CN107391891A - A kind of high aspect ratio wing Optimization Design based on Model Fusion method - Google Patents

Abstract

The invention discloses a large-aspect-ratio wing optimization design method based on a model fusion method, and belongs to the field of overall optimization design of aircraft. The present invention divides optimization into structural discipline optimization model and system-level optimization model according to requirements, uses penalty function method to deal with complex constraints; uses aerodynamic structure coupling modeling technology to establish high-precision and low-precision aerodynamic structure coupling analysis models; uses test design method to separate Generate high-precision and low-precision sample points; respectively call high-precision and low-precision structural coupling analysis models to obtain high-precision and low-precision sample information and store them; use model fusion method to fuse high-precision and low-precision model information to establish a proxy model; based on the current proxy model Use the optimization method to optimize the solution, and judge whether the optimization result is credible according to the difference between the real response value at the optimal solution and the proxy model value based on the model fusion method. Output the optimal design results and complete the optimal design.

Description

An Optimal Design Method for Large Aspect Ratio Wing Based on Model Fusion Method

technical field

The invention relates to a large-aspect-ratio wing optimization design method based on a model fusion method, and belongs to the technical field of aircraft overall optimization design.

Background technique

High-aspect-ratio wings have the characteristics of large lift-to-drag ratio and large wing volume, and are widely used in high-altitude drones, solar-powered aircraft, and large intercontinental airliners. During the flight of this type of aircraft, the wing with a large aspect ratio is affected by the aerodynamic load, and the structural deformation occurs, and the deformation amplitude has a significant impact on the aerodynamic performance. Therefore, the aerodynamic structure coupling problem needs to be considered in the analysis and design of a large aspect ratio wing. For the coupling problem of aerodynamic structure, fluid mechanics and structural mechanics can be solved independently as a single discipline, and interdisciplinary data interaction can be realized through software scheduling technology, and coupling analysis can be realized through iterative solution. In order to improve the accuracy of coupling analysis, high-precision analysis methods such as computational fluid dynamics (CFD) and finite element analysis (FEA) are often used to analyze and solve the two single subjects respectively. However, the high-precision analysis model also brings the problem of time-consuming calculation while improving the analysis accuracy and reliability. Although today's computer hardware and software technology has made great progress, it is still difficult to call a high-precision analysis model to complete an iterative solution. Extremely time consuming. For example, it takes several hours or even dozens of hours to complete an aerodynamic simulation analysis using a CFD model. The optimal design of wings with large aspect ratios is also an iterative process. In the optimization process, it is often necessary to call the high-precision coupling analysis model thousands of times, which further increases the design cost and makes the optimization design efficiency very low.

In order to better illustrate the technical solution of the present invention, the applied aerodynamic structure coupling modeling technology will be specifically introduced below.

Aerodynamic structural coupling modeling technology:

As the aspect ratio of the wing increases, the flexibility of the wing increases continuously, and the coupling phenomenon between its aerodynamic performance and structural performance becomes more obvious. The key to aerodynamic-structure coupled modeling technology is the information transfer between aerodynamic and structural disciplines. In the existing mature aerodynamic structure coupling modeling technology, the three-dimensional interpolation method is often used to realize the transfer of aerodynamic analysis results to the structural discipline, and at the same time, the geometric shape of the updated wing is determined according to the coordinates of the control points on the front and rear edges of the deformed wing , re-analyze the aerodynamic subject, and complete the transfer of the analysis results of the structural subject to the aerodynamic subject. On the other hand, in the coupling modeling of aerodynamic structures, the density of the aerodynamic discipline grid often controls the calculation cost and model accuracy of the entire coupling analysis model. Increasing the grid density can improve the accuracy of the analysis model, but it will also increase the calculation cost. On the contrary, reducing the grid density will reduce the calculation accuracy and reduce the calculation cost.

The flow chart of the aerodynamic structural coupling analysis model is shown in Figure 1, and the specific method steps are as follows:

Step 1. Use the model parameterization technology based on UG secondary development to establish/update the wing parametric model. The parameterized parameters of the geometric model include the geometric design variables aspect ratio, root-to-shoot ratio, sweep angle, airfoil parameters, and the coordinate information of the front and rear edge position control points used to quantitatively represent the structural deformation. After the parameterization is completed, the geometric shape file is output for subsequent analysis, generally in step format or igs format.

