Feature-driven structure and embedded flow channel collaborative optimization design method

Abstract

The invention discloses a feature-driven structure and embedded flow channel collaborative optimization design method, and the method comprises the steps: dividing a design domain into finite element grids, and obtaining a finite element model; constructing a flow channel area and a lightening hole area in the design domain, and determining a first density field of the control flow channel area and a second density field of the lightening hole area; performing material attribute interpolation on the finite element model based on the first density field and the second density field; preset conditions are applied to the finite element model, and a structural mechanical analysis model and a fluid flow simulation model are established; on the basis of the structural mechanical analysis model and the fluid flow simulation model, according to a preset design variable and a change range, constructing a multi-objective optimization model; and performing optimization design by calculating the sensitivity of the target function and the constraint function about the preset design variable. According to the method, collaborative optimization design of the structure and the embedded runner is achieved, the design process is simplified, and the design efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of finite element method, and particularly relates to a feature-driven structure and embedded flow channel collaborative optimization design method. BACKGROUND

[0002] The existing aircraft structure generally adopts a design scheme of load-bearing structure and fluid pipeline analysis. The pipeline is fixed to the outside of the load-bearing structure through supports, clamps, joints and other connecting accessories. This separated design scheme has two problems: (1) the weight of the load-bearing structure and the fluid pipeline is superimposed, and a large number of connecting accessories generate parasitic weight, resulting in redundancy of the total weight of the structure system; (2) there is a large amount of structural coupling between the fluid pipeline and the load-bearing structure, and under the action of external multi-source load, the pipeline is prone to rupture accidents due to the incoordination of pipeline and structure deformation. The functional design of the structure integrates the fluid pipeline into the load-bearing structure to obtain a functional structure with embedded flow channels, which has the function of transporting fluid in addition to bearing, and eliminates the large mass of connecting accessories, which is of great significance for breaking through the weight limit of the aircraft and improving the comprehensive performance.

[0003] At present, the functional structure with embedded flow channels mainly adopts an empirical design mode, and lacks a systematic theoretical design method, so it is difficult to obtain a design result with optimal comprehensive performance in terms of bearing performance and fluid drag reduction. When an advanced topology optimization method is used to design the functional structure with embedded flow channels, the structure bearing optimization and the flow channel layout optimization are usually performed independently: the structure bearing optimization scheme pre-fixes the flow channel layout and form, and can only realize lightweight design of the structure, and cannot optimize the fluid flow characteristics; the flow channel layout optimization scheme only considers the optimization of the flow path, and does not consider the design of the bearing structure, so it is difficult to realize matched design of the structure bearing and fluid drag reduction. SUMMARY

[0004] The embodiment of the present application provides a feature-driven structure and embedded flow channel collaborative optimization design method, and solves the technical problem that the optimization of the fluid flow path and the bearing structure is usually performed independently in the prior art, and it is difficult to realize matched design of the structure bearing and fluid drag reduction.

[0005] The embodiment of the application provides a feature-driven structure and embedded runner collaborative optimization design method, the method comprises the following steps: dividing a design domain into a finite element grid to obtain a finite element model; constructing a runner area and a weight reduction hole area in the design domain, and determining a first density field for controlling the runner area and a second density field for the weight reduction hole area; based on the first density field and the second density field, material property interpolation is performed on the finite element model to obtain the elastic modulus and flow resistance coefficient of each finite element grid; a predetermined condition is applied to the finite element model to establish a structural mechanics analysis model and a fluid flow simulation model; wherein the predetermined condition includes solid constraints, loads, and fluid inlet and outlet and wall boundary conditions; based on the structural mechanics analysis model and the fluid flow simulation model, a multi-objective optimization model is constructed according to a predetermined design variable and a change range; wherein in the multi-objective optimization model, the optimization target is the weighted sum of the overall strain energy and fluid flow dissipation energy of the design domain, the constraint function includes the volume fraction of the runner area and the volume fraction of the weight reduction hole area, and the initial value and the change range of the predetermined design variable; the sensitivity of the objective function and the constraint function with respect to the predetermined design variable is calculated to perform optimization design.

