Multi-scale parallel optimization method for lightweight structure based on lattice discrete optimization

Abstract

The present application belongs to the technical field of additive manufacturing, and particularly relates to a lightweight structure multi-scale parallel optimization method based on lattice discrete optimization. The present application uses the geometric parameters of movable and deformable rods to describe macroscopic structures and microscopic lattice structures through multi-scale parallel optimization design, and uses an improved double-value coding parameterization method, referred to as BCP method, to solve the discrete optimization of the microscopic lattice structure and easily extract the geometric parameters of the optimization results.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of additive manufacturing, and particularly relates to a lightweight structure multi-scale parallel optimization method based on lattice discrete optimization. BACKGROUND

[0002] Additive manufacturing technology provides an innovative path for thin-walled products to break through traditional manufacturing constraints due to its precise manufacturing capability of micro-lattice structure, and is widely used in the fields of aerospace, automobiles, medical devices, etc. Micro-lattice structure exhibits excellent mechanical properties in high stiffness ratio, buckling resistance, energy absorption, heat dissipation, etc. through the distribution of materials at specific positions, thereby greatly determining the overall mechanical properties of the macro-structure. The current multi-scale structure topology optimization research is still insufficient in directly obtaining an optimized result with hollow features, and there are problems such as single micro-lattice form, local material discontinuity, and difficulty in extracting geometric parameters of multiple lattices after optimization.

[0003] In the current multi-scale parallel topology optimization research using micro-lattice structure, there are problems such as difficulty in processing and manufacturing due to single periodic distribution of micro-lattice structure and local material discontinuity of the lattice, or difficulty in capturing geometric shape parameters of multiple lattices obtained by optimization, which requires a large amount of time and resources for post-processing and detailed design of the optimized results. SUMMARY

[0004] Therefore, the present application aims to provide a lightweight structure multi-scale parallel optimization method based on lattice discrete optimization to solve the problem of difficulty in processing and manufacturing due to single periodic distribution of micro-lattice structure and local material discontinuity of the lattice in the prior art. The present application can not only ensure that the optimized result obtains the optimal discrete combination performance of multiple types of micro-lattice structure, but also avoid the problem of lattice discontinuity in the optimization process, and the structure after optimization can be directly described by geometric parameters, which is convenient for processing and manufacturing and improves the efficiency of lightweight structure design.

[0005] To achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0006] A lightweight structure multi-scale parallel optimization method based on lattice discrete optimization, specifically comprising the following steps:

[0007] S1: obtaining the initial layout of the macro-structure and performing grid processing on the macro-structure to obtain macro-units, each macro-unit corresponding to a micro-lattice structure;

[0008] S2: constructing a density function of macro-bar mapping to the macro-unit based on the geometric parameters of the macro-bar used by the macro-structure;

[0009] S3: The micro-lattice structure is constructed using solid rods. The micro-lattice structure is then meshed to obtain micro-units. Based on the geometric parameters of the solid rods, a density function is constructed that maps the solid rods to the micro-units to obtain the constitutive matrix of the micro-lattice structure.

[0010] S4: Based on the BCP method, and combined with the constitutive matrix of the micro-lattice structure, construct the discrete lattice optimization function of the macro-unit;

[0011] S5: Perform finite element analysis on the discrete lattice optimization function to obtain the nodal displacement vectors of the macroscopic elements;

[0012] S6: An optimization model is constructed based on the nodal displacement vector of macroscopic units, the density function of macroscopic bars mapped to macroscopic units, and the constitutive matrix of microscopic lattice structure. The sensitivity of the geometric parameters of macroscopic bars and the sensitivity of the discrete design variables of microscopic lattice structure are calculated based on the objective function.

[0013] S7: Input the calculation results and objective function of step S6 into the optimization algorithm. The optimization algorithm updates the discrete design variables of the macroscopic bar geometry parameters and the microscopic lattice structure. If the number of updates is less than the preset number of iterations or the updated macroscopic bar geometry parameters and the discrete design variables of the microscopic lattice are both less than their respective preset values, then step S2 is executed again. Otherwise, the lattice discrete optimization is completed.

[0014] Furthermore, the macroscopic members are either hollow or solid, with both ends of the hollow or solid members being hemispherical structures.