Step 2. Build an aerodynamic analysis model using CFD. The input geometric shape file and aerodynamic analysis working condition information include Mach number and angle of attack, and the output aerodynamic analysis results include lift force, drag information and aerodynamic force distribution file. Gambit can be used for grid drawing, and Fluent can be used for aerodynamic analysis and solution.

Step 3. Use the FEA method to establish a structural subject analysis model, use Patran for pre-processing, and Nastran for post-processing. Input geometric shape files, use PCL language to carry out relevant analysis and optimization settings such as material properties, unit property definitions, and aerodynamic loading. The built-in SQP optimizer in Nastran can realize structural subject optimization. The final output structure analysis structure includes the maximum stress and maximum displacement and the coordinate information of the control points of the leading and trailing edges of the wing.

Step 4. If it is the first analysis, input the coordinate information of the deformed control points into the model parameterization module, repeat steps 2, 3, and 4, and if it is not the first analysis, calculate the relative displacement. The calculation of the relative displacement η is as follows Formula (1) shown. When the relative displacement is less than 0.01, the iteration ends, and the aerodynamic analysis results at this time are output, including the lift-to-drag ratio, mass, maximum stress, maximum displacement, and optimization results of structural discipline variables; when the relative displacement is greater than 0.01, repeat steps 1, 2, 3, 4, until the relative displacement is less than 0.01, the iteration ends.

In formula (1), i represents the i-th analysis, and i-1 represents the previous analysis of the i-th analysis.

Contents of the invention

Aiming at the problem of high computational cost when considering aerodynamic structure coupling in the process of optimizing the design of wings with large aspect ratios, the invention discloses a method for optimizing the design of wings with large aspect ratios based on the model fusion method. The technical problem to be solved In the case of ensuring the accuracy, considering the aerodynamic structure coupling problem to realize the efficient optimal design of the wing with a large aspect ratio, it has the following advantages: use the model fusion method to effectively fuse the high and low precision analysis model information, make full use of the low precision model The information guarantees the accuracy of the fusion model and reduces the number of calls of the high-precision analysis model, thereby reducing the calculation cost and improving the optimization design efficiency of the wing with a large aspect ratio.

The purpose of the present invention is achieved through the following technical solutions.

The invention discloses a large-aspect-ratio wing optimization design method based on the model fusion method. According to the design requirements, the initial reference airfoil and wing-related shape parameters are selected to determine the design conditions; System-level optimization model, and use penalty function method to deal with complex constraints; use aerodynamic structure coupling modeling technology to establish high-precision and low-precision large-aspect-ratio wing aerodynamic structure coupling analysis models; use experimental design methods to generate high and low-precision sample points respectively ;Invoke the high-precision and low-precision large-aspect-ratio wing aerodynamic structural coupling analysis models to obtain high-precision and low-precision sample information and store them; use the model fusion method to fuse high-precision and low-precision model information, and establish a proxy model to achieve model accuracy Comprehensive coordination with calculation cost; based on the current proxy model, use the optimization method to optimize the solution, and judge whether the optimization result is credible according to the difference between the real response value at the optimal solution and the value of the proxy model based on the model fusion method. Go back to reconstruct the fusion model for optimization and solution, and output the optimal design result if it is credible, that is, complete the efficient optimal design of wings with large aspect ratio considering the aerodynamic structure coupling problem.

A large-aspect-ratio wing optimization design method based on a model fusion method disclosed by the present invention comprises the following steps:

Step 1: According to the design requirements, select the initial reference airfoil and wing-related shape parameters to determine the design conditions.

The design conditions described include Mach number and angle of attack.

Step 2: Establish the optimization model of the structural subject and the system-level optimization model according to the requirements.

Step 2.1: Establish an optimization model of structural disciplines according to requirements.

In order to be able to minimize mass while maintaining structural strength, the size of each structural component of the wing was optimized during the structural analysis. The design variables include skin thickness, web thickness, flange radius, web thickness, and flange radius; the optimization objective is to minimize the structural mass; the constraint conditions are to satisfy the maximum stress constraint and the maximum displacement deformation constraint. The optimization of structural subjects is realized in the analytical model of structural subjects.