[0006] In a possible implementation, the constructing the runner area and the weight reduction hole area in the design domain comprises: defining the geometric profile of the runner area by adopting worm-like features in the design domain, and defining the geometric profile of the weight reduction hole area by adopting closed B-spline features; calculating a first implicit level set function of each worm-like feature and a second implicit level set function of each closed B-spline feature; performing maximum operation on a plurality of the first implicit level set functions and a plurality of the second implicit level set functions respectively to realize Boolean AND of a plurality of the worm-like features and a plurality of the closed B-spline features, and obtain a first implicit level set maximum function and a second implicit level set maximum function.

[0007] In a possible implementation, the determining the first density field for controlling the runner area and the second density field for the weight reduction hole area comprises: mapping the first implicit level set maximum function and the second implicit level set maximum function by adopting a smooth form of Heaviside function respectively to obtain the first density field and the second density field.

[0008] In a possible implementation, the material property interpolation is performed on the finite element model by adopting the following interpolation model: Wherein, α is the flow resistance coefficient, E is the elastic modulus, α max is the flow resistance coefficient of the solid area in the design domain, q is a positive number for controlling the curvature of the interpolation model, E s is the solid elastic modulus, E f is the fluid elastic modulus, γfluid is the first density field, γ void is the second density field.

[0009] In a possible implementation, the preset design variables include: control points and control radii of each of the worm-like features, and center points and control radii of the closed B-spline feature.

[0010] In a possible implementation, before the step of applying preset conditions to the finite element model, establishing a structural mechanics analysis model and a fluid flow simulation model, the method further includes: defining a non-interference constraint function based on the first density field and the second density field, and defining the flow channel region and the weight-reducing hole region.

[0011] In a possible implementation, the step of performing optimization design includes: performing optimization design by using a mathematical programming algorithm.

[0012] The technical solutions provided in the embodiments of the present application have at least the following technical effects:

[0013] The feature-driven structural and embedded flow channel collaborative optimization design method provided in the embodiments of the present application can simultaneously optimize the flow features and the weight-reducing hole region of the design domain, realize collaborative design of fluid transmission and structural bearing functions, does not need to alternately iterate design, simplifies the design process, and improves the design efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the description of the embodiments of the present application will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] Figure 1 A structural schematic diagram of a calculation model provided in the embodiments of the present application;

[0016] Figure 2 A geometric profile of a flow channel region and a geometric profile of a weight-reducing hole region provided in the embodiments of the present application;

[0017] Figure 3 An optimization result of the multi-objective optimization model shown in the embodiments of the present application; Figure 1 An optimization result of the multi-objective optimization model shown in the embodiments of the present application; An optimization result of the multi-objective optimization model shown in the embodiments of the present application;

[0018] An optimization result of the multi-objective optimization model shown in the embodiments of the present application; Figure 4 A flowchart of the feature-driven structural and embedded flow channel collaborative optimization design method provided in the embodiments of the present application; A flowchart of the feature-driven structural and embedded flow channel collaborative optimization design method provided in the embodiments of the present application;

[0019] A flowchart of the feature-driven structural and embedded flow channel collaborative optimization design method provided in the embodiments of the present application; Figure 5The flowchart for constructing the flow channel region and the weight reduction hole region is provided in the embodiments of the present application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be clearly and completely described in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0021] In the description of the embodiments of the present application, the terms “first” and “second” and the like are used to distinguish different objects, rather than to describe a specific order of the objects. It should be understood that the terms thus used can be interchanged under appropriate circumstances, which is merely a distinguishing way adopted in the description of the embodiments of the present application for the objects with the same attribute. In addition, the terms “include” and “have” and any variations thereof are intended to cover the inclusions without exclusivity, so that the processes, methods, systems, products or devices containing a series of units do not have to be limited to those units, but can include other units not clearly listed or inherent to the processes, methods, systems, products or devices.

[0022] The words “exemplary” or “for example” are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as “exemplary” or “for example” should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the exemplary or for example embodiments are presented to best explain the present application and its advantages and functions.

[0023] In order to better understand the technical solutions of the embodiments of the present application, the main terms related to the embodiments of the present application are briefly introduced as follows.

