Method for hybrid optimization design of quantity, size and angle of radial structure of aircraft considering aeroelasticity

Abstract

The present invention proposes a method for hybrid optimization design of the number, size, and angle of the radial structure of an aircraft considering aeroelasticity. Based on the actual working environment of the aircraft, constraints such as aerodynamic heat, allowable stress of materials, and structural weight are comprehensively considered. At the same time, hybrid optimization of the number, size, and angle of the structure is achieved, and the correlation factors between various optimization objectives are considered, which is in line with engineering practice. In addition, for the traditional optimization process based on the basic structure method, the layout of the determined basic structure will not be adjusted, which requires a high level of initial basic structure layout design. In the optimization process of the present invention, the angle variable of the basic structure is introduced as an optimization variable, which reduces the difficulty of the initial layout of the basic structure.

Description

Technical Field

[0001] The present invention relates to the field of hypersonic vehicle structural design, and particularly to an optimization method for hypersonic vehicle structural design considering aeroelasticity, mainly a method for hybrid optimization design of the number, size, and angle of the radial structures of a hypersonic vehicle under the multi-disciplines of wing structure / aeroelasticity / aerodynamic heat. Background Art

[0002] With the development of hypersonic engineering, the vehicle needs to fly at high speed in the atmosphere for a long time, and the aerodynamic load environment faced is very severe. On the other hand, the load-bearing structure of the vehicle develops towards lightweight, and the stiffness of the structure gradually decreases. The aeroelasticity problem under complex aerodynamic loads has gradually become an important constraint in the structural design of the vehicle. Therefore, the research on the optimization design problem of the vehicle structure considering the aeroelasticity problem is of great significance for the development of hypersonic vehicles.

[0003] Structural optimization design involves computational mechanics, mathematical programming, computer science, and other engineering disciplines, and is an important research direction in the field of modern structural design. The structural design of a hypersonic vehicle needs to meet both the strength and stiffness design requirements and the mass and volume constraints, with the characteristics of multiple optimization objectives and complex optimization constraints. The traditional vehicle structural optimization design usually adopts a hierarchical optimization strategy to sequentially realize the layout optimization and size optimization of the structure. Although the hierarchical optimization strategy has the advantages of clear logic and simple method, it ignores the correlation between the quantity variable, size variable, and angle variable, reduces the design space of structural optimization, and weakens the optimization effect.

[0004] In addition, for traditional layout optimization, the basic structure method is mostly adopted. This method needs to arrange the basic structure in advance and perform deletion operations on it to obtain a reasonable layout form from it. However, for radial structures, the range of angle change is relatively large. Only relying on the pre-arranged basic structure, a very large number needs to be arranged, which will lead to a large number of variables in the optimization process and a long optimization time. Summary of the Invention

[0005] Aiming at the deficiencies of hierarchical optimization in the traditional structural design process and minimizing the number of variables in the optimization process of the basic structure method as much as possible, the present invention proposes a hybrid optimization method that simultaneously realizes the optimization of the structure quantity, size, and angle, considers the aeroelasticity problem, and carries out the layout and size optimization design of the radial structure of the hypersonic vehicle, providing a reference for the quality assessment in the overall design stage of the vehicle and the preliminary design of the vehicle structure.

[0006] The technical solution of the present invention is as follows:

[0007] A hybrid optimization design method for the number, size, and angle of the radial structure of a vehicle considering aeroelasticity, comprising the following steps:

[0008] Step 1: Determine the original configuration of the radial structure in the aircraft component, and given the original basic structure, establish a three-dimensional finite element model of the aircraft component;

[0009] Step 2: According to the original configuration determined in Step 1, establish an optimization model:

[0010] Take the number, size, and angle of the radial structures in the aircraft component as design variables;

[0011] Take the lowest aeroelastic influence on the aircraft component as the objective function;

[0012] Take the stress, displacement, mass, and temperature of the radial structures as constraint conditions;

[0013] Step 3: Use an optimization algorithm to solve the optimization model, and perform a mixed optimization of the number, size, and angle of the radial structures to obtain the optimal structural result;

[0014] Step 4: Judge whether the optimization result meets the design requirements. If it meets, output the final result. If not, modify the constraint information and return to Step 2 to re-establish the optimization model.

[0015] Further, the aircraft component is a wing, and the radial structure is the internal beam structure of the wing.

[0016] Further, the original configuration of the radial structure is to arrange several wing beam structures from the middle of the wing root to the leading edge, wing tip, and trailing edge of the wing.

[0017] Further, the design variables are the number of wing beam structures, the width of each wing beam structure, and the angle between each wing beam structure and the wing root.

