A Parametric Modeling Method, Device, Equipment and Medium for Multi-Scale Lattice Structures

Abstract

The present invention relates to the technical field of structural modeling, and particularly relates to a multi-scale lattice structure parameterized modeling method, device, equipment and medium. The method includes: modeling the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model; importing the first geometric model into COMSOL software to adjust the size variables of the first geometric model to generate a second geometric model; wherein, the second geometric model is in the.stl format, and the.stl format second geometric model is generated by outputting the command stream program of the first geometric model and rewriting the command stream program; importing the second geometric model into MATLAB software, and identifying the constraint surface and the loading surface of the second geometric model through MATLAB software; performing finite element analysis on the second geometric model by MATLAB software according to the constraint surface and the loading surface to obtain the stress distribution of the multi-scale lattice structure.

Description

Technical Field

[0001] The present invention relates to the technical field of structural modeling, and particularly relates to a multi-scale lattice structure parametric modeling method, device, equipment and medium. Background Art

[0002] With the development of additive manufacturing technology, additive manufacturing lattice structures have received extensive attention. They have characteristics such as light weight, high specific strength, high specific stiffness, and strong designability. Therefore, lattice structures have become a new choice in the field of aerospace research and are currently widely used in parts such as cabin partitions.

[0003] Due to the layer-by-layer stacking manufacturing process, there are many uncertainties affecting the performance of lattice structures. In order to improve the reliability of lattice structures, it is necessary to analyze the stress distribution of additive manufacturing lattice structures and carry out geometric modeling and finite element analysis.

[0004] Traditional modeling and simulation methods require manual input of parameters such as rod diameter, rod length, elastic modulus, Poisson's ratio, etc., which is time-consuming. In order to improve the analysis efficiency and reduce the operation difficulty of staff, it is crucial to seek high-efficiency modeling and simulation methods. Summary of the Invention

[0005] The purpose of the present invention is to provide a multi-scale lattice structure parametric modeling method, device, equipment and medium, which can solve the technical problem of low efficiency in lattice structure modeling and simulation.

[0006] To solve the above technical problem, an embodiment of the present invention provides a multi-scale lattice structure parametric modeling method, including the following steps:

[0007] Model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure;

[0008] Import the first geometric model into COMSOL software, and adjust the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the step of adjusting the first dimension variable to generate a command stream program and re-writing the command stream program according to the second dimension variable;

[0009] Import the second geometric model into MATLAB software, and identify the constraint surface and loading surface of the second geometric model through MATLAB software;

[0010] Perform finite element analysis on the second geometric model through MATLAB software according to the constraint surface and loading surface to obtain the stress distribution of the multi-scale lattice structure.

[0011] Optionally, the multi-scale lattice structure is modeled by SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure, including:

[0012] Model using SOLIDWORKS software according to the geometric configuration of the multi-scale lattice structure, and during the modeling process, use the equation function within SOLIDWORKS software to define the first size variable of the multi-scale lattice structure to generate the first geometric model.

[0013] Optionally, importing the first geometric model into COMSOL software and adjusting the first size variable of the first geometric model to a second size variable by COMSOL software to generate a second geometric model of the multi-scale lattice structure, including:

[0014] Use the combined module COMSOL Multiphysics of SOLIDWORKS software and COMSOL software to import the first geometric model into COMSOL software;

[0015] Import the first size variable of the defined multi-scale lattice structure into the global definition parameter module of COMSOL software, and generate a command stream file for the steps of setting parameters in the global definition parameter module;

[0016] Rewrite the command stream program to adjust the first size variable of the first geometric model to a second size variable to generate a second geometric model of the multi-scale lattice structure.

[0017] Optionally, identifying the constraint surface and loading surface of the second geometric model by MATLAB software, including:

[0018] Obtain sample geometric models of the multi-scale lattice structure with numbers for several constraint surfaces and loading surfaces, and obtain images of the constraint surfaces and loading surfaces of each sample geometric model; where each image contains the number corresponding to the constraint surface or loading surface;

[0019] Use the images of the constraint surfaces and loading surfaces of several sample geometric models to train an image recognition model, and input the images of the constraint surfaces and loading surfaces of the second geometric model into the image recognition model to obtain the numbers of the constraint surfaces and loading surfaces of the second geometric model, so as to identify the constraint surfaces and loading surfaces of the second geometric model.