Step 2.2: Establish a system-level optimization model based on requirements.

In the system-level optimization, the geometric design parameters are selected as design variables. The design variables include aspect ratio, root-to-tip ratio, and sweep angle, and their upper and lower limits are determined according to requirements; the optimization goal is to maximize the lift-to-drag ratio and minimize the structural mass. Constraints include that the maximum structural stress is less than the allowable stress, the maximum structural displacement is less than the allowable displacement, and the wing area is constant.

Step 3: Use aerodynamic structure coupling modeling technology to establish high-precision and low-precision large-aspect-ratio wing aerodynamic structure coupling analysis models. The grid density of aerodynamics is the main factor of calculation cost and calculation accuracy. Therefore, in the aerodynamic analysis model, the coarse grid is used to establish the low-precision analysis model, and the fine grid is used to establish the high-precision analysis model.

In step 3, the coordination of calculation accuracy and calculation cost is achieved through the density of the grid density of the aerodynamic discipline, and a high-precision and low-precision aerodynamic structure coupling analysis model is established.

Step 4: Use the experimental design method to generate N ^h high-precision sample points and N ^l low-precision sample points respectively. The number of sample points is related to the system-level optimization design variable dimension n _v . The low-precision sample points need to include all high-precision sample points.

In order to achieve high efficiency in the optimal design of large aspect ratio wings considering the aerodynamic structure coupling problem, the experimental design method described in step 4 preferably uses the Latin hypercube experimental design method.

The number of sample points is determined according to theoretical analysis, experiment or empirical value, preferably N ^h =(n _v +3)*(n _v +2), 4N ^h ≤ N ^l ≤ 6N ^h .

Step 5: Invoke the high- and low-precision high-aspect-ratio wing aerodynamic structure coupling analysis model in step 3, obtain the model response values at the N ^h and N ^l sample points in step 4, and store the high and low-precision sample point information.

Step 6: Use the model fusion method to fuse the information of high and low precision sample points to establish a proxy model. The proxy model is a fusion model y ^s (x) composed of a proxy model of the correction model and a proxy model of the error model.

The specific implementation method of step 6 is as follows:

Step 6.1: According to the high-precision samples and the corresponding low-precision sample information, use the least squares method to obtain the correction factor of the low-precision large-aspect-ratio wing aerodynamic structure coupling analysis sample points, as shown in formula (2):

Among them: N ^h is the number of high-precision large-aspect ratio wing aerodynamic structure coupling analysis sample points; y ^h ( _xi ) is the response value of the high-precision aerodynamic structure coupling analysis model, y ^l ( _xi ) is the low-precision aerodynamic The response value of the structural coupling analysis model, the response value includes the lift-to-drag ratio, structural mass, maximum structural stress, and maximum structural displacement; ρ ₀ and ρ ₁ are correction factors for the sample points of the low-precision aerodynamic structural coupling analysis model, each Each response value has its own corresponding correction factor.

Step 6.2: Use the correction factor of the low-precision aerodynamic-structure coupling analysis model sample points in step 6.1 to correct all low-precision aerodynamic-structure coupling analysis model sample points, and use the Kriging method based on the corrected low-precision aerodynamic-structure coupling analysis model sample information To construct a proxy model, the modified model y ^l _s (x) of the low-precision aerodynamic-structure coupling analysis model is expressed as:

y ^l _s (x) = ρ ₀ + ρ ₁ y ^l (x) (3)

where y ^l (x) is the response value of the sample point of the low-precision aerodynamic-structure coupling analysis model, and the correction model of the low-precision aerodynamic-structure coupling analysis model is obtained by correcting the sample point data of all low-precision aerodynamic-structure coupling analysis models using formula (3) y ^l _s (x). The Kriging method is used to complete the construction of the surrogate model y _s ^s (x) of the low-precision aerodynamic-structure coupling analysis model correction model y ^l _s (x).