[0015] Furthermore, step S2 specifically includes:

[0016] S21: Calculate macroscopic elements based on the geometric parameters of macroscopic members. e To the k Distance between the axes of macroscopic rods ;

[0017] S22: Based on the calculation results of step S21, solve the... k A macroscopic bar is mapped to a macroscopic unit. e density function This enables the topological representation of macroscopic structures.

[0018] Furthermore, calculate macroscopic unit e up to the th... k Distance between the axes of macroscopic rods The calculation formula used is:

[0019] ;

[0020] in, The center of macroscopic unit e In the macroscopic coordinate system, ( , , ) is the first k The coordinates of the center of the hemispherical structure at one end of a macroscopic member in the macroscopic coordinate system. ( , , ) is the first k The coordinates of the center of the hemispherical structure at the other end of the macroscopic member in the macroscopic coordinate system.

[0021] Furthermore, step S3 specifically includes:

[0022] S31: Calculating Micro-units To the Distance between the axes of the solid rods ;

[0023] S32: Based on the calculation results of step S31, solve the... A solid rod is mapped to a micro-unit. density function ;

[0024] S33: Based on the calculation result of step S32, calculate the first step using the following formula. j Constitutive matrices of microscopic lattice structures:

[0025] ;

[0026] in, For the volume of the macroscopic unit, For initial unit test strain, For the unknown strain within the microcrystalline lattice structure, For the density function The resulting constitutive matrix.

[0027] Furthermore, in step S4, macroscopic units are constructed using the BCP method. e Discrete lattice optimization function :

[0028] ;

[0029] in, The number of microscopic lattice structures. For the first j The constitutive matrix of a microcrystalline lattice structure macroscopic unit e The corresponding number j The weighting coefficients of the constitutive matrix of a microcrystalline lattice structure.

[0030] Furthermore, the firstj The expression of the weight coefficient of the constitutive matrix of the micro-lattice structure is:

[0031] ;

[0032] ;

[0033] ;

[0034] wherein, is a macro unit e corresponding to the discrete design variable of the first micro-lattice structure, is the total number of the category selection variable of the micro-lattice structure, is the parameter of the BCP method corresponding to the first j micro-lattice structure, is the serial number of the category selection variable of the micro-lattice structure, is an intermediate variable without physical meaning, and p is a first penalty coefficient, which is 3.

[0035] Further, in step S6, the optimization model comprises an objective function and a constraint function, and the expression of the optimization model is:

[0036] ;

[0037] ;

[0038] wherein, C is an objective function, is a design variable of a macro rod, is a geometric parameter of the first k macro rod, is a discrete design variable of a micro-lattice structure, is the number of macro units, F, U and K are respectively an external force matrix, a displacement matrix and an overall stiffness matrix, is a unit stiffness matrix, is a node displacement vector, is an initial volume of a macro structure, is a volume fraction, and are respectively a minimum value and a maximum value of the design variable x of the macro rod, and are respectively a minimum value and a maximum value of the discrete design variable, is a density function of the macro rod mapped to the macro unit e , is a linear strain-displacement relationship matrix of the macro unit, is a volume of the macro unit, is the density function of macro-rod mapped to macro-unit, is the second penalty coefficient, taking 3, is taken as 0.001 to avoid singular minimum value.

[0039] Further, the objective function C The calculation formula for calculating the sensitivity of the geometric parameters of the macro-rod is:

[0040] ;

[0041] wherein, is one of the design variables of the macro-rod, is the unit stiffness matrix, is the second penalty coefficient, is the density function of macro-rod mapped to macro-unit, is the density function of macro-rod mapped to macro-unit, is the second penalty coefficient, taking 3;

[0042] The objective function C The calculation formula for calculating the sensitivity of the discrete design variables of the micro-lattice structure is:

[0043] ;

[0044] ;

[0045] wherein, is the first penalty coefficient, taking 3, is the parameter of the BCP method corresponding to the j th micro-lattice structure, , is the index number, is the discrete design variable of the e th micro-lattice structure corresponding to the macro-unit, is a constant, and is not 0.

[0046] Further, in step S7, the optimization algorithm is the MMA algorithm.