[0020] Optionally, after obtaining the stress distribution of the multi-scale lattice structure, it further includes:

[0021] Construct a limit state function of the multi-scale lattice structure according to the stress distribution; where the limit state function is used to describe whether the multi-scale lattice structure is in a failure state;

[0022] A surrogate model with a Gaussian process model as the limit state function uses the parameter variables that affect the limit state function value of the multi-scale lattice structure as sampling points. Through the adaptive line sampling method, sampling is carried out along the important direction, and the Gaussian process model is used to predict the limit state function value at the sampling points.

[0023] Determine the sampling points that make the multi-scale lattice structure in a failure state according to the limit state function value as failure samples, and determine the failure probability of the multi-scale lattice structure according to the number of failure samples.

[0024] An embodiment of the present invention also provides a multi-scale lattice structure parametric modeling device, including:

[0025] A first model generation module for modeling the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure.

[0026] A second model generation module for importing the first geometric model into COMSOL software and adjusting the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the steps of adjusting the first dimension variable to generate a command flow program and re-writing the command flow program according to the second dimension variable.

[0027] A model identification module for importing the second geometric model into MATLAB software and identifying the constraint surface and loading surface of the second geometric model through MATLAB software.

[0028] A model analysis module for performing finite element analysis on the second geometric model through MATLAB software according to the constraint surface and loading surface to obtain the stress distribution of the multi-scale lattice structure.

[0029] An embodiment of the present invention also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, instructions executable by the at least one processor are stored in the memory, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the above multi-scale lattice structure parametric modeling method.

[0030] An embodiment of the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above multi-scale lattice structure parametric modeling method is implemented.

[0031] The multi-scale lattice structure parameterization modeling method provided by the present invention has at least the following beneficial effects:

[0032] MATLAB can be used for finite element analysis, and then reliability analysis can be carried out using the solution results. Therefore, the present invention uses MATLAB software to model the multi-scale lattice structure, and obtains the stress distribution of the multi-scale lattice structure through finite element analysis, so as to analyze the reliability of the multi-scale lattice structure. Specifically, by combining the three software of SOLIDWORKS, COMSOL, and MATLAB, and re-editing the command flow file of COMSOL, the reconstruction of the model in SOLIDWORKS can be completed, realizing the parameterization modeling and simulation of the multi-scale lattice structure, reducing the operation difficulty and duration. Then, finite element analysis of the lattice structure is carried out through MATLAB, providing strong support for the reliability analysis of the lattice structure and improving the actual efficiency.

[0033] Considering the complex configuration of the lattice structure, there will be a situation where the loading surface and the constraint surface cannot be numbered under multi-scale changes. Therefore, in order to facilitate the parameterized finite element analysis of the lattice structure in MATLAB, the present invention improves the lattice structure in advance. Specifically, first, a first geometric model of the multi-scale lattice structure is modeled by SOLIDWORKS software, and then imported into COMSOL software. By changing the size variables of the first geometric model, a second geometric model of the multi-scale lattice structure is generated. Then, it is imported into MATLAB software for numbering the constraint surface and the loading surface, realizing the modeling and simulation of the multi-scale lattice structure by MATLAB software. Among them, the model in the ".stl" format in MATLAB software can be used for finite element analysis. Therefore, the present invention generates a command flow program by using COMSOL software according to the steps of adjusting the first size variable, and re-writes the command flow program according to the second size variable to generate a second geometric model in the ".stl" format. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] One or more embodiments are exemplarily illustrated by the pictures in the corresponding drawings, and these exemplary illustrations do not constitute limitations on the embodiments.

[0035] Figure 1 is a flow chart of a multi-scale lattice structure parameterization modeling method provided according to an embodiment of the present invention Figure 1 ;

[0036] Figure 2 is a flow chart of a multi-scale lattice structure parameterization modeling method provided according to an embodiment of the present invention Figure 2 ;

[0037] Figure 3It is a schematic diagram of a three-dimensional geometric model of a lattice structure provided according to an embodiment of the present invention;

[0038] Figure 4 It is a schematic diagram of parametric modeling of a lattice structure unit cell provided according to an embodiment of the present invention;

[0039] Figure 5 It is a numbering diagram of a lattice structure unit cell and an identification diagram of the loading surface number of the overall lattice structure provided according to an embodiment of the present invention. Detailed implementation manners

[0040] To make the purposes, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be elaborated in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in the embodiments of the present invention, many technical details are provided for readers to better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed by the present invention can still be implemented. The division of the following embodiments is for convenience of description and should not constitute any limitation to the specific implementation manner of the present invention. The various embodiments can be combined and cited with each other on the premise of not contradicting each other.