Step 6.3: Calculate the error value δ( _{xi) between the sample points of the high-precision aerodynamic-structure coupling analysis model in step 5 and the corrected model of the low-precision aerodynamic-structure coupling analysis model in step 6.2, and the error value δ(xi )} is calculated by the formula ( 4) Calculated to obtain:

δ( _xi )=y ^h ( _xi )-y ^l _s ( _xi )=y ^h ( _xi )-[ρ ₀ +ρ ₁ y ^l ( _xi )])i=1,2,3... N ^h ) (4)

Based on the error information δ( _xi ), the Kriging method is used to complete the construction of the surrogate model δ ^s (x) of the error model.

Step 6.4: Construct a fusion model y ^s (x) consisting of the surrogate model y _s ^s (x) of the correction model in step 6.2 and the surrogate model δ ^s (x) of the error model in step 6.3, as shown in formula (5) Shown:

y ^s (x) = y _s ^s (x) + δ ^s (x) (5)

The fusion model y ^s (x) is a proxy model of a high-precision aerodynamic-structure coupling analysis model.

Step 7: Based on the fusion model y ^s (x) established in step 6, use the penalty function to deal with the complex constraints in the problem, use the optimization algorithm to solve the system optimization problem, and obtain the optimal solution based on the current fusion model y ^s (x) untie

The penalty function is as shown in formula (6):

F(x)=f(x)+MP(x)M>0

Among them: F(x) is the optimized goal after processing, f(x) is the original optimization goal, M is the penalty factor, P(x) is the constraint violation degree, g _i (x) is the inequality constraint, h _i (x) is the equality constraint, m is the number of inequality constraints, and l is the total number of constraints.

In step 7, the optimization algorithm is used to solve the system optimization problem, and the genetic algorithm is preferably solved.

Step 8: call the high-precision large aspect ratio wing aerodynamic structure coupling analysis model in step 3 to obtain the optimal solution of the proxy model in step 7 The real response value at . Calculate the difference between the real response value of the optimal solution and the proxy model value, and judge whether the optimization result is credible according to the difference. If it is not credible, return to step 4, increase the number of sample points in the coupling analysis model of low-precision large-aspect-ratio wing aerodynamic structure, repeat steps 5, 6, 7, and 8 until a credible optimization result is obtained, and if credible, output the most The optimal design results, that is, the efficient optimal design of the large aspect ratio wing considering the aerodynamic structure coupling problem is completed.

Beneficial effect:

1. Aiming at the problem that the aerodynamic structure coupling problem needs to be considered in the design of a large aspect ratio wing, which leads to the problem that the calculation cost of the optimization design process is unbearable, the present invention discloses a large aspect ratio wing optimization design method based on the model fusion method, through Mesh density control realizes the comprehensive coordination of analysis model accuracy and calculation cost.

2. A large-aspect-ratio wing optimization design method based on the model fusion method disclosed in the present invention uses the model fusion method to efficiently fuse high-precision and low-precision model information, and reduces high-precision analysis models while meeting the design precision requirements. The amount of calls can reduce the calculation cost and improve the design efficiency of large aspect ratio wings.

3. A large-aspect-ratio wing optimization design method based on the model fusion method disclosed in the present invention uses a penalty function to deal with complex constraint problems, and realizes simplicity and convenience in the optimization design process.

4. A large-aspect-ratio wing optimization design method based on the model fusion method disclosed in the present invention uses the difference between the real response value of the optimal solution and the proxy model value to determine the reliability of the optimal result and complete the optimization process updates and iterations.

5. A large-aspect-ratio wing optimization design method based on the model fusion method disclosed by the present invention uses the Kriging proxy model method to efficiently complete the construction of the proxy model of the correction model and the proxy model of the error model, and then make the height, Low-precision model information is fused more efficiently.

6. A large-aspect-ratio wing optimization design method based on the model fusion method disclosed in the present invention uses a genetic algorithm for optimization and solution, which can avoid the situation of no solution in the optimization solution and improve the solution feasibility of engineering optimization design problems .

Description of drawings

Figure 1 is a flow chart of the coupling analysis of the aerodynamic structure of the large aspect ratio wing;

Fig. 2 is a flow chart of the optimal design method for large aspect ratio wings considering aerodynamic structure coupling;

Figure 3 is a comparison of high and low precision grids in the discipline of aerodynamics.