[0047] Compared with the prior art, the application can achieve the following beneficial effects:

[0048] ​​(1) The lightweight structure multi-scale parallel optimization method based on lattice discrete optimization, through multi-scale parallel optimization design, uses the geometric parameters of movable deformed rods to describe the macro structure and the micro lattice structure, uses the improved double-value coding parameterization method, referred to as BCP method, solves the local material discontinuity phenomenon in the optimization result, and is easy to extract the geometric parameters of the optimization result.

[0049] (2) The lightweight structure multi-scale parallel optimization method based on lattice discrete optimization realizes the parallel optimization of the discrete combination performance of the macro structure and the micro lattice structure, improves the efficiency of structure optimization, and is convenient for subsequent manufacturing based on the optimization result; the application can perform discrete combination optimization of various types of micro lattice structures, help to quickly locate the position of each lattice in the micro lattice structure, thereby can play the maximum mechanical performance, can quickly provide multiple achievable structure multi-scale optimization design schemes; the application uses the geometric parameters of movable deformed rods to describe the shape of the macro and micro structures, thereby directly extracting the geometric parameters based on the obtained optimization result, and improving the efficiency of post-processing modeling. BRIEF DESCRIPTION OF DRAWINGS

[0050] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The embodiments of the application illustrated in the drawings, and their description, are presented to add generic scope to the application and are not intended to be an undue limitation on the application's scope. In the drawings:

[0051] Figure 1 The flowchart of the lightweight structure multi-scale parallel optimization method based on lattice discrete optimization described in the embodiments of the application;

[0052] Figure 2 The macro structure, macro unit and macro structure initial layout schematic diagram described in the embodiments of the application;

[0053] Figure 3 The structure schematic diagram of the hollow rod described in the embodiments of the application;

[0054] Figure 4 The pre-planned connection position schematic diagram of the micro lattice structure described in the embodiments of the application;

[0055] Figure 5 The structure schematic diagram of the solid rod in the micro lattice structure described in the embodiments of the application;

[0056] Figure 6 The discrete optimization structure schematic diagram of the micro lattice structure described in the embodiments of the application;

[0057] Figure 7A solid and hollow parallel optimization result chart obtained by using 4 kinds of lattice structures is shown in the embodiment of the present invention;

[0058] Figure 8 A solid and hollow parallel optimization result chart obtained by using 8 kinds of lattice structures is shown in the embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and do not constitute a limitation on the present invention.

[0060] It should be noted that the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.

[0061] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present invention and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second" and the like are only used for description purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited by "first", "second" and the like can explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0062] In the description of the present invention, it should be noted that unless otherwise specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the communication between two elements. For those skilled in the art, the specific meaning of the above terms in the present invention can be understood through specific circumstances.

[0063] The present application is oriented to three-dimensional hollow structure design, uses geometric parameters of movable deformed rods to describe macroscopic structure and microscopic lattice structure, uses an improved double-value coding parameterization method (BCP method) to construct a lattice discrete combination optimization scheme of multiple types of manufacturability, and forms a kind of explicit lightweight structure multi-scale parallel optimization design.

[0064] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0065] As shown in Figure 1 The present application provides a lightweight structure multi-scale parallel optimization method based on lattice discrete optimization, specifically comprising the following steps:

[0066] S1: obtaining the initial layout of the macroscopic structure, and performing grid processing on the macroscopic structure to obtain macroscopic units, each macroscopic unit corresponding to a microscopic lattice structure;

[0067] S2: based on the geometric parameters of the macroscopic rods used by the macroscopic structure, constructing a density function of the macroscopic rods mapped to the macroscopic units, to realize the topological expression of the macroscopic structure;

[0068] S3: the microscopic lattice structure is constructed by solid rods, the microscopic lattice structure is subjected to grid processing to obtain microscopic units, and a density function of the solid rods mapped to the microscopic units is constructed based on the geometric parameters of the solid rods to obtain the constitutive matrix of the microscopic lattice structure;

[0069] S4: based on the BCP method, and in combination with the constitutive matrix of the microscopic lattice structure, constructing a discrete lattice optimization function of the macroscopic units;

[0070] S5: performing finite element analysis on the discrete lattice optimization function to obtain the node displacement vector of the macroscopic units;

[0071] S6: based on the node displacement vector of the macroscopic units, the macroscopic unit density function and the constitutive matrix of the microscopic lattice structure, constructing an optimization model, and based on the objective function, calculating the sensitivity of the macroscopic rod geometric parameters and the sensitivity of the discrete design variables of the microscopic lattice structure;

[0072] S7: inputting the calculation results of step S6 and the objective function into an optimization algorithm, and the optimization algorithm updates the macroscopic rod geometric parameters and the discrete design variables of the microscopic lattice structure, if the number of updates is less than a preset iteration number or the updated macroscopic rod geometric parameters and the discrete design variables of the microscopic lattice are less than the respective preset values, then re-executing step S2, otherwise completing the lattice discrete optimization.