[0018] Further, the constraint conditions are that the stress of the wing beam structure is less than the allowable stress of the beam structure used, the maximum displacement of the wing structure does not exceed the set value, the change in wing mass does not exceed the set value, and the maximum temperature and average temperature of the wing under flight conditions do not exceed the set value.

[0019] Further, use a genetic algorithm to solve the optimization model.

[0020] Further, in the genetic algorithm, the chromosome is divided into three parts: topological variables, size variables, and angle variables; among them, the topological variable is a variable with a value of 0 or 1: taking 1 means the existence of the wing beam structure, and taking 0 means the non-existence of the wing beam structure; the size variable and the angle variable are continuous variables within a given range.

[0021] Further, the optimization model is:

[0022] find XT , X S , X D

[0023] min ΔC yα (X T , X S , X D )

[0024] s.t. g i ≤ 1, i = 1, 2, 4, 5

[0025] 0.95 ≤ g3 ≤ 1.05

[0026] X Tj ∈ {0, 1}, j = 1, …, N

[0027] X Sj ∈ [0.5, 20], j = 1, …, N

[0028] X Dj ∈ [0°, 180°], j = 1, …, N

[0029] g1 = g1(X T , X S , X D ) = σ imax / 35

[0030] g2 = g2(X T , X S , X D ) = ε max / 2

[0031] g3 = g3(X T , X S , X D ) = m imax / 4.5

[0032] g4 = g4(X T , X S , X D ) = T max / 1100

[0033] g5 = g5(X T , X S , X D ) = T average / 570

[0034] Where X T is the topological variable of the structural component, taking values of 0 or 1; X S is the dimensional variable of the structural component, with a value range of 0.5 - 20 mm; X DThe angular variable of the structural component, with a value range of 0° to 180°; ΔC yα is the aeroelastic influence quantity; g i is a constraint. Among them, g1 is the stress constraint of the wing structure material, which is required not to exceed the allowable stress of 35 Mpa; g2 is the maximum displacement constraint of the wing structure, which is required not to exceed 2 mm; g3 is the total mass change constraint of the wing structure, which requires the total wing mass to be stable at 4.5 kg and the structural mass change not to exceed 5%; g4 is the maximum temperature constraint of the wing under flight conditions, which is required not to exceed 1200 K; g5 is the average temperature constraint of the wing under flight conditions, which is required not to exceed 570 K.

[0035] A storage medium, on which a computer program is stored; when the computer program is run, it executes the above method.

[0036] An electronic device, including a processor and a storage medium; a computer program is stored on the storage medium; when the computer program is run by the processor, it executes the above method.

[0037] Beneficial effects

[0038] Based on an optimization algorithm, the present invention establishes an effective hybrid multi-constraint optimization method for a radial structure considering aeroelasticity. Different from traditional hierarchical optimization, the present invention, based on the actual working environment of the aircraft, comprehensively considers constraints such as aerothermal, material allowable stress, and structural weight, and simultaneously realizes the hybrid optimization of the number, size, and angle of the structure, considering the correlation factors between various optimization objectives, which conforms to engineering practice. In addition, for the traditional optimization process based on the basic structure method, the layout of the determined basic structure will not be adjusted, which requires a high requirement for the initial basic structure layout design. In the optimization process of the present invention, the angular variable of the basic structure is introduced as an optimization variable, reducing the difficulty of the initial layout of the basic structure.

[0039] The additional aspects and advantages of the present invention will be partly given in the following description, partly will become obvious from the following description, or will be understood through the practice of the present invention. Description of the drawings

[0040] The above and / or additional aspects and advantages of the present invention will become obvious and easy to understand from the description of the embodiments in conjunction with the following drawings, in which:

[0041] Figure 1 Structural optimization framework

[0042] Figure 2 Optimization program framework

[0043] Figure 3 Radial structure basic structure diagram Specific implementation manners

[0044] Embodiments of the present invention will be described in detail below. The embodiments are exemplary and are intended to explain the present invention, but should not be construed as limiting the present invention.

[0045] Aiming at the deficiencies of hierarchical optimization in the traditional structural design process and minimizing the number of variables in the optimization process of the basic structure method as much as possible, this embodiment provides an optimization design method for the radial structure of a hypersonic vehicle, specifically a hybrid optimization of structure quantity - size - angle considering aeroelasticity based on a genetic algorithm to reduce the aeroelastic influence of the hypersonic vehicle. It includes the following three steps:

[0046] Step 1: Determine the original configuration of the radial structure in the aircraft component, and given the original basic structure, establish a three - dimensional finite element model of the aircraft component.

[0047] As Figure 3 shown, the aircraft component is a wing, and the radial structure is the internal beam structure of the wing. The original configuration of the radial structure is to arrange several wing beam structures from the middle of the wing root to the leading edge, the wing tip, and the trailing edge of the wing.