Among them, Figure 3a is a high-precision analysis model grid, and Figure 3b is a low-precision analysis model grid;

Fig. 4 is a flow chart of the model fusion method;

detailed description

In order to better illustrate the technical solutions and advantages of the present invention, the present invention will be further described through specific examples of optimized design of wings with large aspect ratios, combined with drawings and tables. The specific implementation methods are as follows.

A large aspect ratio wing optimization design method based on the model fusion method disclosed in this embodiment, the flow chart is shown in Figure 2, and the specific implementation steps are as follows:

Step 1: Select the laminar flow airfoil NACA64A816 as the reference initial airfoil, the design condition is the flight Mach number Ma=0.64, and the angle of attack α=2°. The shape of the wing is determined by the initial value of the system variables, as shown in Table 2.

Step 2: Establish the optimization model of the structural subject and the system-level optimization model according to the requirements.

Step 2.1: Establish an optimization model of structural disciplines according to requirements.

Dimensional optimization of each structural component of the wing is performed in an optimization model of the structural discipline. Select the skin thickness of each wing box (T _skin ), the web thickness of each rib (T _rib ), the flange radius of each rib (R _rib ), the web thickness of each spar (T _spar ), and the upper and lower flange radii (R _spar ) of each spar, are used as structural subject optimization design variables. Constraint conditions include that the maximum structural stress σ _max is less than the allowable stress of 100MPa, and the maximum structural displacement δ _max is less than the allowable displacement of 900mm. The structural optimization goal is to minimize the structural mass W of the wing. The optimization of structural subjects is realized in the analytical model of structural subjects. The structural optimization model is shown in the following formula (7).

Among them, x _struc is the optimization design variable of structural subject, x _struc ^lb and x _struc ^ub are the upper limit and lower limit of structural design variables respectively, and the values of design variables are shown in Table 1.

Table 1 Structural design variables and range of change

Step 2.2: Establish a system-level optimization model based on requirements.

The geometric design parameters selected in system-level optimization are design variables. The geometric design parameters include aspect ratio, root-to-shoot ratio, and sweep angle, and their upper and lower limits are determined according to requirements, as shown in Table 2; the lift-to-drag ratio D The maximum /L and the minimum structural mass W are the optimization objectives. The constraints include that the maximum structural stress σ _max is less than the allowable stress of 100MPa, the maximum structural displacement δ _max is less than the allowable displacement of 900mm, and the wing area is constant at 50.17m ² . The system-level optimization model is shown in formula (8).

min F(X)＝1/2×C _weight +1/2×C _D/L

stσ _max ≤100Mpa (8)

δ _max ≤900mm

X ^lb ≤ X ≤ X ^ub

S=50.17m ²

F(X) is the comprehensive optimization objective, which is linearly weighted by the structural quality W of the two optimization objectives and the lift-to-drag ratio D/L. Since the order of magnitude of each target is different, the structural quality W ^baseline of the initial wing and the lift-to-drag ratio (D/L) ^baseline of the initial wing are used to normalize the optimized target structure mass and lift-to-drag ratio respectively, to obtain The normalized objective function response values C _weight and C _D/L . X is the design variable, X ^lb and X ^ub are the upper and lower limits of the design variable respectively, and the specific values are shown in Table 2.

Table 2 System-level design variables and range of variation

Step 3: Use the aerodynamic structure coupling modeling technology to establish the high aspect ratio wing aerodynamic structure coupling analysis model and the low precision large aspect ratio wing aerodynamic structure coupling analysis model. In this step, the distinction between high-precision and low-precision analysis models is achieved by adjusting the grid drawing density. In this embodiment, the grid density of high precision is twice that of low precision, as shown in FIG. 3 . In the structural subject analysis model, the finite element model unit attribute definition of the structural subject is shown in Table 3, and the SQP optimizer that comes with Nastran is used to complete the optimization of the structural subject, and the optimization model is described in the optimization model of the structural subject in step 2.1 .