[0073] The macroscopic rod geometry parameters are explained as follows: if the design requirement is to obtain a hollow structure, a hollow rod is selected as the macroscopic rod, the middle section of the hollow rod is a double-layer coaxial cylindrical structure, the two ends of the hollow rod are hemispherical structures, the overall structure of the hollow rod is a capsule-shaped hollow structure, the centers of the hemispherical structures at the two ends are located at coordinates of the macroscopic coordinate system, and the radius of the inner hollow cylinder of the double-layer coaxial cylindrical structure is , and the thickness of the hollow rod is , that is, there are 8 macroscopic rod geometry parameters; if the design requirement is to obtain a solid structure, a solid rod is selected as the macroscopic rod, and there are 7 macroscopic rod geometry parameters, the middle section of the solid rod is a solid cylindrical structure, the two ends of the solid rod are hemispherical structures, and the centers of the hemispherical structures at the two ends are located at coordinates of the macroscopic coordinate system, which are 6 geometry parameters, and the radius of the solid cylindrical structure is set to , and it should be noted that the structures of the macroscopic rods are the same.

[0074] Further, the preset value and the preset iteration number are set according to actual requirements.

[0075] Example 1

[0076] Step 1, define the design domain and working conditions, and construct the macroscopic unit of the design domain, such as Figure 2 (a) in which is a macroscopic structure; each macroscopic unit corresponds to a microcrystalline lattice structure, Figure 2 (b) in which is a grid division of the macroscopic structure; Figure 2 (c) in which is an initial layout of the macroscopic structure using a solid rod, Figure 2 (d) in which is an initial layout of the macroscopic structure using a hollow rod.

[0077] The initial layout of the macroscopic structure can be selected using a hollow rod or a solid rod according to the design requirement. If the design requirement is to obtain a hollow structure, a hollow rod is selected as the macroscopic rod, and if the design requirement is to obtain a solid structure, a solid rod is selected as the macroscopic rod.

[0078] Step 2, based on the geometry parameters of the macroscopic rod used by the macroscopic structure, construct the density function of the macroscopic rod mapping to the macroscopic unit, and realize the topological expression of the macroscopic structure.

[0079] Taking the macroscopic structure using a hollow rod as an example, Figure 3 ​​​​​​(a) in the figure describes the macroscopic coordinate system x-y-z In the middle, the projection of the k-th hollow rod onto the macroscopic element, Figure 3 (b) describes the external shape of the hollow rod, specifically consisting of two cylinders, inner and outer. Figure 3 (c) describes the internal cross-sectional shape of the hollow member through the axis. The hollow member contains eight geometric parameters: the coordinates of the centers of the hemispherical structures at both ends of the hollow member. ( , , )and ( , , The radius of the inner cylinder in the middle section of the hollow rod. And the thickness of the hollow rod. .

[0080] Based on macro units e To the k Distance between the axes of macroscopic rods Solve the first... k A macroscopic bar is mapped to a macroscopic unit. e density function :

[0081] ;

[0082] ;

[0083] ;

[0084] in, It is the element density function of the outer member of the hollow member. It is the element density function of the inner members of the hollow member. To select the number of macroscopic members, This is a constant used to control the convergence of the density function; here it is set to 6.

[0085] If the macrostructure uses solid rods, the parameter setting method is the same as that for hollow rods, except that the radius of the cylinder in the middle section of the solid rod is different. There is no need to set the thickness of the rods; furthermore, macroscopic units... e To the k Distance between the axes of macroscopic rods The solution process is the same for both hollow and solid members.