[0041] An embodiment of the present invention relates to a parametric modeling method for a multi-scale lattice structure. The implementation details of the parametric modeling method for the multi-scale lattice structure in this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0042] The specific process of the parametric modeling method for the multi-scale lattice structure in this embodiment can be as Figure 1 shown, including:

[0043] Step 101, model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure.

[0044] Specifically, according to the geometric configuration of the multi-scale lattice structure, use SOLIDWORKS software for modeling. During the modeling process, use the equation function in SOLIDWORKS software to define the size variables of the multi-scale lattice structure, that is, the first size variables, such as rod diameter, rod length, etc., to generate the first geometric model. Among them, when performing finite element analysis in MATLAB, the MATLAB program will number each face of the additive manufacturing lattice structure. Due to the complex configuration of the additive manufacturing lattice structure, under multi-scale changes, there will be a situation where the loading surface and the constraint surface cannot be numbered. To facilitate parametric finite element analysis in MATLAB, improve the additive manufacturing lattice structure in advance, and add geometric bodies with a thickness of 0.05 mm to the loading surface and the constraint surface.

[0045] This step is used to determine the geometric configuration of the additive manufacturing lattice structure, implement dimensional parameterization within SOLIDWORKS, and propose improvements to the lattice configuration to achieve parametric modeling under subsequent multi-scale changes.

[0046] Step 102: Import the first geometric model into the COMSOL software, and adjust the first dimension variable of the first geometric model to the second dimension variable through the COMSOL software to generate the second geometric model of the multi-scale lattice structure. Among them, the second geometric model is in the.stl format, and the.stl format second geometric model is generated by the COMSOL software according to the step of adjusting the first dimension variable to generate a command flow program and re-writing the command flow program according to the second dimension variable.

[0047] Specifically, use the combined module COMSOL Multiphysics of the SOLIDWORKS software and the COMSOL software to import the first geometric model into the COMSOL software; import the dimension variables of the defined multi-scale lattice structure into the global definition parameter module of the COMSOL software, and change the dimension variables of the multi-scale lattice structure in the global definition parameter module (that is, adjust the first dimension variable of the first geometric model to the second dimension variable) to generate the second geometric model of the multi-scale lattice structure, realize the reconstruction of the model in SOLIDWORKS, that is, combine SOLIDWORKS and COMSOL to achieve the parameterization of the lattice model in COMSOL.

[0048] Step 103: Import the second geometric model into the MATLAB software, and identify the constraint surface and the loading surface of the second geometric model through the MATLAB software.

[0049] In specific implementation, the COMSOL Multiphysics with MATLAB module is a combined section of COMSOL and MATLAB, which can be used to combine the two software. Operations in COMSOL can generate a command stream program that can be run by MATLAB. By editing and changing the command stream program, the operations in COMSOL can be controlled. Using this module, in the global definition module of COMSOL, the steps of changing the lattice structure size are output to generate a command stream program, which is output as a program that can be run by MATLAB. To achieve secondary development of the software, that is, to reconstruct the lattice structure, the program is rewritten, and the size change is achieved through the program, that is, the re - modeling of the lattice structure. In MATLAB software, only models in the ".stl" format can be used for finite element analysis. Therefore, the command stream program is changed and written to write a program for saving the lattice structure model. Through a loop, the multi - scale lattice models are saved in the ".stl" format for finite element simulation and analysis. Based on this, the combination of the lattice structure in SOLIDWORKS, COMSOL, and MATLAB three software is completed, and the command stream program is recompiled to achieve the programmed modeling of the additive manufacturing lattice structure at multiple scales.