[0048] Step 2: According to the original configuration determined in Step 1, establish an optimization model:

[0049] Take the quantity, size, and angle of the radial structure in the aircraft component as design variables; specifically, the quantity of the wing beam structures, the width of each wing beam structure, and the angle between each wing beam structure and the wing root.

[0050] Take the minimum aeroelastic influence amount of the aircraft component as the objective function;

[0051] Take the stress, displacement, mass, and temperature of the radial structure as constraint conditions; specifically, the stress of the wing beam structure is less than the allowable stress used for the beam structure, the maximum displacement of the wing structure does not exceed the set value, the change in the wing mass does not exceed the set value, and the highest temperature and average temperature of the wing under flight conditions do not exceed the set value.

[0052] Step 3: Use an optimization algorithm to solve the optimization model, and perform a hybrid optimization of the quantity, size, and angle of the radial structure to obtain the optimal structural result.

[0053] In this embodiment, a genetic algorithm is used to solve the optimization model. In the genetic algorithm, the chromosome for the hybrid optimization of structure layout and size is divided into three parts: topological variables, size variables, and angle variables; among them, the topological variable is a variable with a value of 0 or 1: taking 1 indicates the existence of the wing beam structure, and taking 0 indicates the non - existence of the wing beam structure; the size variables and angle variables are continuous variables within a given range. To avoid the mutual interference between the topological variables and the size variables, a single - point crossover method is used for the topological variable, size variable, and angle variable parts of the chromosome respectively.

[0054] The established optimization model is as follows:

[0055] find X T ,X S ,X D

[0056] minΔC yα (X T ,X S ,X D )

[0057] s.t.g i ≤1 i = 1, 2, 4, 5

[0058] 0.95 ≤ g3 ≤ 1.05

[0059] X Tj ∈ {0, 1} j = 1, …, N

[0060] X Sj ∈ [0.5, 20] j = 1, …, N

[0061] X Dj ∈ [0°, 180°] j = 1, …, N

[0062] g1 = g1(X T ,X S ,X D ) = σ imax / 35

[0063] g2 = g2(X T ,X S ,X D ) = ε max / 2

[0064] g3 = g3(X T ,X S ,X D ) = m imax / 4.5

[0065] g4 = g4(X T ,X S ,X D ) = T max / 1100

[0066] g5 = g5(X T ,X S ,X D ) = T average / 570

[0067] where X T is the topological variable of the structural component, taking values of 0 or 1; XS is the size variable of the structural component, with a value range of 0.5 to 20 mm; X D is the angular variable of the structural component, with a value range of 0° to 180°; ΔC yα is the aeroelastic influence quantity, where, ΔC yα =(C yα刚性 -C yα弹性 ) / C yα刚性 ×100%; g i is the constraint, where, g1 is the stress constraint of the wing structural material, requiring not to exceed the allowable stress of 35 Mpa; g2 is the maximum displacement constraint of the wing structure, requiring not to exceed 2 mm; g3 is the total mass change constraint of the wing structure, requiring the total mass of the wing to be stable at 4.5 kg and the structural mass change not to exceed 5%; g4 is the maximum temperature constraint of the wing under flight conditions, requiring not to exceed 1200 K; g5 is the average temperature constraint of the wing under flight conditions, requiring not to exceed 570 K.

[0068] The external penalty function form of the structural optimization problem is defined as follows:

[0069]

[0070] When

[0071] g i ≤1 i = 1, 2, 4, 5

[0072] 0.95 ≤ g3 ≤ 1.05

[0073] at this time, u i = 0, otherwise u i = 1, r is the external penalty factor.

[0074] The update of the finite element model of the structure is realized by Matlab programming and modifying the Nastran mesh file. This module reads the mesh file of the finite element model of the base structure, changes the structure layout and structure size according to the values of the quantity variable, size variable and angular variable, and generates the finite element model of the new structure. The optimization framework recalculates the newly generated finite element model, and obtains the aeroelastic influence quantity, temperature distribution, maximum stress, maximum displacement of the structural component by calling Nastran for calculation to meet the constraint function of the optimization problem. Then, the mass and aeroelastic influence quantity, temperature distribution, maximum stress, maximum displacement of the structure are substituted into the objective function to calculate the fitness of the population individuals. Here, the evolutionary generation of the population is selected as the convergence judgment criterion of the optimization framework, or when it is observed that the objective function tends to be stable, the optimization program can also be manually terminated.

[0075] Step 4: Finally, determine whether the optimization result meets the design requirements. If it does, output the final result; if not, modify the constraint information and return to Step 2 to re-establish the optimization model.