[0086] Calculate macroscopic unit e to the th k Distance between the axes of macroscopic rods The calculation formula used is:

[0087] ;

[0088] wherein, is the center of the macroscopic unit e is the coordinate of the center of the macroscopic unit e in the macroscopic coordinate system, is the coordinate of the center of the macroscopic unit e in the macroscopic coordinate system, , , is the coordinate of the center of the hemispherical structure of one end of the macroscopic rod member in the macroscopic coordinate system, k is the coordinate of the center of the hemispherical structure of one end of the macroscopic rod member in the macroscopic coordinate system, is the coordinate of the center of the hemispherical structure of one end of the macroscopic rod member in the macroscopic coordinate system. . k

[0089] In addition, if the macroscopic structure adopts solid rod members, the density function of the macroscopic rod member mapped to the macroscopic unit e k :

[0090] .

[0091] Step three, the micro-lattice structure is all solid rod members, the explicit lattice finite element model is constructed by using the improved double-value coding parameterization method and the geometric parameters of the solid rod members (specifically, solid movable and deformable rod members), and the interpolation function form expression of the material matrix of the macroscopic unit is: e

[0092] ;

[0093] wherein, is the number of micro-lattice structures, is the constitutive matrix of the micro-lattice structure, j is the corresponding weight coefficient, and the sum of the total weights is 1.

[0094] ;

[0095] ;

[0096] ; As shown in FIG. 8, in the design stage, the existence of the material is planned in advance in the orange part of the 8 corners in the micro-lattice structure, so as to ensure the connectivity between the micro-lattice structures. Then, the basic shape of the micro-lattice structure is established by using the geometric parameters of the solid rod members,

[0097] Figure 4 Figure 5 ​​​​​​​(a) in FIG. 1 depicts the mapping of the micro local coordinate system In (b) in FIG. 1, the micro lattice structure is composed of 7 geometric parameters of the solid rod, including the coordinates of the centers of the two hemispherical structures at the ends of the solid rod in the micro coordinate system and the radii of the two hemispherical structures The micro lattice structure is divided into micro units in the region where the micro lattice structure is located Figure 5 In (b) in FIG. 1, the micro lattice structure is composed of 7 geometric parameters of the solid rod, including the coordinates of the centers of the two hemispherical structures at the ends of the solid rod in the micro coordinate system and the radii of the two hemispherical structures The distance from the i-th micro unit to the j-th micro solid rod is The density function of the solid rod is defined as : ;

[0098] ;

[0099] The constitutive matrix of the i-th micro lattice structure can be calculated by the material distribution in the micro lattice structure: j

[0100] ; wherein, V is the volume of the micro lattice structure, which is also the volume of the macro unit; E is the initial unit test strain; and K is the constitutive matrix obtained by the penalty function.

[0101] Step four, based on the BCP method and combined with the constitutive matrix of the micro lattice structure, a discrete lattice optimization function of the macro unit is constructed, as shown in FIG. 1, there are 8 types of lattice structures, D1~D8, and the weight coefficient is adjusted according to the selected type, if only one type is selected, the corresponding weight coefficient is selected as 1. Step five, finite element analysis is performed on the discrete lattice optimization function, and the node displacement vector of the macro unit is obtained. Step six, based on the node displacement vector of the macro unit, the density function of the macro rod mapped to the macro unit and the constitutive matrix of the micro lattice structure, an optimization model is constructed, and the sensitivity of the geometric parameters of the macro rod and the sensitivity of the discrete design variables of the micro lattice structure are calculated based on the objective function.

[0102] Figure 6 Step seven, iterative optimization and convergence judgment. The corresponding design variables are updated by the MMA algorithm, if the preset value or the maximum iteration number of the design variables is reached, the optimization is ended; otherwise, return to step two to continue optimization.

[0103] Step seven, iterative optimization and convergence judgment. The corresponding design variables are updated by the MMA algorithm, if the preset value or the maximum iteration number of the design variables is reached, the optimization is ended; otherwise, return to step two to continue optimization.

[0104] Step seven, iterative optimization and convergence judgment. The corresponding design variables are updated by the MMA algorithm, if the preset value or the maximum iteration number of the design variables is reached, the optimization is ended; otherwise, return to step two to continue optimization.

[0105] Step seven, iterative optimization and convergence judgment. The corresponding design variables are updated by the MMA algorithm, if the preset value or the maximum iteration number of the design variables is reached, the optimization is ended; otherwise, return to step two to continue optimization.

