Structural topology optimization method and device based on progressive nonlinear correction

Abstract

The present invention relates to the technical field of computational mechanics and structural optimization design, and provides a method and device for structural topology optimization based on progressive nonlinear correction. The method divides the optimization process of structural topology into the initial optimization stage, the middle optimization stage and the late optimization stage, realizes the segmented processing of the nonlinear problem of the structure, and dynamically introduces nonlinear factors in the middle optimization stage and the late optimization stage, so as to balance the computational efficiency and accuracy, realize the efficient solution of complex nonlinear problems, significantly reduce the computational cost, and ensure the accuracy of the results. The method can be widely applied to the design requirements of complex structures such as large deformation, nonlinear materials, and contact problems.

Description

Technical Field

[0001] The present invention relates to the technical field of computational mechanics and structural optimization design, and particularly relates to a structural topology optimization method and device based on progressive non-linear correction. Background Art

[0002] As an advanced structural design method, topology optimization is widely used in fields such as aerospace and automotive manufacturing.

[0003] Generally, the non-linear sources in a structural model include materials, structures, and boundary conditions. Existing topology optimization methods mainly assume that materials and structures are both linear, and then calculate linear problems. However, this can only consider small deformation problems on the premise that the non-linearity of materials and boundary conditions does not exist, and cannot effectively handle complex working conditions such as large deformations and material non-linearity, which limits its applicability in actual engineering.

[0004] Existing solutions often rely on high-cost non-linear iterative calculations, with low computational efficiency and results easily affected by initial conditions. Based on this, there is an urgent need to provide a new structural topology optimization method. Summary of the Invention

[0005] The present invention provides a structural topology optimization method and device based on progressive non-linear correction to solve the defects existing in the prior art.

[0006] The present invention provides a structural topology optimization method based on progressive non-linear correction, including:

[0007] In the initial stage of optimization, simplify the structural response into a linear problem, and based on the displacement vector and external load vector of the structure, determine the first objective function, and iteratively solve for the first material distribution density of the structure when minimizing the first objective function;

[0008] In the middle stage of optimization, based on a progressive loading strategy, introduce non-linear effects, determine the displacement increment and load increment for each iteration round of loading, and based on the displacement increment and the load increment, correct the first objective function to obtain a second objective function, and based on the first material distribution density, iteratively solve for the second material distribution density of the structure when minimizing the second objective function;

[0009] In the later stage of optimization, determine the additional stiffness matrix caused by the material non-linearity of the structure, and based on the additional stiffness matrix, correct the second objective function to obtain a third objective function, and based on the second material distribution density, iteratively solve for the third material distribution density of the structure when minimizing the third objective function.

[0010] A structural topology optimization method based on progressive non - linear correction provided by the present invention, the loads applied in each iteration round are determined based on the following steps:

[0011] Determine the step - size factor of the current iteration round;

[0012] Based on the step - size factor of the current iteration round and the target load, determine the load applied in the current iteration round;

[0013] Wherein, the step - size factors of two adjacent iteration rounds differ by a fixed step - size interval.

[0014] A structural topology optimization method based on progressive non - linear correction provided by the present invention further includes:

[0015] In the middle and late stages of the optimization, based on the convergence of the optimization iteration, apply a penalty parameter to dynamically adjust the non - linear correction intensity.

[0016] A structural topology optimization method based on progressive non - linear correction provided by the present invention further includes:

[0017] Construct a multi - objective optimization function, the optimization objectives of the multi - objective optimization function include maximizing the stiffness - energy absorption ratio of the structure and the maximum allowable strain of the structure being less than or equal to the strain threshold;

[0018] Solve the multi - objective optimization function to perform topology optimization on the structure.

[0019] For a structural topology optimization method based on progressive non - linear correction provided by the present invention, the mesh element size of the mesh model of the structure decreases successively in the initial, middle, and late stages of the optimization.

[0020] For a structural topology optimization method based on progressive non - linear correction provided by the present invention, the first material distribution density of the structure when iteratively solving to minimize the first objective function includes:

[0021] Based on the convergence speed of the first objective function, determine the first material distribution density.

[0022] For a structural topology optimization method based on progressive non - linear correction provided by the present invention, the third material distribution density of the structure when iteratively solving to minimize the third objective function based on the second material distribution density includes:

[0023] Based on the second material distribution density, use the Newton - Raphson iteration method to iteratively solve the third material distribution density of the structure when minimizing the third objective function.