Table 3 finite element model element properties

Step 4: Use the Latin hypercube experimental design method to generate high-precision model sample points and low-precision model sample points. In the present invention, calculation cost is calculated by CPU calculation time. According to experimental statistics, each high-precision analysis model takes about 20 minutes, and the calculation cost of each low-precision analysis model is about 3 minutes. Generate 30 high-precision sample points and 130 low-precision sample points for the model fusion method. For efficiency comparison, 50 high-precision sample points (calculation cost is about the sum of 30 high-precision analysis and 130 low-precision analysis) are generated at the same time to construct a proxy model using traditional methods.

In this implementation case, the aforementioned proxy model constructed using the traditional method is a proxy model that directly constructs a high-precision large-aspect-ratio wing aerodynamic structural coupling analysis model using the Kriging method alone.

Step 5: Invoke the high- and low-precision high-aspect-ratio wing aerodynamic structural coupling analysis model in step 3, obtain the model response values at 30 high-precision sample points and 130 low-precision sample points in step 4, and store the high and low Accurate large aspect ratio wing aerodynamic structure coupling analysis model sample point information. In order to compare the efficiency, it is necessary to obtain the model response values at 50 high-precision sample points used to construct the proxy model based on the traditional method at the same time.

Step 6: Use the model fusion method to fuse the information of 30 high-precision sample points in step 5 with the information of 130 low-precision sample points, and establish a proxy for the high-precision large-span wing aerodynamic structural coupling analysis model based on the model fusion method Model. Its specific flow chart is shown in Figure 4. At the same time, 50 high-precision sample point information is used to directly construct a proxy model of a high-precision large-span wing aerodynamic structural coupling analysis model based on traditional methods.

Step 7: Based on the proxy model established by the model fusion method established in step 6 and the proxy model constructed by the traditional method, the genetic algorithm is used for optimization. For the complex constraints in this optimization problem, a penalty function is used to deal with it, and the penalty factor is set to 1000. The optimal solution based on the model fusion method and the optimal solution based on the traditional method are respectively obtained.

Step 8: call the high-precision large aspect ratio wing aerodynamic structure coupling analysis model in step 3 to obtain the optimal solution of the proxy model in step 7 The real response value at . Calculate the difference between the real response value of the optimal solution and the proxy model value, and judge whether the optimization result is credible according to the difference. If it is not credible, return to step 4, increase the number of sample points in the coupling analysis model of low-precision large-aspect-ratio wing aerodynamic structure, repeat steps 5, 6, 7, and 8 until a credible optimization result is obtained, and if credible, output the most The optimal design results, that is, the efficient optimal design of the large aspect ratio wing considering the aerodynamic structure coupling problem is completed.

The statistical system optimization results are shown in Table 4, and the structural subject optimization results are shown in Table 5.

Table 4 3D wing system optimization results

Observing Table 4, comparing the optimal design results using the two methods, it can be found that the lift-to-drag ratio has a small improvement, but the structural quality has changed significantly. Using the optimal design method in the present invention, the quality is reduced by 54%, while the optimization result of the traditional method only reduces the quality by 4%. After using the method of the present invention, the normalized comprehensive optimization target value is 0.7258, which is far smaller than the optimization result of the traditional method under the same calculation cost. At the same time, when using the optimal design method of the present invention, the difference between the real target value and the proxy model value is small, indicating that the optimal design method of the present invention has higher precision. Through the comparison of experimental results, it can be concluded that compared with the traditional method, the method of the present invention not only has higher model accuracy but also has better optimal design results under the same calculation cost. Therefore, adopting a large-aspect-ratio wing optimization design method based on the model fusion method proposed by the present invention to carry out the large-aspect-ratio wing optimization design can reduce the call volume of high-precision analysis models while ensuring accuracy, thereby reducing calculation Cost, improve the optimization design efficiency of large aspect ratio wings.

Table 5 3D wing structure optimization results

According to the analysis of the above-mentioned specific large-aspect-ratio wing optimization examples, the present invention can realize the expected purpose of the invention. Compared with the traditional large-aspect-ratio wing optimization design method, the present invention helps to improve the Wing optimization design results and design quality; on the other hand, it involves the optimization of high-precision analysis models for wings with large aspect ratios. The present invention can also greatly improve optimization efficiency, reduce optimization design costs, and shorten optimization design cycles.