[0076] Based on the actual working environment of the aircraft, the present invention comprehensively considers constraints such as aerodynamic heat, allowable material stress, and structural weight, and simultaneously realizes the hybrid optimization of the number, size, and angle of the structure, taking into account the correlation factors among various optimization objectives, which is in line with engineering practice.

[0077] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention without departing from the principle and purpose of the present invention.

Claims

1. A method for the mixed optimization design of the number, size, and angle of the radial structure of an aircraft considering aeroelasticity, characterized in that: Including the following steps: Step 1: Determine the original configuration of the radial structure in the aircraft component, given the original basic structure, and establish a three-dimensional finite element model of the aircraft component; Step 2: According to the original configuration determined in Step 1, establish an optimization model: Taking the number, size, and angle of the radial structures in the aircraft component as design variables; Taking the lowest aeroelastic influence on the aircraft component as the objective function; Taking the stress, displacement, mass, and temperature of the radial structure as constraints; The aircraft component is a wing, and the radial structure is the internal beam structure of the wing; The optimization model is: find X T ,X S ,X D minΔC yα (X T ,X S ,X D ) s.t.g i ≤1 for i = 1, 2, 4, 5 0.95≤g3≤1.05 X Tj ∈ {0, 1}, j = 1, …, N X Sj ∈[0.5, 20] for j = 1, …, N X Dj ∈ [0 o , 180 o for j = 1, …, N g1 = g1(X T , X S , X D ) = σ imax / 35 g2 = g2(X T , X S , X D ) = ε max / 2 g3 = g3(X T , X S , X D ) = m imax / 4.5 g4 = g4(X T , X S , X D ) = T max / 1100 g5 = g5(X T , X S , X D ) = T average / 570 where X T is the topological variable of the structural component, taking values of 0 or 1; X S is the dimensional variable of the structural component, with a value range of 0.5 - 20 mm; X D is the angular variable of the structural component, with a value range of 0° - 180°; ΔC yα is the aeroelastic influence quantity; g i is the constraint. Among them, g1 is the stress constraint of the wing structure material, required not to exceed the allowable stress of 35 Mpa; g2 is the maximum displacement constraint of the wing structure, required not to exceed 2 mm; g3 is the total mass change constraint of the wing structure, requiring the total wing mass to be stable at 4.5 kg and the structural mass change not to exceed 5%; g4 is the maximum temperature constraint of the wing under flight conditions, required not to exceed 1200 K; g5 is the average temperature constraint of the wing under flight conditions, required not to exceed 570 K; Step 3: Use an optimization algorithm to solve the optimization model, and perform a mixed optimization of the number, size, and angle of the radial structures to obtain the optimal structural result; Step 4: Judge whether the optimization result meets the design requirements. If it meets, output the final result. If it does not meet, modify the constraint information and return to Step 2 to re-establish the optimization model.

2. The method for hybrid optimization design of the number, size and angle of the radial structure of an aircraft considering aeroelasticity according to claim 1, wherein: The original configuration of the radial structure is to arrange several wing beam structures from the middle of the wing root to the leading edge, wing tip, and trailing edge of the wing.

3. The method for hybrid optimization design of the number, size and angle of the radial structure of an aircraft considering aeroelasticity according to claim 2, wherein: The design variables are the number of wing beam structures, the width of each wing beam structure, and the angle between each wing beam structure and the wing root.

4. A method for hybrid optimization design of the number, size, and angle of the radial structure of an aircraft considering aeroelasticity according to claim 1 or 3, characterized in that: The constraints are that the stress of the wing beam structure is less than the allowable stress used for the beam structure, the maximum displacement of the wing structure does not exceed the set value, the change in wing mass does not exceed the set value, and the highest temperature and average temperature of the wing under flight conditions do not exceed the set value.

5. The method for hybrid optimization design of the number, size and angle of the radial structure of an aircraft considering aeroelasticity according to claim 4, characterized in that: Use a genetic algorithm to solve the optimization model.

6. A method for optimizing the hybrid design of the number, size, and angle of the radial structure of an aircraft considering aeroelasticity, characterized in that: In the genetic algorithm, the chromosome is divided into three parts: topological variables, size variables, and angle variables; among them, the topological variable is a variable with a value of 0 or 1: taking 1 means the wing beam structure exists, and taking 0 means the wing beam structure does not exist; the size variable and the angle variable are continuous variables within a given range.

7. A storage medium, on which a computer program is stored; characterized in that: When the computer program is run, it executes the method described in claims 1 to 6.

8. An electronic device, comprising a processor and a storage medium; characterized in that: A computer program is stored on the storage medium; when the computer program is run by the processor, it executes the method described in claims 1 to 6.

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