[0050] Next, complete the parametric simulation of the multi - scale lattice structure in MATLAB: When using MATLAB for finite element analysis, the ".stl" model needs to be imported. After importing the model, the MATLAB program will automatically number each face of the model to specify the constrained face and the loaded face. To achieve the finite element analysis of the multi - scale lattice structure, that is, to achieve parametric modeling and simulation, parametric constraints and loading need to be implemented.

[0051] In one example, due to the complex configuration of the additive manufacturing lattice structure, the automatic numbering will change. To solve this problem and achieve the simulation of the multi - scale lattice structure, an image recognition technology is proposed to perform image recognition on the numbers of the loaded face and the constrained face, and loading and constraint are carried out through the recognized numbers.

[0052] Specifically, obtain a sample geometric model of the multi - scale lattice structure with numbers on several constrained faces and loaded faces, and obtain the images of the constrained faces and loaded faces of each sample geometric model; where each image contains the numbers corresponding to the constrained face or the loaded face; use the images of the constrained faces and loaded faces of several sample geometric models to train an image recognition model, and input the images of the constrained faces and loaded faces of the second geometric model into the image recognition model to obtain the numbers of the constrained faces and loaded faces of the second geometric model, so as to identify the constrained faces and loaded faces of the second geometric model.

[0053] In specific implementation, first, the ".stl" model of the additive manufacturing lattice structure is automatically numbered, and the numbered output figure window is displayed; then a program is written to output the figure window as a picture, and the picture is cropped to crop out the numbers of the loading surface and the constraint surface, and the cropped picture is saved; 100 cropped pictures are placed in the Optical Character Recognition (OCR) Trainer section of MATLAB to train the pictures, and an image recognition program is written to output the numbers of the loading surface and the constraint surface.

[0054] Step 104, perform finite element analysis on the second geometric model according to the constraint surface and the loading surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

[0055] Specifically, the above image recognition program and the finite element analysis program are written into an article, and finite element analysis is performed using the recognized numbers to output the stress results and stress nephograms, realizing the joint simulation of the parametric modeling of the additive manufacturing lattice structure.

[0056] In one example, after realizing the parametric modeling of the lattice structure, an adaptive line sampling method is proposed to solve the reliability sensitivity, an approximate limit state function is obtained using the Gaussian process model, and the analysis results of the lattice structure are calculated through the global sensitivity index.

[0057] Specifically, based on the stress distribution of the multi-scale lattice structure, a limit state function of the multi-scale lattice structure is constructed; among them, the limit state function is used to describe whether the multi-scale lattice structure is in a failure state; using the Gaussian process model as the surrogate model of the limit state function, and using the parameter variables that affect the limit state function value of the multi-scale lattice structure as sampling points, sampling is performed along the important direction through the adaptive line sampling method, and the limit state function value at the sampling points is predicted using the Gaussian process model; according to the limit state function value, the sampling points that make the multi-scale lattice structure in a failure state are determined as failure samples, and according to the number of failure samples, the failure probability of the multi-scale lattice structure is determined.

[0058] In specific implementation, the input variables in the original space are defined as , in order to measure the influence of the input variables on the failure probability within the entire distribution range, the concept of global sensitivity is as follows:

[0059] ;

[0060] ;

[0061] In the formula, the input variable refers to the parameter variable that affects the limit state function, represents the a random variable , is the global sensitivity representing the failure probability is the failure probability when it is a certain value is an unbiased estimator of the global sensitivity is an estimator of the failure probability is the sample falling into the failure domain the estimator of the joint probability density function represents the mean value represents the joint probability density function of

[0062] The line sampling method is carried out in the standard normal space. The original space input variable is subjected to a coordinate transformation and transformed into the standard normal space, and the input variable in the standard normal space is defined as , and the limit state function is defined as . From the joint probability density function of the variables, samples are generated . Using existing technical means, the important direction in the standard normal space and the design point are solved. Through the corresponding vector transformation, a vector parallel to the unit important direction and passing through the sample point is obtained. The specific formula is as follows:

[0063] ;

[0064] In the formula, represents the dot product of and represents a vector parallel to , represents a vector perpendicular to .

[0065] The problem of solving the failure sample point is transformed into the problem of solving the intersection point of and the limit state function . Among them, represents the coefficient of variation represents the cumulative distribution function is the reliability index. The specific steps are as follows:

[0066] Given the coefficients three initial values , , and obtain the vector of the sample point .