[0024] Design domain: In topology optimization, the design domain refers to a predefined geometric space range, which is an initial region allowing material distribution or adjustment in the optimization process. The design domain is defined by a three-dimensional or two-dimensional geometric model, and the boundary conditions of material distribution are clear. Engineers need to apply external conditions such as mechanical load, support constraint, etc. in it, and determine the invariable region (such as connection point, mounting position, etc.). The material distribution is iteratively optimized in the design domain by mathematical algorithm, and the low-efficiency material is removed and the high-stress region is reserved, finally generating a lightweight structure meeting the performance target.

[0025] Density field: The density field is a continuous function or a set of discrete variables that describes the distribution state of the material in the design domain; a value of 1 of the density field indicates that the region is completely filled with the material; a value of 0 of the density field indicates that the region is not filled with the material, and a value of the density field between 0 and 1 corresponds to the partial existence of the material, which needs to be mapped to the actual physical properties (such as the elastic modulus) through an interpolation function to realize the optimizability.

[0026] Flow field: The flow field is used to describe the dynamic distribution state of the fluid in space; in the topology optimization process, the flow resistance is often reduced by adjusting the geometric shape of the flow channel (such as the flow channel of the liquid cooling plate).

[0027] Displacement field: The displacement field represents the deformation response of the structure under the action of the load; in the topology optimization process, the material deformation is often described by the node displacement vector, and the strain energy, stiffness and other objective functions are calculated by coupling with the density field.

[0028] Material property interpolation: The material property interpolation is a mathematical method for mapping the design variable (such as the density field) to the physical property (such as the elastic modulus, thermal conductivity) in the topology optimization, which is often applied to flow-thermal coupled optimization, structure lightweighting, etc.

[0029] The feature-driven structure and embedded flow channel collaborative optimization design method provided in the present application will be described in detail below in combination with the accompanying drawings.

[0030] As shown in Figure 4 , the feature-driven structure and embedded flow channel collaborative optimization design method provided in the embodiments of the present application includes steps S401 to S407.

[0031] S401, dividing the design domain into finite element meshes to obtain a finite element model.

[0032] The design domain with continuous structure is discretized into a large number of small grid elements, which provides a basis for subsequent optimization calculation. Exemplarily, the finite element mesh can be a tetrahedral structure.

[0033] S402, constructing a flow channel region and a weight reduction hole region in the design domain.

[0034] Exemplarily, the flow channel region and the weight reduction hole region constructed on the design domain are as shown in Figure 2 .

[0035] Specifically, in the embodiments of the present application, as shown in Figure 5 , step S402 includes steps S501 to S503.

[0036] S501, defining the geometric profile of the flow channel region by using the worm-like feature in the design domain, and defining the geometric profile of the weight reduction hole region by using the closed B-spline feature.

[0037] Each flow channel region is defined by a plurality of control points and a control radius at each control point. For example, each flow channel region is defined by six control point coordinates P1, P2, ..., P6 and six corresponding control radii r1, r2, ..., r6.

[0038] Each weight reduction hole area is determined by the center point coordinates and multiple control radii. For example, each weight reduction hole area is determined by the center point coordinates (x0, y0) and 12 control radii R1, R2, ..., R 12 Sure.

[0039] S502 : Calculate a first implicit level set function of each worm-like feature and a second implicit level set function of each closed B-spline feature.

[0040] The first implicit level set function φ of each worm-like feature at the finite element mesh node (x, y) is f as follows:

[0041]

[0042] Among them, B i,p is the i-th basis function of the p-order B-spline, ξ′ is the mapping parameter of the finite element mesh node on the B-spline, r i is the ith control radius of each worm-like feature, P i is the coordinate of the i-th control point, and ||·|| is the length of the plane vector.

[0043] The second implicit level set function φ of each closed B-spline feature at the finite element mesh node (x, y) v as follows:

[0044]

[0045] Among them, R i is the i-th control radius of each closed B-spline feature, and (x0, y0) is the coordinate of the center point of the closed B-spline feature.

[0046] S503 , performing maximum operations on the multiple first implicit level set functions and the multiple second implicit level set functions respectively to achieve a Boolean union of the multiple worm-like features and the multiple closed B-spline features, and obtaining a first implicit level set maximum function and a second implicit level set maximum function.

