the height corresponding to any point in the multidimensional gradient structure model.

[0067] Step S2, importing the multi-dimensional gradient structure model after the distribution block division into a finite element processing module to generate a finite element input file with different density gradient distributions.

[0068] In this step, the finite element processing module includes a parameter adding unit, a meshing unit and a file generating unit, wherein the parameter adding unit is used to batch add the material parameters of the corresponding distribution blocks according to the density value of each distribution block; the meshing unit is used to assign corresponding values ​​between the distribution blocks and the material parameters, and mesh the multidimensional gradient structure model according to the spatial position of each distribution block and the Lagrangian grid; the file generating unit is used to generate a finite element input file corresponding to the distribution block. The finite element input file includes the mesh nodes, material properties, boundary conditions, load parameters and analysis control parameters of the multidimensional gradient structure model.

[0069] In one example, the designed multidimensional gradient structure model is assigned to the finite element software Ls-dyna for calculation. Create a new project in the commercial finite element software Ansys Workbench, open "Explicit Dynamics", and create an explicit dynamics analysis system module. The multidimensional gradient structure model is imported into the "Geometry" module, and the model size unit is mm; in the "Engineering Data" module, the material parameters of each distribution block are added in batches according to the density of S2. In the "model" module, the physical model of the multidimensional gradient structure model is post-processed. According to the spatial position of each distribution block, the plug-in is used to realize the rapid corresponding assignment of distribution block-material parameters and divide it using Lagrangian grid, and the grid unit size is 1E-4m.

[0070] By obtaining the spatial coordinates of each distribution block and calculating the density value of each distribution block according to the multi-dimensional gradient distribution conditions, spatial coordinates and random parameter groups, the density gradient inside the model can be precisely controlled. This enables the finite element model to more accurately reflect the density changes in the actual structure, improve the authenticity and accuracy of the simulation results, save the calculated density values ​​and spatial coordinates of each distribution block to a text file, and replace them in batches into the finite element input file to generate finite element models with different density gradient distributions, which can more carefully simulate the heterogeneity and gradient characteristics of the material in finite element analysis, improve the simulation accuracy and the credibility of the results, and use the batch replacement method to automatically insert the density value into the finite element input file, which improves the efficiency of data processing. By introducing random parameter groups, multiple finite element models with different density gradient distributions can be quickly generated, which provides convenience for parametric research and optimization design.

[0071] This step also includes steps S21 to S22.

[0072] Step S21, obtaining the spatial coordinates of each distribution block, and calculating the density value of each distribution block according to the multi-dimensional gradient distribution condition, the spatial coordinates and the random parameter group.

[0073] In this step, the random parameter group includes a first random seed value in a value range corresponding to a power function in a multidimensional gradient distribution condition and a second random seed value in a value range corresponding to an exponential function and a trigonometric function in a multidimensional gradient distribution condition.

[0074] Step S22, saving the density value and spatial coordinates of each distribution block into a text file, and replacing the density values ​​in the text file into the finite element input file in batches to generate a finite element input file with different density gradient distributions.

[0075] Furthermore, the initial velocity is assigned to the multidimensional gradient structure model, the calculation time is set to 1E-6 s, the time step is set to 1E-8 s, and the hourglass coefficient and energy cycle are set to the system default. After completing the above settings, click "Generate MAPDL File" in the "ExplicitDynamics" module to obtain the ".k" file, which is the finite element input file. The ".k" file is an input file format used by the LS-DYNA solver. It contains all the information that defines the finite element model, including nodes, elements, material properties, boundary conditions, loads, and analysis control parameters.

[0076] By obtaining the spatial coordinates of each small block of the multidimensional gradient structure model ( r , z , theta), these coordinates represent the radius, height, and rotation angle of each small block in space, and the coordinates will be used for subsequent density calculations. The 18 sets of density expressions of the multidimensional gradient structure model are written as calculation functions. c Set to a random parameter group to control different density gradients. It is worth noting that for the power function c 1∈(0,+∞), for exponential and trigonometric functions c 2∈(1,+∞), and the random number generation is based on a preset seed value to ensure the repeatability of the results. r , z , theta ), using different c 1. c 2 combinations, calculate 18× c 1 value× c 2. Set the density value and save the result to a text file. Use the random density function just generated to assign density to each block of the gradient structure to achieve a multi-dimensional density gradient structure.