[0067] From the formula , calculate the failure probability and the coefficient of variation

[0068] Perform three-point quadratic interpolation on three points to find the point .

[0069] Combine the above line sampling method with the Gaussian process model, and use the Gaussian process model to surrogate the limit state function , predict the intersection point through adaptive learning, and calculate the failure probability. Define the learning function of the Gaussian process model as follows

[0070] ;

[0071] In the formula represents the learning function represents the probability density of the Gaussian distribution with a mean of and a variance of , represents the estimated value of the limit state function by the Gaussian process model represents the variance of the Gaussian process model represents the mean of the Gaussian process model is the error tolerance used to control the width of the integration interval, and its value should be selected to be close to 10 - 100 times the function value at the intersection point .

[0072] The specific calculation steps of the adaptive line sampling method are as follows

[0073] Define the prediction sample pool , the initial training sample pool , use the performance function to calculate the response value , calculate the vector taken by the line sampling from , and calculate the intersection point corresponding to the initial training sample point

[0074] From the samples in the training sample pool and their corresponding limit state functions, train the Gaussian process model. According to the limit state function value of the prediction samples of the Gaussian process model and the variance of the Gaussian process model, when the learning function of the model reaches the stopping threshold , that is , output the result; otherwise, calculate the point with the smallest learning function in the samples, add it to the training sample pool, and continue to train the Gaussian process model. Among them, it is recommended that the stopping threshold​ The selection is 0.8 - 0.9.

[0075] When the model meets the learning function stop threshold, that is , calculate the failure probability and its coefficient of variation. When , output the result; otherwise, extract new samples and add them to the prediction sample pool until the stop condition is met.

[0076] The adaptive line sampling method samples according to the distribution of values, where satisfies the standard normal distribution. According to the intersection point , filter to obtain the samples falling into the failure domain, and use kernel density estimation to calculate the joint probability density and , then the reliability sensitivity can be calculated.

[0077] Therefore, the reliability sensitivity analysis of the lattice structure in this embodiment can be realized through the process shown in Figure 2 :

[0078] Implement the content of step 101 in SOLIDWORKS software. The improvement of the additive manufacturing lattice structure refers to determining the configuration of the additive manufacturing lattice structure in step 101, adding a geometric body with a thickness of 0.05 mm to the loading surface and the constraint surface, and defining the size parameters of the additive manufacturing lattice structure using the equation function; implement the content of step 102 in COMSOL software to parameterize the additive manufacturing lattice structure in COMSOL, which can be reconstructed by changing the parameters, and output the operation steps as a command stream file that can be run by MATLAB; implement the content of step 103 and step 104 in MATLAB software, write a command stream program to programmatically assign values to the size parameters, write an image recognition and finite element analysis program to achieve parametric modeling and joint simulation of the additive manufacturing lattice structure; finally, use MATLAB software to write a program for the adaptive line sampling algorithm, construct the failure mode of the lattice structure, propose an adaptive line sampling method to solve the reliability sensitivity, obtain an approximate limit state function using the Gaussian process model, and calculate the analysis result of the lattice structure through the global sensitivity index.

[0079] In this embodiment, by combining three software, SOLIDWORKS, COMSOL, and MATLAB, the command flow file of COMSOL is recompiled to reconstruct the model in SOLIDWORKS, reducing the operation difficulty and duration. An image recognition technology is proposed, and MATLAB finite element analysis and image recognition programs are written to achieve parametric modeling and simulation of multi-scale lattice structures, providing strong support for the reliability analysis of additively manufactured lattice structures and improving the actual efficiency. At the same time, an adaptive line sampling method is proposed, which can obtain extremely accurate calculation results at a very small computational cost, greatly reducing the computational cost of traditional reliability analysis. Combining the adaptive surrogate model with the line sampling method realizes global sensitivity analysis in high-dimensional problems, improves the computational efficiency, and provides strong technical support for the reliability analysis of additively manufactured lattice structures. In addition, this method can also provide reference for the modeling and reliability sensitivity analysis of other structures.

[0080] A specific embodiment is provided below. Taking the classic L-shaped additively manufactured lattice structure as an example, a combined simulation of parametric modeling of the lattice structure is carried out. In this embodiment, the lattice material is selected as 316L, the top left end of the additively manufactured lattice structure is constrained, and a vertically downward load is applied at the rightmost position.