[0047] The first implicit level set maximum function of the merged flow channel area is: The second implicit level set maximum function of the merged weight-reducing hole area is:

[0048] For example, Figure 2Two flow passage regions and 17 lightening hole regions are shown.

[0049] S403, determine a first density field of the flow passage region and a second density field of the lightening hole region.

[0050] The first implicit level set maximum function and the second implicit level set maximum function are mapped by using the smooth form of the Heaviside function respectively, to obtain the first density field and the second density field. The calculation formula is: Wherein, γ fluid is the first density field, γ void is the second density field, H(·) is the smooth form of the Heaviside function, Φ f is the first implicit level set function of the flow passage region, and Φ v is the second implicit level set function of the lightening hole region.

[0051] S404, based on the first density field and the second density field, material property interpolation is performed on the finite element model.

[0052] Specifically, the interpolation model is used to perform material property interpolation on the design domain. In the embodiments of the present application, the interpolation model is as follows:

[0053]

[0054] Wherein, α is the flow resistance coefficient, E is the elastic modulus, α max is the flow resistance coefficient of the solid region in the design domain, q is a positive number controlling the curvature of the interpolation model, E s is the solid elastic modulus, E f is the fluid elastic modulus, γ fluid is the first density field, γ void is the second density field.

[0055] S405, a predetermined condition is applied to the design domain to establish a structural mechanics analysis model and a fluid flow simulation model. The predetermined condition includes solid constraint, load, and fluid inlet and outlet and wall boundary conditions.

[0056] The obtained structural mechanics analysis model is used to calculate the overall strain energy, and the obtained fluid flow simulation model is used to calculate the fluid flow dissipation energy.

[0057] S406, based on the structural mechanics analysis model and the fluid flow simulation model, a multi-objective optimization model is constructed according to the preset design variable and the variation range.

[0058] Specifically, in the multi-objective optimization model, the optimization objective is a weighted sum of the overall strain energy of the design domain and the fluid flow dissipation energy, and the constraint functions include the volume fraction of the flow passage region and the volume fraction of the weight-reducing hole region, as well as the initial value and the variation range of the preset design variable.

[0059] When the flow passage region is defined by the worm-like feature and the weight-reducing hole region is defined by the closed B-spline feature, the preset design variable includes the control point and the control radius of each worm-like feature, and the center point and the control radius of the closed B-spline feature. At this time, the optimization objective and the constraint functions of the multi-objective optimization model are as follows:

[0060] Findα=(P k ,r k ,(x0,y0),R k )

[0061]

[0062] where J is the objective function, w is the weight coefficient, ψ is the fluid flow dissipation energy, C is the overall strain energy of the structure, and the normalized values ψ0 and C0 in the objective function are determined by the simulation results of the initial layout. The upper limit of the volume fraction of the fluid is set to 0.2, and the lower limit of the volume fraction of the weight-reducing hole is set to 0.3. α i are the upper limit and the lower limit of the preset design variable, respectively, and n is the number of design variables.

[0063] S407, the optimization design is performed by calculating the sensitivity of the objective function and the constraint function with respect to the preset design variable.

[0064] In the embodiments of the present application, a mathematical programming algorithm is used for optimization design. In other embodiments of the present application, a moving asymptote method (English: Moving Asymptotes Method; abbreviated: MMA) can also be used for optimization design.

[0065] Figure 3 The optimization results of the calculation model in Figure 1 are shown.

[0066] Further, in the embodiments of the present application, before step S404, the method further includes: based on the first density field and the second density field, and a non-interference constraint function defining the flow passage region and the weight-reducing hole region. The constraint function in the multi-objective optimization module further includes the non-interference constraint function.

[0067] ​​​The non-interference constraint function can avoid the overlap of the flow channel area and the weight-reducing hole area, which may lead to errors in the optimization results. At this time, the optimization objectives and constraint functions of the multi-objective optimization model are as follows:

[0068] Findα=(P k ,r k ,(x0,y0),R k )

[0069]

[0070] Where g is the non-interference constraint function.