[0077] Save the calculated density values ​​and the corresponding coordinate data into a single text file. The contents of the file are organized into a table, with each row corresponding to the coordinates of a point and its 18 density values. c 1. c 2 The corresponding density values ​​are batch replaced to each small density value of the multidimensional gradient structure model in the ".k" file generated in the previous step. Through this step, the density is replaced to the ".k" file for the next batch calculation. Finally, a series of different c 1. c 2 combinations, multidimensional gradient structure models with different multidimensional density gradient distributions, and corresponding calculated ".k" files. This file can be used as subsequent analysis or data input to ensure data integrity and repeatability. Figure 5 As shown, this is a schematic diagram of the gradient structure density distribution of two different combinations.

[0078] The meshing unit assigns corresponding values ​​to the distribution blocks and material parameters, and accurately meshes the multidimensional gradient structure model according to the spatial position of each distribution block and the Lagrangian grid, so as to ensure the spatial accuracy of the model and help improve the accuracy of finite element analysis. Through the collaborative work of parameter addition and meshing units, the gradient structure model with multidimensional gradient density distribution can be accurately modeled. At the same time, the generated finite element input file can accurately simulate the response of the gradient structure under various working conditions, thereby improving the reliability of the simulation results.

[0079] Step S3, input all finite element input files into the Ls-dyna solver for batch calculation, obtain the structural response data file of each multidimensional gradient structure model during the loading process, and adjust the side waveform of the multidimensional gradient structure model to realize the automatic design of the multidimensional gradient structure, wherein the structural response data file includes the particle velocity curve and strain rate curve of the grid node.

[0080] Open each d3plot file in the post-processing software Ls-prepost, use the coordinate search function of the software to obtain the grid node information of the required position, and extract the particle velocity curve and strain rate curve of the node. By adjusting the mathematical expression and parameters of the multi-dimensional gradient structure model, the loading and side waveform can be adjusted.

[0081] like Figure 6 As shown in the figure, from left to right are the schematic diagram of the two points of capturing the particle velocity curve, the particle velocity curves of the ten random multi-dimensional gradient expression calculation results shown in point 1, and the particle velocity curves of the ten random multi-dimensional gradient expression calculation results shown in point 2. The comparison of the particle velocity curve at point 1 and the particle velocity curve at point 2 proves that the above multi-dimensional gradient structure model can achieve controllable loading on the side.

[0082] By constructing a multidimensional gradient structure model and dividing it into equal-volume distribution blocks that satisfy the multidimensional gradient distribution conditions in the axial, radial and circumferential directions, precise control of the internal density of the gradient structure is achieved so that the gradient structure has specific mechanical properties in different directions. At the same time, the finite element input file with different density gradient distributions is generated through the finite element processing module. The behavior of the gradient structure during loading can be accurately simulated in the finite element analysis, and controllable loading is achieved by controlling the density distribution of the multidimensional gradient structure, thereby improving the accuracy and reliability of the simulation results, and obtaining the response data of the gradient structure during loading, thereby regulating the side waveform of the gradient structure, realizing the automatic design and optimization of the gradient structure, improving the design efficiency and reducing manual intervention.

[0083] Based on the above method, the present application embodiment discloses a multi-dimensional gradient structure automatic design device, referring to Figure 7 The multi-dimensional gradient structure automatic design device 1 comprises a structure segmentation module 11, a gradient output module 12 and a model optimization module 13, wherein:

[0084] The structure segmentation module 11 is used to construct a multidimensional gradient structure model, taking the bottom center of the multidimensional gradient structure model as the coordinate origin, and dividing the multidimensional gradient structure model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks in the axial, radial and circumferential directions all meet the multidimensional gradient distribution conditions;

[0085] The gradient output module 12 is used to import the multi-dimensional gradient structure model after the distribution block division into the finite element processing module to generate a finite element input file with different density gradient distributions;

[0086] The model optimization module 13 is used to input all finite element input files into the Ls-dyna solver for batch calculation, obtain the structural response data file of each multidimensional gradient structure model during the loading process, and regulate the side waveform of the multidimensional gradient structure model to realize the automatic design of the multidimensional gradient structure, wherein the structural response data file includes the particle velocity curve and strain rate curve of the grid node.

[0087] In one example, the structure cutting module 11 is used to cut the multi-dimensional gradient structure model multiple times along the horizontal direction, the vertical direction of the center of the circle, and the concentric circle direction to obtain multiple distribution blocks of equal volume.

[0088] In one example, the volume expression of the distribution block is:

[0089]

[0090] in, V 3 represents the volume of the distribution block, r j It means that the multi-dimensional gradient structure model is cut along the concentric circle direction. j The radius of the concentric circles, h Represents the height of the multidimensional gradient structure model, n Represents the number of equally spaced cuts of the multidimensional gradient structure model along the horizontal direction, m Represents the number of times the multidimensional gradient structure model is cut vertically along the center of the circle.