[0081] The L-shaped additively manufactured lattice structure is selected. The circumscribed cube of this lattice structure is 16.67 mm, the connecting rod diameter is 5 mm, and the overall lattice size is 6 * 6 * 2 units, as Figure 3 shown. The top left end of the additively manufactured lattice structure is constrained, and a vertically downward load is applied at the rightmost position. The lattice material is selected as 316L steel, and the material density is 7.8 g / m 2 , and the limit state function of the lattice structure is defined as , where, is the maximum stress, is the ultimate stress of the material.

[0082] The specific parameter variables are shown in Table 1:

[0083] Table 1

[0084]

[0085] Continue to refer to Figure 3 , Figure 3 (a), the target object is an additively manufactured lattice structure with an overall lattice size of 6 * 6 * 2 units, a connecting rod diameter of 5 mm, a circumscribed cube of 16.67 mm for this unit cell, and a load is applied at the end point. Figure 3 (b), the target object is the geometric modeling diagram of the improved lattice structure, that is, geometries with a thickness of 0.05 mm are added to the loading surface and the constraint surface.

[0086] In this embodiment, the SOLIDWORKS software is used to improve and geometrically model the additive manufacturing lattice structure. By using the equation function, dimensional variables such as the rod diameter and rod length of the additive manufacturing lattice structure are defined to achieve dimensional parameterization. The geometric model of the additive manufacturing lattice structure is imported into the COMSOL software, and the dimensional variables are imported using the combined module COMSOL Multiphysics to achieve parameterization of the additive manufacturing lattice structure within COMSOL. By changing the parameter values in the global definition parameter module, the real-time change of the SOLIDWORKS model can be achieved. In the global definition module of COMSOL, the dimensional variables of the lattice structure are changed, and a command stream program is output. The command stream program is recompiled to reassign the dimensional variables with loop commands to achieve the parametric modeling of the multi-scale lattice structure. A MATLAB image recognition program is written to achieve the identification and specification of the numbers of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure. A finite element analysis program is written to achieve the finite element analysis and simulation of the multi-scale additive manufacturing lattice structure in the MATLAB software, and the stress results and stress nephograms are output to achieve the combined simulation of the parametric modeling of the additive manufacturing lattice structure. An adaptive line sampling method is proposed to solve the reliability sensitivity, and an approximate limit state function is obtained using the Gaussian process model. The analysis results of the lattice structure are calculated through the global sensitivity index.

[0087] See Figure 4 , which is a parametric modeling diagram of the lattice structure unit cell. In this embodiment, through the combination of SOLIDWORKS, COMSOL, and MATLAB, and by recompiling the COMSOL command stream file and writing the MATLAB program, the parametric modeling and simulation of the multi-scale lattice structure are achieved. Figure 4 Specifically, it is a unit cell modeling diagram of the multi-scale lattice structure. Figure 4 The radius of the unit cell of the lattice structure in (a) is 1.6 mm. Figure 4 The radius of the unit cell of the lattice structure in (b) is 0.6 mm.

[0088] See Figure 5 , which is a diagram of the numbers of the lattice structure unit cell and an identification diagram of the numbers of the loading surfaces of the overall lattice structure. In this embodiment, a MATLAB image recognition program is written to achieve the identification and specification of the numbers of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure. Figure 5 In (a), it is a diagram of the numbers of the unit cell structure. Figure 5 In (b), it is an identification diagram of the numbers of the loading surfaces of the overall lattice structure.

[0089] In this embodiment, the finite element analysis of the additive manufacturing lattice structure is carried out by using MATLAB software. The tetrahedral elements are used to perform the finite element mesh division of the structure, and the stress distribution nephogram is drawn.

[0090] After building the parametric modeling platform of the lattice structure, the reliability sensitivity analysis of the lattice structure is carried out. The existing improved first-order second-moment method is used to solve the design point. The adaptive line sampling method is compared with the importance sampling method to solve the reliability and global sensitivity. The results are shown in Table 2, where refers to the number of calls of the limit state function.