[0024] The present invention also provides a structural topology optimization device based on progressive non-linear correction, comprising:

[0025] A first optimization stage module, configured to simplify the structural response into a linear problem at the initial stage of optimization, determine a first objective function based on the displacement vector and the external load vector of the structure, and iteratively solve for the first material distribution density of the structure when minimizing the first objective function;

[0026] A second optimization stage module, configured to introduce non-linear effects based on a progressive loading strategy at the middle stage of optimization, determine the displacement increment and the load increment for each iteration round of loading, and correct the first objective function based on the displacement increment and the load increment to obtain a second objective function, and iteratively solve for the second material distribution density of the structure when minimizing the second objective function based on the first material distribution density;

[0027] A third optimization stage module, configured to determine an additional stiffness matrix caused by the material non-linearity of the structure at the later stage of optimization, and correct the second objective function based on the additional stiffness matrix to obtain a third objective function, and iteratively solve for the third material distribution density of the structure when minimizing the third objective function based on the second material distribution density.

[0028] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, it implements the structural topology optimization method based on progressive non-linear correction as described in any one of the above.

[0029] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the structural topology optimization method based on progressive non-linear correction as described in any one of the above.

[0030] The present invention also provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, it implements the structural topology optimization method based on progressive non-linear correction as described in any one of the above.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The structural topology optimization method and device based on progressive non-linear correction provided by the present invention divide the optimization process of the structural topology into the initial stage, the middle stage and the later stage of optimization, realizing the segmented processing of the non-linear problems of the structure, and dynamically introducing non-linear factors in the middle stage and the later stage of optimization, so as to balance the calculation efficiency and accuracy, realize the efficient solution of complex non-linear problems, significantly reduce the calculation cost, and ensure the accuracy of the results at the same time. This method can be widely applied to the design requirements of complex structures such as large deformation, non-linear materials, and contact problems. Brief Description of the Drawings

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below can also be obtained by those of ordinary skill in the art from these drawings without creative efforts.

[0034] Figure 1 is a schematic flow chart of the structural topology optimization method based on progressive non-linear correction provided by the present invention;

[0035] Figure 2 is a schematic structural diagram of the structural topology optimization device based on progressive non-linear correction provided by the present invention;

[0036] Figure 3 is a schematic structural diagram of the electronic device provided by the present invention. Detailed Embodiments

[0037] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] Since the existing topology optimization methods often rely on high-cost non-linear iterative calculations, the calculation efficiency is low and the results are easily affected by the initial conditions. Based on this, an embodiment of the present invention provides a structural topology optimization method based on progressive non-linear correction.

[0039] Figure 1 is a schematic flow chart of a structural topology optimization method based on progressive non-linear correction provided in an embodiment of the present invention, as Figure 1 shown, the method includes:

[0040] S1. In the initial stage of optimization, simplify the structural response into a linear problem. Based on the displacement vector of the structure and the external load vector, determine the first objective function, and iteratively solve for the first material distribution density of the structure when minimizing the first objective function.

[0041] S2. In the middle stage of optimization, based on the progressive loading strategy, introduce the nonlinear effect, determine the displacement increment and load increment for each iteration round of loading, and based on the displacement increment and the load increment, correct the first objective function to obtain the second objective function. Based on the first material distribution density, iteratively solve for the second material distribution density of the structure when minimizing the second objective function.

[0042] S3. In the later stage of optimization, determine the additional stiffness matrix caused by the material nonlinearity of the structure, and based on the additional stiffness matrix, correct the second objective function to obtain the third objective function. Based on the second material distribution density, iteratively solve for the third material distribution density of the structure when minimizing the third objective function.

[0043] Specifically, in the embodiment of the present invention, the structural topology optimization method based on progressive nonlinear correction has an execution entity which is a structural topology optimization device based on progressive nonlinear correction. This device can be configured in a computer, and the computer can be a local computer or a cloud computer. The local computer can be a computer, a tablet, etc., and no specific limitation is made here.

[0044] The structural topology optimization method based on progressive nonlinear correction provided in the embodiment of the present invention is divided into three stages, namely the initial stage of optimization, the middle stage of optimization, and the later stage of optimization. After the initial stage of optimization ends, it enters the middle stage of optimization, and after the middle stage of optimization ends, it enters the later stage of optimization.