[0071] Below Figure 1 The above method is illustrated by taking the optimization design of a cantilever beam structure with one end fixed under terminal pressure and an embedded flow channel with a given inlet and outlet as an example. The length of the spatial cantilever beam is 10 mm, the width is 5 mm, and the thickness is 1 mm. The left boundary surface adopts a fixed constraint, and a vertical downward concentrated force of 1 N is applied to the midpoint of the lower right corner. The lower left and upper right are the flow inlet and flow outlet respectively, and the inlet normal velocity is 0.1 m / s. The rest are fixed wall surfaces, and a no-slip boundary is adopted. For this example, the topology optimization of the drag reduction flow channel and the load-bearing structure is performed simultaneously.

[0072] Step 1: Figure 1 The rectangular parallelepiped structure shown is used as the design domain, and the design domain is divided into a finite element mesh in the shape of a tetrahedron with a side length of 0.3 mm.

[0073] Step 2: In the design domain, the worm-like feature is used to define the geometric contour of the flow channel area, and the closed B-spline feature is used to define the geometric contour of the weight-reducing hole area.

[0074] Step 3: Calculate the first implicit level set function of each worm-like feature and the second implicit level set function of each closed B-spline feature.

[0075] Each worm-like feature is determined by the coordinates of six control points P1, P2, ..., P6 and the corresponding six control radii r1, r2, ..., r6. The first implicit level set function φ of each worm-like feature at the finite element mesh node (x, y) is f as follows:

[0076]

[0077] Where B i,p is the i-th basis function of the p-order B-spline, ξ′ is the mapping parameter of the finite element mesh node on the B-spline, r i is the ith control radius of each flow channel region, P i is the coordinate of the i-th control point, and ||·|| is the length of the plane vector.

[0078] where each closed B-spline feature is defined by a center point coordinate (x0, y0) and 12 control radii R1, R2,..., R12. 12 determine a second implicit level set function φ v as follows:

[0079]

[0080] where R i is the i-th control radius of each closed B-spline feature, and (x0, y0) is the center point coordinate of each closed B-spline feature.

[0081] Step four, perform maximum value operation on the plurality of first implicit level set functions and the plurality of second implicit level set functions respectively, and perform Boolean AND on the two initial worm-like features and the 17 closed B-spline features to obtain the geometric profile of the merged flow channel region and the geometric profile of the weight-reducing hole region.

[0082] The first implicit level set maximum function of the merged flow channel region is: The second implicit level set maximum function of the merged weight-reducing hole region is:

[0083] Step five, map the first implicit level set maximum function and the second implicit level set maximum function using a smooth Heaviside function to obtain the first density field γ fluid and the second density field γ void .

[0084] The first implicit level set function Φ f inside each worm-like feature is positive, and the corresponding density value is 1; the density value outside the flow channel region is 0; similarly, the second implicit level set function Φ v inside each closed B-spline feature is positive, and the corresponding density value is 1; the density value outside the weight-reducing hole region is 0. The two first density fields and second density fields are calculated by the following formula:

[0085]

[0086] where H(·) is a smooth Heaviside function, Φ f is the first implicit level set function, and Φ v is the second implicit level set function.

[0087] Step six, define a non-interference constraint function of the flow channel region and the weight-reducing hole region based on the first density field and the second density field. The constraint function in the multi-objective optimization module further includes the non-interference constraint function.

[0088] Step seven, based on the first density field and the second density field, material attribute interpolation is performed on the finite element model by using the following interpolation model:

[0089]

[0090] wherein, α is the flow resistance coefficient, E is the elastic modulus, α max is the flow resistance coefficient of the solid region in the design domain, q is a positive number controlling the curvature of the interpolation model, E s is the solid elastic modulus, E f is the fluid elastic modulus, γ fluid is the first density field, γ void is the second density field.

[0091] Step eight, a structural mechanics analysis model and a fluid flow simulation model are established by applying preset conditions to the design domain. The preset conditions include solid constraints, loads, and fluid inlet and outlet and wall boundary conditions.