[0091] In one example, the density expression of the multidimensional gradient structure model is:

[0092]

[0093]

[0094]

[0095]

[0096] in, f 1( x ) represents the power function in the multidimensional gradient distribution condition, ρ 1 represents the density of the first material, Δ ρ represents the difference in density between the first material and the second material, a The characteristic scale representing the multidimensional gradient distribution condition, f2( x ) represents the exponential function in the multidimensional gradient distribution condition, c represents a random parameter group, f 3( x ) represents the trigonometric function in the multidimensional gradient distribution condition, F 1( r ) represents any one of the power function, exponential function and trigonometric function in the multidimensional gradient distribution condition, F 2( θ ) represents any one of the power function, exponential function and trigonometric function in the multidimensional gradient distribution condition, F 3( h ) represents the power function or exponential function in the multidimensional gradient distribution condition, r represents the radius corresponding to any point in the multidimensional gradient structure model, θ represents the rotation angle corresponding to any point in the multidimensional gradient structure model, h Represents the height corresponding to any point in the multidimensional gradient structure model.

[0097] In one example, the gradient output module 12 is used to obtain the spatial coordinates of each distribution block, and calculate the density value of each distribution block based on the multidimensional gradient distribution conditions, spatial coordinates and random parameter group; the density value and spatial coordinates of each distribution block are saved in a text file, and the density values ​​in the text file are batch replaced into the finite element input file to generate a finite element input file with different density gradient distributions.

[0098] In one example, the finite element processing module includes a parameter adding unit, a meshing unit, and a file generating unit, wherein:

[0099] The parameter adding unit is used to batch add material parameters of corresponding distribution blocks according to the density value of each distribution block;

[0100] The grid division unit is used to assign corresponding values ​​between distribution blocks and material parameters, and to grid the multi-dimensional gradient structure model according to the spatial position of each distribution block and the Lagrangian grid;

[0101] The file generation unit is used to generate a finite element input file corresponding to the distribution block.

[0102] In one example, the random parameter group includes a first random seed value in a value range corresponding to a power function in a multidimensional gradient distribution condition, and a second random seed value in a value range corresponding to an exponential function and a trigonometric function in a multidimensional gradient distribution condition.

[0103] In one example, the finite element input file includes mesh nodes, material properties, boundary conditions, load parameters, and analysis control parameters of the multi-dimensional gradient structure model.

[0104] See also Figure 8 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 8 As shown, the electronic device 2 may include: at least one processor 21 , at least one network interface 24 , a user interface 23 , a memory 25 , and at least one communication bus 22 .

[0105] The communication bus 22 is used to realize the connection and communication between these components.

[0106] The user interface 23 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 23 may also include a standard wired interface and a wireless interface.

[0107] The network interface 24 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0108] Among them, the processor 21 may include one or more processing cores. The processor 21 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 25, and calling data stored in the memory 25. Optionally, the processor 21 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 21 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 21, and it can be implemented separately through a chip.

[0109] The memory 25 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 25 includes a non-transitory computer-readable storage medium. The memory 25 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 25 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 25 may optionally be at least one storage device located away from the aforementioned processor 21. As Figure 8 As shown, the memory 25 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a multi-dimensional gradient structure automatic design method.

[0110] exist Figure 8 In the electronic device 2 shown, the user interface 23 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 21 can be used to call an application program for a multi-dimensional gradient structure automatic design method stored in the memory 25. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0111] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the technical field that are not recorded in the present disclosure.

[0112] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-dimensional gradient structure automated design method, characterized in that: The method comprises: Constructing a multidimensional gradient structure model, taking the center of the bottom surface of the multidimensional gradient structure model as the coordinate origin, dividing the multidimensional gradient structure model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks satisfies the multidimensional gradient distribution conditions in the axial, radial and circumferential directions; Importing the multi-dimensional gradient structure model after distribution block division into a finite element processing module to generate a finite element input file with different density gradient distributions; All finite element input files are input into the Ls-dyna solver for batch calculation, and the structural response data file of each multidimensional gradient structure model during the loading process is obtained, and the side waveform of the multidimensional gradient structure model is regulated, wherein the structural response data file includes the particle velocity curve and the strain rate curve of the grid node.