[0045] First, execute step S1. In the initial stage of optimization, simplify the structural response into a linear problem, take the material distribution density as the design variable, and obtain the optimized first material distribution density through rapid iterative convergence. It can be understood that the structure can be a mechanical structure, such as an explosion-proof stiffening structure, a high-speed light-load mechanism, a hinge-free compliant mechanism, etc., which need to perform topology optimization, and no specific limitation is made here.

[0046] The finite element equation in the initial stage of optimization can be expressed as:

[0047] ;

[0048] where, K 0 is the linearized initial stiffness matrix, u 0 is the displacement vector of the structure, f 0 is the external load vector, which is the load of the structure, that is, the external force it receives.

[0049] The first objective function can be expressed as:

[0050] ;

[0051] Minimizing the first objective function can be expressed as:

[0052] ;

[0053] The constraint conditions are:

[0054] ;

[0055] Where, is the dependent variable of the first objective function, ρ represents the material distribution density, which is the independent variable of the first objective function, can be constraint conditions such as displacement, stress, volume, modal frequency, etc., is the material distribution density obtained in the i-th iteration round at the initial stage of optimization.

[0056] Then step S2 is executed. In the middle stage of optimization, based on the progressive loading strategy, nonlinear effects are introduced, such as geometric nonlinearity or material nonlinearity, that is, the nonlinear problem is decomposed into multiple linear problems with small-amplitude loading, and the first material distribution density is iteratively corrected.

[0057] At this time, the displacement increment and load increment for each iteration round of loading can be determined, and then the finite element equation in the middle stage of optimization, that is, the incremental finite element equation, can be determined.

[0058] The incremental finite element equation can be expressed as:

[0059] ;

[0060] Where, is the stiffness matrix considering geometric nonlinearity correction in the n-th iteration round in the middle stage of optimization, is the displacement increment for loading in the n-th iteration round in the middle stage of optimization, is the load increment for loading in the n-th iteration round in the middle stage of optimization.

[0061] And there is: ; N is the total number of iteration rounds in the middle stage of optimization.

[0062] After that, using the displacement increment and load increment for each iteration round of loading, the first objective function can be corrected to obtain the second objective function.

[0063] The second objective function can be expressed as:

[0064] .

[0065] Where, is the dependent variable of the second objective function.

[0066] Thereafter, using the first material distribution density as the initial value of the material distribution density in the middle stage of optimization, iteratively solve for the second material distribution density of the structure when minimizing the second objective function.

[0067] Finally, execute step S3. In the late stage of optimization, comprehensively introduce material nonlinearity and complex boundary conditions to determine the additional stiffness matrix caused by the material nonlinearity of the structure . The finite element equation in the late stage of optimization can be expressed as:

[0068] .

[0069] Where is the stiffness matrix corresponding to the displacement vector u in the late stage of optimization, is the displacement increment in the late stage of optimization, is the load increment in the late stage of optimization.

[0070] Using the additional stiffness matrix, correct the second objective function to obtain the third objective function. The third objective function can be expressed as:

[0071] ;

[0072] Where is the third objective function, V is the volume of the structure, is the strain and the energy density corresponding to the material distribution density , and this energy density includes non - linear strain energy.

[0073] The final form of the optimization problem of minimizing the third objective function can be:

[0074] .

[0075] Thereafter, using the second material distribution density as the initial value of the material distribution density in the late stage of optimization, iteratively solve for the third material distribution density of the structure when minimizing the third objective function.

[0076] In the structural topology optimization method based on progressive non - linear correction provided in the embodiments of the present invention, the optimization process of the structural topology is divided into the initial stage, the middle stage, and the late stage of optimization, realizing segmented processing of the non - linear problems of the structure. And in the middle and late stages of optimization, non - linear factors are dynamically introduced, so as to balance the calculation efficiency and accuracy, achieve efficient solution of complex non - linear problems, significantly reduce the calculation cost, and ensure the accuracy of the results at the same time. This method can be widely applied to the design requirements of complex structures such as large deformation, non - linear materials, and contact problems.

[0077] Based on the above embodiments, the load applied in each iteration round is determined according to the following steps:

[0078] Determine the step factor of the current iteration round;

[0079] Based on the step factor of the current iteration round and the target load, determine the load applied in the current iteration round;

[0080] Wherein, there is a fixed step interval difference between the step factors of two adjacent iteration rounds.