[0091] Table 2

[0092]

[0093] The number of calls of the limit state function by the importance sampling method is 1000 times, and the number of calls of the limit state function by the adaptive line sampling method is 97 times, and it meets the accuracy requirements. The calculation results are stable, and the sensitivity ranking is consistent. This shows that the algorithm has wide applicability and greatly reduces the calculation time. In addition, the adaptive line sampling algorithm is independently repeated for ten times to ensure the robustness and convergence of the algorithm. The values in parentheses in the table represent the standard deviation of the results. It can be seen that the present invention can programmatically realize the geometric modeling and finite element analysis of the additive manufacturing lattice structure, reduce the calculation cost, and ensure the accuracy of the simulation results, proving the effectiveness and efficiency of the method of the present invention.

[0094] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as they include the same logical relationship, they are all within the protection scope of the present invention; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but not changing the core design of its algorithm and process are all within the protection scope of the invention.

[0095] Another embodiment of the present invention relates to a multi-scale lattice structure parametric modeling device. The implementation details of the multi-scale lattice structure parametric modeling device in this embodiment are specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing the solution. The multi-scale lattice structure parametric modeling device in this embodiment includes:

[0096] A first model generation module, configured to model the multi-scale lattice structure by using SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure;

[0097] The second model generation module is used to import the first geometric model into the COMSOL software, and adjust the dimension variables of the first geometric model through the COMSOL software to generate a second geometric model of a multi-scale lattice structure; wherein, the second geometric model is in the.stl format, and the.stl format second geometric model is generated by adopting the command flow program for outputting the first geometric model by the COMSOL software and re-writing the command flow program.

[0098] The model recognition module is used to import the second geometric model into the MATLAB software, and identify the constraint surface and the loading surface of the second geometric model through the MATLAB software.

[0099] The model analysis module is used to perform finite element analysis on the second geometric model according to the constraint surface and the loading surface through the MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

[0100] In one example, the parametric modeling device for the multi-scale lattice structure of the present invention includes:

[0101] The parametric modeling module: Improve and geometrically model the additive manufacturing lattice structure by using the SOLIDWORKS software, and realize dimension parameterization; Import the geometric model of the additive manufacturing lattice structure into the COMSOL software, and use the combined module COMSOL Multiphysics to import dimension variables to realize the parameterization of the additive manufacturing lattice structure within COMSOL; In the global definition module of COMSOL, change the dimension variables of the lattice structure, output the command flow program, re-write the command flow program, and re-assign the dimension variables with a loop command to realize the parametric modeling of the multi-scale lattice structure.

[0102] The parametric co-simulation module: Write a MATLAB image recognition program to realize the identification and designation of the numbers of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure, and write a finite element analysis program to realize the finite element analysis of the parameterization of the multi-scale lattice structure.

[0103] The reliability sensitivity analysis module: Propose an adaptive line sampling method to solve the reliability sensitivity, obtain an approximate limit state function by using a Gaussian process model, and calculate the analysis results of the lattice structure through the global sensitivity index.

[0104] It is easy to find that this embodiment is a device embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment. The relevant technical details and technical effects mentioned in the above embodiments are still valid in this embodiment. To avoid repetition, they are not elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied in the above embodiments.

[0105] It is worth mentioning that all the modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, units that are not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0106] Another embodiment of the present invention relates to a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the multi-scale lattice structure parametric modeling method in the above embodiments.

[0107] Among them, the memory and the processor are connected by a bus. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be an element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted on the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0108] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory can be used to store the data used by the processor when executing operations.

[0109] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiment is implemented.

[0110] That is, those skilled in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. This program is stored in a storage medium and includes several instructions to enable a device (such as a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0111] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention. In actual applications, various changes can be made to them in form and details without departing from the spirit and scope of the present invention.