[0106] ​​​​​The establishment of macro coordinate system and micro coordinate system is well known in the field of material mechanics, solid physics and crystal lattice structure analysis, and will not be described here.

[0107] The elastic modulus and Poisson ratio of the materials used in the macro structure and micro structure are set to 1 and 0.3 respectively. Figure 7 (a) in (b) in (c) in Figure 7 The corresponding optimization in (b) in (c) in adopts four kinds of lattice structures with different weight coefficients, and the percentage of the green lattice is almost negligible, which also shows that if a lattice structure is selected that cannot be connected at the predetermined position, it can also be ignored in the optimization process. Moreover, the flexibility value of the hollow optimization result is 723, which is lower than the flexibility value 1384 of the solid optimization result. If one kind of lattice structure is replaced, Figure 7 (c) shows the corresponding hollow optimization result and the proportion of the lattice, and the flexibility value of the hollow optimization result is 539. If eight kinds of lattice structures are used, as shown in Figure 8 , the optimization result with a flexibility value of 459 (using hollow rod members to build the macro structure), Figure 8 (a) in (b) in (c) in (a) is the image result of the density function of the macroscopic rod mapped to the macroscopic unit after optimization using hollow rod members to build the macro structure, Figure 8 (b) is the cross-sectional shape of the optimized macro structure using hollow rod members to build the macro structure, Figure 8 (c) is the optimization result of the corresponding micro lattice structure of the macro structure using hollow rod members to build the macro structure. This optimization result is not only easy to manufacture, but also almost only retains one kind of lattice structure, which shows that this kind of lattice structure plays the best mechanical performance in this case. In short, these examples well illustrate the high efficiency of the present application.

[0108] The Sigmoid function is used in steps two and three to express the unit density function. If the hyperbolic tangent translation function or other 0-1 functions are selected, similar effects can also be achieved.

[0109] The present application performs finite element analysis under the condition that the structure is in linear elastic small deformation. Any improvement of other finite element analysis such as considering large deformation, buckling and dynamics should be included in the scope of protection of the discrete optimization design of the lattice structure of the present application.

[0110] It should be understood that the various forms of the flow shown above can be reordered, added or deleted steps. For example, the steps described in the present application can be executed in parallel, sequentially or in different order, as long as the desired results of the technical solutions disclosed in the present application can be achieved, which is not limited herein.

[0111] The above detailed description does not limit the scope of the application. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the application shall be included in the scope of the application.

Claims

1. A multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization, characterized in that: Specifically, the steps include the following: S1: Obtain the initial layout of the macroscopic structure and perform gridding on the macroscopic structure to obtain macroscopic units, each macroscopic unit corresponding to a microscopic lattice structure; S2: Based on the geometric parameters of the macro members used in the macro structure, construct the density function that maps the macro members to the macro elements; S3: The micro-lattice structure is constructed using solid rods. The micro-lattice structure is then meshed to obtain micro-units. Based on the geometric parameters of the solid rods, a density function is constructed that maps the solid rods to the micro-units to obtain the constitutive matrix of the micro-lattice structure. S4: Based on the BCP method, and combined with the constitutive matrix of the micro-lattice structure, construct the discrete lattice optimization function of the macro-unit; In step S4, macroscopic units are constructed using the BCP method. e Discrete lattice optimization function : ； in, The number of microscopic lattice structures. For the first j The constitutive matrix of a microcrystalline lattice structure macroscopic unit e The corresponding number j The weighting coefficients of the constitutive matrix of a microcrystalline lattice structure; No. j The expression for the weighting coefficients of the constitutive matrix of a certain microcrystalline lattice structure is as follows: ； ； ； in, macroscopic unit e The corresponding number Discrete design variables for a microcrystalline lattice structure The total number of variables to choose from for the types of microscopic lattice structures. For the BCP method corresponding to the first j The parameters of the microcrystalline lattice structure, The sequence number of the variable is selected for the type of microcrystalline lattice structure. This is an intermediate variable with no physical meaning; p is the first penalty coefficient, which is set to 3. S5: Perform finite element analysis on the discrete lattice optimization function to obtain the nodal displacement vectors of the macroscopic elements; S6: An optimization model is constructed based on the nodal displacement vector of macroscopic units, the density function of macroscopic bars mapped to macroscopic units, and the constitutive matrix of microscopic lattice structure. The sensitivity of the geometric parameters of macroscopic bars and the sensitivity of the discrete design variables of microscopic lattice structure are calculated based on the objective function. S7: Input the calculation results and objective function of step S6 into the optimization algorithm. The optimization algorithm updates the discrete design variables of the macroscopic bar geometry parameters and the microscopic lattice structure. If the number of updates is less than the preset number of iterations or the updated macroscopic bar geometry parameters and the discrete design variables of the microscopic lattice are both less than their respective preset values, then step S2 is executed again. Otherwise, the lattice discrete optimization is completed.

