Airborne equipment wing profile hollow structure layout and size collaborative optimization method and system

Abstract

The present application relates to the technical field of airborne equipment structure optimization, and discloses a method and system for layout and size collaborative optimization of a hollow structure of an airfoil member of airborne equipment based on parameterized modeling, so as to achieve more refined weight reduction and efficiency improvement. The method comprises the following steps: dividing the skin into an array of regions in m rows and k columns in the width and length directions respectively; and constraining the relationship between parameters of the same type to be: the thickness of each wing spar is equally spaced from a first cubic spline curve in the arrangement order; the thickness of the m regions with k being 1 is equally spaced from a second cubic spline curve in the arrangement order; the thickness of the subsequent k-1 region units is the product of the thickness of the region unit with k being 1 in the same row and a proportionality coefficient, the proportionality coefficients of the m region units with the same k are consistent in value, and the k-1 proportionality coefficients are equally spaced from a third cubic spline curve in the arrangement order; and the optimal solution is obtained by constructing an optimization list, modeling and iteration.

Description

Technical Field

[0001] This invention relates to the field of airborne equipment structural optimization technology, and in particular to a method and system for the coordinated optimization of the layout and dimensions of hollow airfoil components of airborne equipment based on parametric modeling. Background Technology

[0002] Airfoil structures possess special functional characteristics such as generating lift and increasing flight distance, as well as excellent structural features such as lightweight and high specific stiffness. They are used as one of the important components that significantly improve the key performance of advanced airborne equipment. Among them, the integral airfoil structure has gradually become a design configuration with broad application prospects due to its characteristics of fewer connecting parts, low manufacturing cost and high design efficiency.

[0003] Currently, for the structural optimization design of airfoil structures, due to the complexity, diversity, and high dimensionality of the optimization variables, engineers generally adopt a step-by-step optimization method to solve engineering design optimization problems.

[0004] First, an initial conceptual layout design configuration is given based on traditional design methods or topology optimization methods, and then detailed dimensional optimization design is carried out based on the initial design scheme. However, in the initial design stage, the design configuration based on traditional design methods is usually established based on the designer's engineering experience, and often requires repeated iterative modifications. As the complexity of the design problem increases, the optimal solution of this type of method is only applicable to the optimal solution under specific conditions, and deviates significantly from the optimal solution of the optimization problem, making it difficult to obtain the optimal load-bearing layout configuration of the structure.

[0005] Secondly, although the conceptual design configuration obtained based on the topology optimization method can provide the optimal distribution design under finite material volume, its topology optimization solution has problems such as high computational cost and complex geometric features, making it difficult to achieve rapid design and efficient manufacturing.

[0006] Furthermore, in the detailed design phase, traditional dimensional optimization methods typically employ constant stiffness design methods. However, since the load on airfoil structures is non-uniformly distributed in service environments, constant stiffness design methods can lead to redundancy in the safety margin of the structure, making it difficult to achieve a rational distribution of stiffness. Summary of the Invention

[0007] The purpose of this invention is to disclose a method and system for co-optimizing the layout and size of hollow structures in airborne equipment airfoil components based on parametric modeling, so as to achieve more refined weight reduction and efficiency improvement.

[0008] To achieve the above objectives, the present invention discloses a method for coordinated optimization of the layout and dimensions of hollow structures in airborne equipment airfoil components based on parametric modeling, comprising:

[0009] Step S1: Determine the aerodynamic shape parameters and material type of the hollow airfoil structure. With minimizing the overall mass of the hollow airfoil structure as the optimization objective, divide the skin at both ends of the wing spars into a region array with m rows and k columns along the width and length directions, respectively. Determine the upper and lower limits of the target parameters to be optimized for the hollow airfoil structure and the overall allowable maximum deformation constraint. The target parameters include: the thickness of each skin region unit, the number of wing spars, their positions, and their thickness; the width direction is parallel to the centerline of the aircraft, and the skin thickness of the opposite region units at both ends of the wing spars is consistent.

[0010] Step S2: Construct an optimized representation and parameterized model of the hollow structure of the airfoil, and constrain the relationships between similar target parameters in the optimized representation as follows:

[0011] The thickness of each wing spars is taken at equal intervals from the first cubic spline curve according to the arrangement order;

[0012] Assume that the column order of each skin region unit increases with the increase of the distance from the centerline of the carrier aircraft. The thickness of the m regions with k=1 is taken at equal intervals from the second cubic spline curve according to the arrangement order. The thickness of the subsequent k-1 region units is uniformly taken as the product of the thickness of the region unit with k=1 in the same row and the scaling factor. Among them, the scaling factor of the m region units with the same k is consistent, and the values ​​of the k-1 scaling factors are all greater than 0 and less than 1, and are taken at equal intervals from the third cubic spline curve according to the arrangement order.