Claims

1. A multi-scale lattice structure parameter modeling method, characterized in that: The method comprises: Modeling the multi-scale lattice structure using SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; Importing the first geometric model into COMSOL software, and adjusting the first size variable of the first geometric model to the second size variable using the COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein the second geometric model is in .stl format, and the second geometric model in .stl format is generated by the COMSOL software according to the steps of adjusting the first size variable, and the command flow program is rewritten and generated according to the second size variable; Importing the second geometric model into MATLAB software, and identifying the constraint surface and the loading surface of the second geometric model through the MATLAB software; Finite element analysis of the second geometric model is performed using MATLAB software based on the constraint surface and the loading surface to obtain the stress distribution of the multi-scale lattice structure; The identifying of the constraint surface and the loading surface of the second geometric model by using MATLAB software includes: Acquire a plurality of sample geometric models having a multi-scale lattice structure with numbered constraint surfaces and loading surfaces, and acquire an image of the constraint surface and loading surface of each sample geometric model; wherein each image contains the number of the corresponding constraint surface or loading surface; An image recognition model is trained using images of the constraint surfaces and loading surfaces of several sample geometric models, and the images of the constraint surfaces and loading surfaces of the second geometric model are input into the image recognition model to obtain the numbers of the constraint surfaces and loading surfaces of the second geometric model so as to identify the constraint surfaces and loading surfaces of the second geometric model.

2. The multi-scale lattice structure parameter modeling method according to claim 1, characterized in that: The multi-scale lattice structure is modeled using SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure, including: According to the geometric configuration of the multi-scale lattice structure, SOLIDWORKS software is used to perform modeling. During the modeling process, the equation function is used within the SOLIDWORKS software to define the first size variable of the multi-scale lattice structure to generate a first geometric model.

3. The multi-scale lattice structure parameter modeling method according to claim 2, characterized in that: The method of importing the first geometric model into COMSOL software and adjusting the first size variable of the first geometric model to a second size variable by the COMSOL software to generate a second geometric model of the multi-scale lattice structure includes: Using COMSOL Multiphysics, a joint module of SOLIDWORKS software and COMSOL software, the first geometric model is imported into COMSOL software; Import the first dimension variable of the defined multi-scale lattice structure into the global parameter definition module of COMSOL software, and generate the steps of setting parameters in the global parameter definition module into a command stream file; The command flow program is rewritten to adjust the first size variable of the first geometric model to the second size variable to generate a second geometric model of the multi-scale lattice structure.

4. The multi-scale lattice structure parameter modeling method according to claim 1, characterized in that: After obtaining the stress distribution of the multi-scale lattice structure, the method further includes: According to the stress distribution, the limit state function of the multi-scale lattice structure is constructed; wherein the limit state function is used to describe whether the multi-scale lattice structure is in a failure state; The Gaussian process model is used as a proxy model for the limit state function. The parameter variables that affect the limit state function value of the multi-scale lattice structure are used as sampling points. The adaptive line sampling method is used to sample along important directions, and the Gaussian process model is used to predict the limit state function value at the sampling points. According to the limit state function value, sampling points that make the multi-scale lattice structure in a failure state are determined as failure samples, and according to the number of failure samples, the failure probability of the multi-scale lattice structure is determined.

5. A multi-scale lattice structure parameter modeling device, characterized in that: The device comprises: A first model generation module is used to model the multi-scale lattice structure using SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; a second model generation module, configured to import the first geometric model into COMSOL software, and adjust the first size variable of the first geometric model to a second size variable using the COMSOL software to generate a second geometric model of a multi-scale lattice structure; wherein the second geometric model is in .stl format, and the second geometric model in .stl format is generated by the COMSOL software according to the steps of adjusting the first size variable, and the command flow program is rewritten and generated according to the second size variable; A model identification module is used to import the second geometric model into MATLAB software and identify the constraint surface and the loading surface of the second geometric model through the MATLAB software; A model analysis module is used to perform finite element analysis on the second geometric model based on the constraint surface and the loading surface using MATLAB software to obtain the stress distribution of the multi-scale lattice structure; Among them, the model recognition module is also used to obtain several sample geometric models with multi-scale lattice structures having numbered constraint surfaces and loading surfaces, and obtain images of the constraint surfaces and loading surfaces of each sample geometric model; use the images of the constraint surfaces and loading surfaces of several sample geometric models to train an image recognition model, and input the images of the constraint surfaces and loading surfaces of the second geometric model into the image recognition model to obtain the numbers of the constraint surfaces and loading surfaces of the second geometric model to identify the constraint surfaces and loading surfaces of the second geometric model; wherein each image contains the number of the corresponding constraint surface or loading surface.

6. A computer device, characterized in that: include: at least one processor; And, a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the multi-scale lattice structure parametric modeling method as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the multi-scale lattice structure parameterized modeling method according to any one of claims 1 to 4 is implemented.

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