The specific description above further elaborates the purpose, technical solutions and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention, which is used to explain the present invention and is not used to To limit the protection scope of the present invention, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims (7)

1. A kind of 1. high aspect ratio wing Optimization Design based on Model Fusion method, it is characterised in that：Comprise the following steps,

   Step 1：According to design requirement, initial reference aerofoil profile and wing associated shape parameter are selected, determines design conditions；

   Step 2：The Optimized model of structure subject and system-level Optimized model are established according to demand；

   Step 3：High and low precision high aspect ratio wing pneumatic structure coupling analysis mould is established using pneumatic structure Coupling method technology Type；Pneumatic subject mesh-density is the principal element for calculating cost and computational accuracy, therefore using thick in aerodynamic analysis model Grid establishes low precision analysis model, and high-precision analysis model is established using refined net；

   Step 4：N is generated respectively using test design method^hHigh-precision sample point and N^lIndividual low precision sample point；Sample point quantity With system-level optimization design variable dimension n_vIt is related；Need to include all high-precision sample points in wherein low precision sample point；

   Step 5：High and low precision high aspect ratio wing pneumatic structure model of coupling in invocation step 3, obtain the N in step 4^h And N^lModel response at sample point, store high and low precision sample point information；

   Step 6:High and low precision sample point information is merged using Model Fusion method, establishes agent model；Described generation Reason model is the Fusion Model y being made up of the agent model of correction model and the agent model of error model^s(x)；

   Step 7：Based on the Fusion Model y established in step 6^s(x), using the Complex Constraints in penalty function process problem, use Optimized algorithm carries out system optimization problem solving, obtains being based on present fusion model y^s(x) optimal solution

   Shown in described penalty function such as formula (6)：

   <mrow> <mtable> <mtr> <mtd> <mtable> <mtr> <mtd> <mrow> <mi>F</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>M</mi> <mi>P</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <mi>M</mi> <mo>&gt;</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mrow> <mo>(</mo> <mi>max</mi> <mo>(</mo> <mrow> <mn>0</mn> <mo>,</mo> <msub> <mi>g</mi> <mi>i</mi> </msub> <msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> <mo>)</mo> <mo>)</mo> </mrow> <mo>+</mo> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mi>m</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msub> <mi>h</mi> <mi>i</mi> </msub> <msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>

   Wherein：F (x) is the optimization aim after processing, and f (x) is original optimization aim, and M is penalty factor, and P (x) runs counter to for constraint Degree, g_i(x) it is inequality constraints, h_i(x) it is equality constraint, m is inequality constraints number, and l is constraint total number；

   Step 8：High-precision high aspect ratio wing pneumatic structure model of coupling in invocation step 3, obtain in step 7 The optimal solution of agent modelThe true response at place；Calculate the true response of optimal solution and the difference of agent model value, root Judge whether the optimum results are credible according to size of the difference；Return to step 4 if insincere, increase low precision high aspect ratio wing gas Dynamic structure coupling analysis model sample point quantity, repeat step 5,6,7,8, until believable optimum results are obtained, if credible Optimal design result is exported, that is, completes to consider the effectively optimizing design of the high aspect ratio wing of pneumatic structure coupled problem.
2. 2. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 1, its feature It is：Step 2 concrete methods of realizing is,

   Step 2.1：The Optimized model of structure subject is established according to demand；

   In order to while structural strength is ensured, quality be reduced to greatest extent, to wing during structural analysis Each construction package carries out dimensionally-optimised；Design variable includes skin thickness, web thickness, flange radius, web thickness, flange Radius；Optimization aim is that architecture quality is minimum；Constraints constrains to meet that maximum stress constraint deforms with maximum displacement；Structure The optimization of subject is realized in structure subject analysis model；

   Step 2.2：System-level Optimized model is established according to demand；

   It is design variable that geometry design parameter is selected in system-level optimization, and described design variable includes aspect ratio, contraction coefficient, sweepback Angle, and its bound is determined according to demand；Maximum, the minimum optimization aim of architecture quality with lift-drag ratio, constraints include knot Structure maximum stress is less than allowable stress, structure maximum displacement is less than displacement allowable and wing area is constant.
3. 3. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 1 or 2, it is special Sign is：Computational accuracy is realized by the density degree of pneumatic subject mesh-density in step 3 and calculates the coordination of cost, is established The pneumatic structure model of coupling of high and low precision.
4. 4. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 3, its feature It is：The concrete methods of realizing of step 6 is as follows：