[0013] Step S3: During the optimization iteration of the target parameters, the mechanical properties of each solution under the target load are simulated based on the parameterized model of the hollow structure of the airfoil. When the iteration termination condition is reached, the iteration is terminated and the optimal solution that satisfies the optimization objective and constraint conditions is obtained.

[0014] Preferably, the position of the spar satisfies the following relationship:

[0015] ;

[0016] in, Expressed as the length of the airfoil section, For the first The location of the root wing spars For each wing spars, there is a dimensionless variable related to the spacing between the wing spars, and The target parameters to be optimized are: This refers to the number of wing beams.

[0017] Preferably, each cubic spline curve consists of three nodes: ( , ), ( , )and( , ) to determine, among which, and These are the constants 0 and 1 given by normalization, respectively. , , and For design variables;

[0018] The specific calculation formulas and equations for each cubic spline curve are as follows:

[0019] ; ;

[0020] In the formula, The values ​​include 0 and 1. Represented as in the interval a cubic polynomial segment on, , , and The coefficients are represented as a cubic polynomial segment; where the three cubic spline curves describe the normalized skin thickness or spar thickness based on the selected y-axis coordinate values.

[0021] To achieve the above objectives, the present invention also discloses a system for coordinated optimization of the layout and size of hollow structures of airborne equipment airfoil components based on parametric modeling, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method.

[0022] In contrast, traditional designs for hollow airfoil structures typically employ a uniform thickness for different spars, and the skin also uses a uniform thickness without regional differentiation. This invention, while performing more refined optimization of the skin by region, also simultaneously optimizes the number, position, and thickness of the spars, achieving coordinated optimization of layout and dimensions, and offering the following beneficial effects:

[0023] By constraining the relationships between similar target parameters, the thickness of each spar is determined by taking equidistant points from the first cubic spline curve in the order of arrangement; the thickness of the m regions with k=1 is determined by taking equidistant points from the second cubic spline curve in the order of arrangement; the thickness values ​​of the subsequent k-1 region elements are uniformly determined by multiplying the thickness of the region element with k=1 in the same row by the scaling factor, and the scaling factors of the m region elements with the same k are consistent, and the k-1 scaling factors are taken equidistantly from the third cubic spline curve in the order of arrangement. Since cubic spline curve functions can be determined using fewer control points, this invention selects three cubic spline curves to describe the collaborative relationship of airfoil skin thickness in different regions and the thickness collaborative relationship between different spars, effectively reducing the dimensionality of optimization variables and enriching the optimization design space. This allows for rapid optimization of each target parameter while ensuring the overall performance reliability of weight reduction and efficiency improvement.

[0024] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0025] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0026] Figure 1 This is a schematic diagram of the target parameters for optimizing the hollow structure of the airfoil disclosed in an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram of the optimization variable equidistant value selection method based on cubic spline curve function disclosed in the embodiments of the present invention.

[0028] Figure 3 This is a schematic diagram of the process for the collaborative optimization of the layout and size of the hollow structure of airfoil components of airborne equipment based on parametric modeling, as disclosed in an embodiment of the present invention. Detailed Implementation

[0029] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims.

[0030] Example 1

[0031] This embodiment discloses a method for the coordinated optimization of the layout and dimensions of hollow structures in airborne equipment airfoil components based on parametric modeling. The specific steps can be divided into:

[0032] Step 1: Based on the technical requirements of the hollow metal structure of the airfoil, determine the aerodynamic shape parameters, connection method, and material type of the airfoil structure.

[0033] Step 2: Based on the technical requirements of the project, establish an optimized list of lightweight designs for the hollow structure of the airfoil.

[0034] In this step, the number of spars, their spatial distribution, and the thickness of the spars and skin are used as optimization variables. The goal is to minimize the mass of the airfoil. Geometric constraints that meet the manufacturing process requirements are given. Under a given aerodynamic load, the maximum overall displacement of the airfoil structure is required to be within the reasonable design requirements. Partial optimization is shown in formula (1):

[0035] Formula (1)

[0036] in, This refers to the number of wing spars (also known as "stiffeners," hence indicated by their first letter). and This represents the minimum and maximum number of spars; This is expressed as the thickness of each spar. and Represented as the minimum and maximum thickness of the spar; This is expressed as the distance between each spar and the wingtip. and These represent the minimum and maximum distance positions of the wing spars; Represented as structural mass; This represents the maximum deformation of the entire structure. This represents the maximum allowable deformation within the design specifications.

[0037] In this embodiment, refer to Figure 1 The skin at both ends of the wing sparb is divided into a region array with m rows and k columns along the width and length directions, respectively; wherein the width direction is parallel to the centerline of the aircraft, and the skin thickness of the opposite region units at both ends of the wing sparb is consistent. In the formulation of formula (1), This represents the skin thickness of the m regions closest to the centerline of the aircraft in the width direction. and This is expressed as the minimum and maximum thickness of the skin. Simultaneously, this embodiment constrains the relationship between similar target parameters as follows: the thickness of each spar is taken at equal intervals from the first cubic spline curve according to the arrangement order; the thickness of the m regions where k is 1 (i.e., corresponding to...) The values ​​of k and k are taken at equal intervals from the second cubic spline curve in the order of arrangement. The thickness of the subsequent k-1 regional units (i.e., the regional units numbered 2-11 in the figure) is uniformly taken as the product of the thickness of the regional unit where k is 1 in the same row and the scaling factor. The scaling factor of the m regional units with the same k is consistent, and the k-1 scaling factors are taken at equal intervals from the third cubic spline curve in the order of arrangement.