2. The lightweight structure multi-scale parallel optimization method based on lattice discretization optimization according to claim 1, characterized in that: The macroscopic members are hollow or solid members, and both ends of the hollow or solid members are hemispherical structures.

3. The lightweight structure multi-scale parallel optimization method based on lattice discretization optimization according to claim 2, characterized in that: Step S2 specifically includes: S21: Calculate macroscopic elements based on the geometric parameters of macroscopic members. e To the k Distance between the axes of macroscopic rods ; S22: Based on the calculation results of step S21, solve the... k A macroscopic bar is mapped to a macroscopic unit. e density function This enables the topological representation of macroscopic structures.

4. The multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization according to claim 3, characterized in that: Calculate macroscopic unit e to the th k Distance between the axes of macroscopic rods The calculation formula used is: ； in, The center of macroscopic unit e In the macroscopic coordinate system, ( , , Let be the coordinates of the center of the hemispherical structure at one end of the k-th macroscopic member in the macroscopic coordinate system. ( , , Let be the coordinates of the center of the hemispherical structure at the other end of the kth macroscopic member in the macroscopic coordinate system.

5. The multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization according to claim 1, characterized in that: Step S3 specifically includes: S31: Calculating Micro-units To the Distance between the axes of the solid rods ; S32: Based on the calculation results of step S31, solve the... A solid rod is mapped to a micro-unit. density function ; S33: Based on the calculation result of step S32, calculate the first step using the following formula. j Constitutive matrices of microscopic lattice structures: ； in, For the volume of the macroscopic unit, For initial unit test strain, For strain within the microcrystalline lattice structure, For the density function The resulting constitutive matrix.

6. The multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization according to claim 1, characterized in that: In step S6, the optimization model includes an objective function and constraint functions, and the expression of the optimization model is: ； ； in, C Let be the objective function. For the design variables of macroscopic rods, For the first k Geometric parameters of a macroscopic bar, Discrete design variables for microcrystalline lattice structures, This refers to the number of macroscopic units, where F, U, and K are the external force matrix, displacement matrix, and overall stiffness matrix, respectively. The element stiffness matrix, It is a nodal displacement vector. The initial volume of the macrostructure. It is the volume fraction. and Let x be the minimum and maximum values ​​of the design variable x for the macroscopic member, respectively. and These are the minimum and maximum values ​​of the discrete design variables, respectively. Mapping macroscopic members to macroscopic units e density function, This is the linear strain-displacement relationship matrix for a macroscopic element. For the volume of the macroscopic unit, The density function that maps macroscopic bars to macroscopic elements. Power of 1 The second penalty coefficient is set to 3. To avoid singular local minima, we set it to 0.

001.

7. The multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization according to claim 6, characterized in that: Using the objective function C The formula used to calculate the sensitivity of the geometric parameters of macroscopic members is as follows: ； in, As one of the design variables for macroscopic members, The element stiffness matrix, This is the second penalty coefficient. The density function is used to map macroscopic bars to macroscopic elements. The density function that maps macroscopic bars to macroscopic elements. Power of 1 The second penalty coefficient is set to 3. Using the objective function C The formula used to calculate the sensitivity of discrete design variables for microcrystalline lattice structures is as follows: ； ； in, The first penalty coefficient is set to 3. For the BCP method corresponding to the first j The parameters of the microcrystalline lattice structure, , For index number, macroscopic unit e The corresponding number The discrete design variables for the microscopic lattice structure, where β is a constant and not equal to 0.

8. The multi-scale parallel optimization method for lightweight structures based on lattice discretization optimization according to claim 6, characterized in that: In step S7, the optimization algorithm is the MMA algorithm.

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