   Step 6.1：According to high-precision sample and corresponding low precision sample information, it is big to obtain low precision using least square method Shown in the modifying factor such as formula (2) of aspect ratio wing aerodynamic structure coupling analysis sample point：

   <mrow> <mi>min</mi> <mi> </mi> <mi>L</mi> <mrow> <mo>(</mo> <msub> <mi>&amp;rho;</mi> <mn>0</mn> </msub> <mo>,</mo> <msub> <mi>&amp;rho;</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <msup> <mi>N</mi> <mi>h</mi> </msup> </munderover> <msup> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>&amp;rho;</mi> <mn>0</mn> </msub> <mo>+</mo> <msub> <mi>&amp;rho;</mi> <mn>1</mn> </msub> <msup> <mi>y</mi> <mi>l</mi> </msup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msup> <mi>y</mi> <mi>h</mi> </msup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> <mo>...</mo> <msup> <mi>N</mi> <mi>h</mi> </msup> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>

   Wherein：N^hFor high-precision high aspect ratio wing pneumatic structure coupling analysis sample point number；y^h(x_i) it is high-precision pneumatic knot The response of structure model of coupling, y^l(x_i) be low precision pneumatic structure model of coupling response, described response Including lift-drag ratio, architecture quality, structure maximum stress, structure maximum displacement；ρ₀、ρ₁For low precision pneumatic structure coupling analysis mould The modifying factor of type sample point, each response have modifying factor corresponding to oneself；

   Step 6.2：Using the modifying factor of the low precision pneumatic structure model of coupling sample point in step 6.1 to all low Precision pneumatic structure model of coupling sample point is modified, based on revised low precision pneumatic structure model of coupling Sample information uses Kriging method construct agent models, the correction model y of low precision pneumatic structure model of coupling^l _s(x) It is expressed as：

   y^l _s(x)=ρ₀+ρ₁y^l(x) (3)

   Wherein y^l(x) it is the response of low precision pneumatic structure model of coupling sample point, using formula (3) to all low precision Pneumatic structure model of coupling sample points evidence is modified the amendment mould for obtaining low precision pneumatic structure model of coupling Type y^l _s(x)；Low precision pneumatic structure model of coupling correction model y is completed using Kriging methods^l _s(x) agent model y_s ^s(x) construct；

   Step 6.3：High-precision pneumatic structure coupling analysis model sample point and low precision in step 6.2 are pneumatic in calculation procedure 5 Error amount δ (x between the correction model of structure coupling analysis model_i), error amount δ (x_i) obtained by formula (4) calculating：

   δ(x_i)=y^h(x_i)-y^l _s(x_i)=y^h(x_i)-[ρ₀+ρ₁y^l(x_i)] (i=1,2,3 ... N^h) (4)

   Based on control information δ (x_i), using Kriging methods, complete the agent model δ of error model^s(x) construction；

   Step 6.4：Build the agent model y by the correction model in step 6.2_s ^s(x) generation of the error model and in step 6.3 Manage model δ^s(x) the Fusion Model y of composition^s(x), as shown in formula (5)：

   y^s(x)=y_s ^s(x)+δ^s(x) (5)

   Described Fusion Model y^s(x) it is the agent model of high-precision pneumatic structure coupling analysis model.
5. 5. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 4, its feature It is：To realize the high efficiency for the high aspect ratio wing optimization design for considering pneumatic structure coupled problem, the examination described in step 4 Test design method and use Latin hypercube experimental design method.
6. 6. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 5, its feature It is：Sample point quantity takes N depending on theory analysis, experiment or empirical value in step 4^h=(n_v+3)*(n_v+ 2), 4N^h≤N^l ≤6N^h。
7. 7. a kind of high aspect ratio wing Optimization Design based on Model Fusion method as claimed in claim 6, its feature It is：Carrying out system optimization problem solving using optimized algorithm in step 7 selects genetic algorithm to solve.