[0092] Step nine, based on the structural mechanics analysis model and the fluid flow simulation model, an optimization model is constructed according to 18 design variables (6 x and y coordinates and 6 control radii) of each simulation-worm feature and 14 preset design variables (center point x and y coordinates and 12 control radii) of each closed B-spline feature as follows:

[0093] Findα=(P k ,r k ,(x0,y0),R k )

[0094]

[0095] wherein, g is the non-interference constraint function; J is the objective function, w is the weight coefficient, ψ is the fluid flow dissipation energy, C is the overall strain energy of the structure, the normalized values ψ0 and C0 in the objective function are determined by the simulation results under the initial layout, the upper limit of the volume fraction of the fluid may be set to 0.2, the lower limit of the volume fraction of the weight-reducing hole may be set to 0.3, and α i are the upper limit and the lower limit of the preset design variable respectively, and n is the number of design variables.

[0096] Step ten, the optimization design is performed by using a mathematical programming algorithm by calculating the sensitivity of the objective function and the constraint function with respect to the preset design variables.

[0097] The various embodiments in the specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the difference from other embodiments.

[0098] The above examples are only used to illustrate the technical solutions of the present application, and are not limited to the present application; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can still be modified, or some or all of the technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the present application.

Claims

1. A feature-driven structural and in-mold runner co-optimization design method, characterized in that, The method comprises the following steps: dividing a finite element grid for a design domain to obtain a finite element model; constructing a flow channel region and a lightening hole region in the design domain, and determining a first density field for controlling the flow channel region and a second density field for the lightening hole region; based on the first density field and the second density field, performing material property interpolation on the finite element model to obtain an elastic modulus and a flow resistance coefficient of each finite element grid; applying a preset condition to the finite element model to establish a structural mechanics analysis model and a fluid flow simulation model; wherein the preset condition comprises a solid constraint, a load, and a fluid inlet and outlet and wall boundary condition; based on the structural mechanics analysis model and the fluid flow simulation model, constructing a multi-objective optimization model according to a preset design variable and a variation range; wherein in the multi-objective optimization model, an optimization objective is a weighted sum of an overall strain energy and a fluid flow dissipation energy of the design domain, and a constraint function comprises a volume fraction of the flow channel region and a volume fraction of the lightening hole region, and an initial value and a variation range of the preset design variable; performing optimization design by calculating a sensitivity of the objective function and the constraint function with respect to the preset design variable.

2. The method of claim 1, wherein, The step of constructing a flow channel region and a lightening hole region in the design domain comprises the following steps: defining a geometric profile of the flow channel region by using a worm-like feature in the design domain, and defining a geometric profile of the lightening hole region by using a closed B-spline feature; calculating a first implicit level set function of each worm-like feature, and a second implicit level set function of each closed B-spline feature; performing maximum value operation on a plurality of the first implicit level set functions and a plurality of the second implicit level set functions to realize Boolean AND of a plurality of the worm-like features and a plurality of the closed B-spline features, and obtaining a first implicit level set maximum function and a second implicit level set maximum function.

3. The method of claim 2, wherein, The step of determining a first density field for controlling the flow channel region and a second density field for the lightening hole region comprises the following steps: mapping the first implicit level set maximum function and the second implicit level set maximum function by using a smooth form of a Heaviside function, respectively, to obtain the first density field and the second density field.

4. The method of claim 2, wherein, The step of performing material property interpolation on the finite element model comprises the following step: where a is the flow resistance coefficient, E is the elastic modulus, a max is the flow resistance coefficient of the solid region in the design domain, q is a positive number that controls the curvature of the interpolation model, E s is the solid elastic modulus, E f is the fluid elastic modulus, g fluid is the first density field, g void is the second density field.

5. The method of claim 2, wherein, The preset design variable comprises a control point and a control radius of each worm-like feature, and a center point and a control radius of the closed B-spline feature.

6. The method of claim 1, wherein, Before the step of applying a preset condition to the finite element model to establish a structural mechanics analysis model and a fluid flow simulation model, the method further comprises the following step: based on the first density field and the second density field, and a non-interference constraint function for defining the flow channel region and the lightening hole region; wherein the constraint function in the multi-objective optimization model further comprises the non-interference constraint function.

7. The method of claim 1, wherein, The step of performing optimization design comprises the following step: performing optimization design by using a mathematical programming algorithm.

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