[0081] Specifically, when the current iteration round is set as n, the load applied in the current iteration round n can be expressed as , when determining , first determine the step factor of the current iteration round n, and the initial step factor can be set as needed.

[0082] Thereafter, use the step factor of the current iteration round n and the target load to determine the load applied in the current iteration round n. The target load can be the maximum load , then can be expressed as: .

[0083] It can be understood that there is a fixed step interval difference between the step factors of two adjacent iteration rounds. The product of this fixed step interval and the target load is the load increment applied in the current iteration round n, that is, there is .

[0084] The relationship between the step factors of two adjacent iteration rounds can be expressed as:

[0085] .

[0086] In the embodiments of the present invention, the determination of the applied load is achieved through the relationship between the step factors of each iteration round, which can gradually increase the loading amplitude and ensure the stability of the optimization process.

[0087] Based on the above embodiments, it further includes:

[0088] In the middle and late stages of the optimization, based on the convergence situation of the optimization iteration, apply a penalty parameter to dynamically adjust the non-linear correction intensity.

[0089] Specifically, in the embodiments of the present invention, a penalty parameter β, i.e., a non-linear correction parameter, can be introduced to gradually adjust and optimize the sensitivity analysis formula to achieve dynamic adjustment of the non-linear correction intensity. The penalty parameter β can be equivalent to 0 in the initial stage of optimization and gradually increase in the middle and late stages of optimization to comprehensively consider the non-linear effect.

[0090] Among them, the sensitivity analysis formula can be expressed as:

[0091] ;

[0092] Among them, is the composite numerical gradient of the i-th iteration round in the middle or late stage of optimization, which can represent the convergence of the optimization iteration in the middle or late stage of optimization. is the linear numerical gradient of the i-th iteration round in the middle or late stage of optimization, which can represent the linear convergence in the middle or late stage of optimization. is the non-linear numerical gradient of the i-th iteration round in the middle or late stage of optimization, which can represent the non-linear convergence in the middle or late stage of optimization.

[0093] By calculating high-precision gradient information through the composite numerical gradient and finite difference technology, the dynamic adjustment of the non-linear correction intensity is realized, the stability and convergence speed of the optimization process are improved, and the divergence problem caused by overcorrection is avoided.

[0094] Based on the above embodiments, it further includes:

[0095] Construct a multi-objective optimization function, and the optimization objectives of the multi-objective optimization function include maximizing the stiffness-energy absorption ratio of the structure and the maximum allowable strain of the structure being less than or equal to the strain threshold;

[0096] Solve the multi-objective optimization function to perform topology optimization on the structure.

[0097] Specifically, in the embodiments of the present invention, a multi-objective optimization function can be constructed for non-linear problems, and its optimization objectives can include maximizing the stiffness-energy absorption ratio of the structure and the maximum allowable strain of the structure being less than or equal to the strain threshold. By comprehensively considering various performance indicators such as structural stiffness, energy absorption, and material non-linearity, the effective optimization of non-linear effects is realized.

[0098] Based on the above embodiments, the mesh element size of the mesh model of the structure decreases successively in the initial stage, the middle stage, and the late stage of the optimization.

[0099] Specifically, in the embodiments of the present invention, a multi-resolution model can be designed to quickly converge using a mesh model with a coarse mesh in the initial stage of optimization and gradually refine the mesh in the middle and late stages of optimization to improve the accuracy.

[0100] Based on the above embodiments, when iteratively solving to minimize the first objective function for the first material distribution density of the structure, it includes:

[0101] Determining the first material distribution density based on the convergence rate of the first objective function.

[0102] Specifically, in the embodiments of the present invention, when iteratively solving to minimize the first objective function for the first material distribution density of the structure, the convergence rate of the first objective function can be utilized to determine the first material distribution density. That is, the convergence rate of the first objective function is used to judge the end condition in the initial stage of optimization. Since the main objective in the initial stage of optimization is to quickly converge to obtain the first material distribution density, when the convergence rate of the first objective function reaches a certain degree, such as continuous iterations for several times (for example, 3 - 5 times), and the change amount of the first objective function is less than a set threshold (such as 1% - 5% of the initial value of the first objective function), it is considered that the linear stage in the initial stage of optimization ends and enters the non - linear stage in the middle stage of optimization.

[0103] Based on the above embodiments, when iteratively solving to minimize the third objective function for the third material distribution density of the structure based on the second material distribution density, it includes:

[0104] Based on the second material distribution density, using the Newton - Raphson iteration method to iteratively solve for the third material distribution density of the structure when minimizing the third objective function.