2. The method according to claim 1, characterized in that The step of dividing the multi-dimensional structural model into a plurality of distribution blocks of equal volume specifically includes: The multi-dimensional gradient structure model is cut multiple times along the horizontal direction, the vertical direction of the center of the circle, and the concentric circle direction to obtain multiple distribution blocks of equal volume.

3. The method according to claim 2, characterized in that The volume expression of the distribution block is: ； in, V 3 represents the volume of the distribution block, r j It means that the multi-dimensional gradient structure model is cut along the concentric circle direction. j The radius of the concentric circles, h represents the height of the multidimensional gradient structure model, n represents the number of times the multidimensional gradient structure model is cut equally along the horizontal direction, m Indicates the number of times the multidimensional gradient structure model is cut along the vertical direction of the center of the circle.

4. The method according to claim 1, characterized in that The density expression of the multidimensional gradient structure model is: ； ； ； ； in, f 1( x ) represents the power function in the multidimensional gradient distribution condition, ρ 1 represents the density of the first material, Δ ρ represents the difference in density between the first material and the second material, a represents the characteristic scale of the multidimensional gradient distribution condition, f 2( x ) represents the exponential function in the multidimensional gradient distribution condition, c represents a random parameter group, f 3( x ) represents the trigonometric function in the multidimensional gradient distribution condition, F 1( r ) represents any one of a power function, an exponential function and a trigonometric function in the multidimensional gradient distribution condition, F 2( θ ) represents any one of a power function, an exponential function and a trigonometric function in the multidimensional gradient distribution condition, F 3( h ) represents a power function or exponential function in the multidimensional gradient distribution condition, r represents the radius corresponding to any point in the multidimensional gradient structure model, θ represents the rotation angle corresponding to any point in the multidimensional gradient structure model, h Represents the height corresponding to any point in the multidimensional gradient structure model.

5. The method according to claim 4, characterized in that The generating of the finite element input file with different density gradient distributions specifically includes: Obtaining the spatial coordinates of each distribution block, and calculating the density value of each distribution block according to the multi-dimensional gradient distribution condition, the spatial coordinates and the random parameter group; The density value and spatial coordinate of each distribution block are saved in a text file, and the density values ​​in the text file are batch-replaced into the finite element input file to generate a finite element input file with different density gradient distributions.

6. The method according to claim 5, characterized in that The finite element processing module includes a parameter adding unit, a meshing unit and a file generating unit, wherein: The parameter adding unit is used to batch add material parameters of corresponding distribution blocks according to the density value of each distribution block; The grid division unit is used to assign corresponding values ​​between the distribution blocks and material parameters, and to perform grid division on the multi-dimensional gradient structure model according to the spatial position of each distribution block and the Lagrangian grid; The file generating unit is used to generate the finite element input file corresponding to the distribution block.

7. The method according to claim 5, characterized in that The random parameter group includes a first random seed value in a value range corresponding to a power function in the multidimensional gradient distribution condition and a second random seed value in a value range corresponding to an exponential function and a trigonometric function in the multidimensional gradient distribution condition.

8. The method according to claim 1, characterized in that The finite element input file includes the mesh nodes, material properties, boundary conditions, load parameters and analysis control parameters of the multi-dimensional gradient structure model.

9. A multi-dimensional gradient structure automatic design device, characterized in that: The multi-dimensional gradient structure automatic design device (1) comprises a structure segmentation module (11), a gradient output module (12) and a model optimization module (13), wherein: The structural segmentation module (11) is used to construct a multidimensional gradient structural model, taking the bottom center of the multidimensional gradient structural model as the coordinate origin, and dividing the multidimensional gradient structural model into a plurality of distribution blocks of equal volume, wherein the density of the distribution blocks in the axial, radial and circumferential directions all meets the multidimensional gradient distribution conditions; The gradient output module (12) is used to import the multi-dimensional gradient structure model after the distribution block division into the finite element processing module to generate a finite element input file with different density gradient distributions; The model optimization module (13) is used to input all finite element input files into the Ls-dyna solver for batch calculation, obtain the structural response data file of each multidimensional gradient structure model during the loading process, and regulate the side waveform of the multidimensional gradient structure model to realize the automatic design of the multidimensional gradient structure, wherein the structural response data file includes the particle velocity curve and the strain rate curve of the grid node.

10. An electronic device, characterized in that: The electronic device (2) comprises a processor (21), a memory (25), a user interface (23) and a network interface (24), wherein the memory (25) is used to store instructions, the user interface (23) and the network interface (24) are used to communicate with other devices, and the processor (21) is used to execute the instructions stored in the memory (25) so that the electronic device (2) executes the method according to any one of claims 1 to 8.

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