[0105] Specifically, in the later stage of optimization, comprehensively introducing material and geometric non - linear factors, using the Newton - Raphson iteration method, with the second material distribution density as the initial value of the material distribution density, to solve for minimizing the third objective function, can quickly and accurately determine the third material distribution density and achieve the optimization of the structure topology.

[0106] Based on the above embodiments, in the embodiments of the present invention, parallel computing technology can be combined to distribute the non - linear solution to multiple computing nodes to improve the solution efficiency of large - scale problems.

[0107] As Figure 2 shown, based on the above embodiments, in the embodiments of the present invention, a structure topology optimization device based on progressive non - linear correction is provided, including:

[0108] A first optimization stage module 21, configured to simplify the structural response into a linear problem in the initial stage of optimization, determine the first objective function based on the displacement vector of the structure and the external load vector, and iteratively solve for the first material distribution density of the structure when minimizing the first objective function;

[0109] The second optimization stage module 22 is used in the middle stage of optimization. Based on the progressive loading strategy, it introduces the nonlinear effect, determines the displacement increment and load increment loaded in each iteration round, and corrects the first objective function based on the displacement increment and the load increment to obtain a second objective function. Based on the first material distribution density, it iteratively solves for the second material distribution density of the structure when minimizing the second objective function;

[0110] The third optimization stage module 23 is used in the later stage of optimization. It determines the additional stiffness matrix caused by the material nonlinearity of the structure, and corrects the second objective function based on the additional stiffness matrix to obtain a third objective function. Based on the second material distribution density, it iteratively solves for the third material distribution density of the structure when minimizing the third objective function.

[0111] Based on the above embodiments, in the structure topology optimization device provided in the embodiments of the present invention based on progressive nonlinear correction, the load loaded in each iteration round is determined according to the following steps:

[0112] Determine the step factor of the current iteration round;

[0113] Based on the step factor of the current iteration round and the target load, determine the load loaded in the current iteration round;

[0114] Wherein, the step factors of two adjacent iteration rounds differ by a fixed step interval.

[0115] Based on the above embodiments, the structure topology optimization device provided in the embodiments of the present invention based on progressive nonlinear correction further includes a dynamic adjustment module for:

[0116] In the middle stage and the later stage of the optimization, based on the convergence of the optimization iteration, apply a penalty parameter to dynamically adjust the intensity of the nonlinear correction.

[0117] Based on the above embodiments, the structure topology optimization device provided in the embodiments of the present invention based on progressive nonlinear correction further includes a multi-objective optimization module for:

[0118] Construct a multi-objective optimization function, and the optimization objectives of the multi-objective optimization function include maximizing the stiffness-energy absorption ratio of the structure and the maximum allowable strain of the structure being less than or equal to the strain threshold;

[0119] Solve the multi-objective optimization function to perform topology optimization on the structure.

[0120] Based on the above embodiments, in the structural topology optimization device provided in the embodiments of the present invention based on progressive non-linear correction, the mesh element size of the mesh model of the structure decreases successively in the initial stage, the middle stage, and the later stage of the optimization.

[0121] Based on the above embodiments, in the structural topology optimization device provided in the embodiments of the present invention based on progressive non-linear correction, the first optimization stage module is specifically configured to:

[0122] Determine the first material distribution density based on the convergence rate of the first objective function.

[0123] Based on the above embodiments, in the structural topology optimization device provided in the embodiments of the present invention based on progressive non-linear correction, the third optimization stage module is specifically configured to:

[0124] Based on the second material distribution density, use the Newton-Raphson iteration method to iteratively solve the third material distribution density of the structure when minimizing the third objective function.

[0125] Specifically, the functions of the modules in the structural topology optimization device provided in the embodiments of the present invention based on progressive non-linear correction correspond one-to-one to the operation processes of the steps in the above method embodiments, and the achieved effects are also the same. For details, please refer to the above embodiments, and the embodiments of the present invention will not be elaborated herein.

[0126] Figure 3 Illustrates a schematic diagram of the physical structure of an electronic device, as Figure 3 shown. The electronic device may include: a processor (Processor) 310, a communication interface (Communications Interface) 320, a memory (Memory) 330, and a communication bus 340. Among them, the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logical instructions in the memory 330 to execute the structural topology optimization method based on progressive non-linear correction provided in the above embodiments.

[0127] In addition, when the logical instructions in the above-mentioned memory 330 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0128] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the structure topology optimization method based on progressive non-linear correction provided in the above-mentioned various embodiments.

[0129] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the structure topology optimization method based on progressive non-linear correction provided in the above-mentioned various embodiments.

[0130] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0131] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A structural topology optimization method based on progressive nonlinear correction, characterized in that: include: In the initial stage of optimization, the structural response is simplified into a linear problem, a first objective function is determined based on the displacement vector of the structure and the external load vector, and a first material distribution density of the structure is iteratively solved when minimizing the first objective function; In the middle of the optimization, based on the progressive loading strategy, nonlinear effects are introduced to determine the displacement increment and load increment of each iterative round of loading, and based on the displacement increment and the load increment, the first objective function is corrected to obtain the second objective function, and based on the first material distribution density, the second material distribution density of the structure is iteratively solved to minimize the second objective function; In the later stage of optimization, an additional stiffness matrix caused by material nonlinearity of the structure is determined, and based on the additional stiffness matrix, the second objective function is modified to obtain a third objective function, and based on the second material distribution density, the third material distribution density of the structure is iteratively solved when minimizing the third objective function; The load applied in each iteration is determined based on the following steps: Determine the step size factor for the current iteration round; Determining the load loaded in the current iteration round based on the step size factor and the target load of the current iteration round; Among them, the step factors of two adjacent iteration rounds differ by a fixed step interval.

2. The structural topology optimization method based on progressive nonlinear correction according to claim 1, characterized in that: Also includes: In the middle and late stages of the optimization, based on the convergence of the optimization iterations, penalty parameters are applied to dynamically adjust the nonlinear correction strength.

3. The structural topology optimization method based on progressive nonlinear correction according to claim 1, characterized in that: Also includes: Constructing a multi-objective optimization function, wherein the optimization objectives of the multi-objective optimization function include maximizing the stiffness-energy absorption ratio of the structure and the maximum allowable strain of the structure being less than or equal to a strain threshold; Solve the multi-objective optimization function and perform topology optimization on the structure.

4. The structural topology optimization method based on progressive nonlinear correction according to any one of claims 1 to 3, characterized in that: The mesh unit size of the mesh model of the structure decreases in sequence in the initial stage of the optimization, the middle stage of the optimization and the late stage of the optimization.

5. The structural topology optimization method based on progressive nonlinear correction according to any one of claims 1 to 3, characterized in that: The iterative solution for minimizing the first material distribution density of the structure when the first objective function is minimized includes: The first material distribution density is determined based on a convergence rate of the first objective function.

6. The structural topology optimization method based on progressive nonlinear correction according to any one of claims 1 to 3, characterized in that: The iteratively solving the third material distribution density of the structure when minimizing the third objective function based on the second material distribution density includes: Based on the second material distribution density, a Newton-Raphson iterative method is used to iteratively solve the third material distribution density of the structure when minimizing the third objective function.

7. A structural topology optimization device based on progressive nonlinear correction, characterized in that: include: A first optimization stage module is used to simplify the structural response into a linear problem at the initial stage of optimization, determine a first objective function based on the displacement vector of the structure and the external load vector, and iteratively solve the first material distribution density of the structure when minimizing the first objective function; A second optimization phase module is used to introduce nonlinear effects in the middle of optimization based on a progressive loading strategy, determine the displacement increment and load increment of each iterative round of loading, and modify the first objective function based on the displacement increment and the load increment to obtain a second objective function, and iteratively solve the second material distribution density of the structure when minimizing the second objective function based on the first material distribution density; A third optimization stage module is used to determine, in the later stage of optimization, an additional stiffness matrix caused by material nonlinearity of the structure, and based on the additional stiffness matrix, correct the second objective function to obtain a third objective function, and iteratively solve the third material distribution density of the structure when minimizing the third objective function based on the second material distribution density; The load applied in each iteration is determined based on the following steps: Determine the step size factor for the current iteration round; Determining the load loaded in the current iteration round based on the step size factor and the target load of the current iteration round; Among them, the step factors of two adjacent iteration rounds differ by a fixed step interval.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the structural topology optimization method based on progressive nonlinear correction as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the structural topology optimization method based on progressive nonlinear correction as described in any one of claims 1 to 6 is implemented.

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