[0038] The so-called "equidistant point selection" means: assuming that the number of parameters of the same type to be optimized (the thickness, number of spars, position and thickness of each skin unit belong to different parameter types) is S, then in the normalized corresponding cubic spline curve, the X-axis direction is divided into S+1 uniformly distributed intervals, and the parameter values ​​are the values ​​of the cubic spline curve on the Y-axis; during the optimization process, the distance between two adjacent parameters of the same type in the X-axis direction is kept constant at 1 / (S+1); which is equivalent to keeping the translation amount of the same type of parameters in the X-axis direction constant during the optimization process.

[0039] Considering that cubic spline curve functions can be determined using fewer control points, effectively reducing the dimensionality of optimization variables and enriching the optimization design space, this embodiment selects three cubic spline curves to describe optimization parameters such as airfoil skin thickness and spar thickness.

[0040] In this embodiment, each cubic spline curve consists of three nodes: ( , ), ( , )and( , ) to determine, among which, and These are the constants 0 and 1 given by normalization, respectively. , , and The design variables are used; the specific calculation formulas and equations for each cubic spline curve can be as follows:

[0041] ;Formula (2)

[0042] ;Formula (3)

[0043] In the formula, The values ​​include 0 and 1. Represented as in the interval a cubic polynomial segment on, , , and It is represented as the coefficient of a cubic polynomial segment.

[0044] In this embodiment, the three cubic spline curves describe the normalized skin thickness or spar thickness based on the selected y-axis coordinate values. Taking the thickness parameters of four spars as an example, the optimization parameter selection method based on the cubic spline curve function is as follows: Figure 2 As shown, where, For a given constant, The value ranges from 1 to Based on the number of spars, the interval containing the X-axis The point is determined by taking equidistant points within the area; The optimization variables are located in the Y-axis direction, corresponding to the thickness of each wing beam to be optimized. It is worth noting that the optimization processes of the three cubic spline curves in this embodiment are independent of each other.

[0045] In this step, the preferred position of the spar satisfies the following relationship: ;in, Expressed as the length of the airfoil section, For the first ( The location of the root wing beam, For each wing spars, there is a dimensionless variable related to the spacing between the wing spars, and These are the target parameters to be optimized.

[0046] Based on the above, the constructed optimized formula can be rewritten as based on , Among the parameters of the three control points corresponding to each cubic spline curve , , and The search for optimization.

[0047] Furthermore, the thickness of the spar and skin can be normalized based on the maximum and minimum values ​​of the constraints. For example, if the lower limit of the stiffener thickness is 4mm and the upper limit is 12mm, then this range of values ​​can be mapped to an interval. When the width of a certain spar is 0.5, its corresponding actual thickness is 8mm; this is common knowledge for those skilled in the art and will not be elaborated further.

[0048] Step 3: Based on the transformed optimization parameters, optimization objectives, and constraints, establish an automated workflow for the entire process of finite element parametric modeling, analysis, and post-processing based on the hollow metal structure of the airfoil. This can be further divided into the following sub-steps.

[0049] Step 3.1: Based on the geometric characteristics of the optimized structure, , Among the parameters of the three control points corresponding to each cubic spline curve , , and The design variables are used as parameters to achieve parametric modeling of the airfoil geometry. The thickness parameters of the spar and skin are normalized, and the arrangement order of the spar and skin and the mapping relationship between the points of the corresponding cubic spline curves are preset in the background program.

[0050] Step 3.2: Based on the design characteristics of the airfoil structure, set the structural material properties and perform mesh generation for each component to ensure that the mesh quality meets the accuracy requirements.

[0051] Step 3.3: Based on the connection form and load boundary conditions of the airfoil structure, the analysis model is reasonably simplified, and an appropriate analysis load step type is selected to realize the parametric modeling and numerical calculation of the airfoil finite element model.

[0052] Step 3.4: Based on the optimization objective and constraints, extract the overall structural mass and maximum deformation from the calculation results.

[0053] Step 4: Using the optimization algorithm, perform optimization on the transformed optimized representation, select the optimal design variables, and obtain the quality and maximum deformation of the optimized model to meet the optimization objectives and constraints.

[0054] In summary, the essence of this embodiment lies in... Figure 3 The following are the core steps:

[0055] Step S1: Determine the aerodynamic shape parameters and material type of the hollow airfoil structure. With minimizing the overall mass of the hollow airfoil structure as the optimization objective, divide the skin at both ends of the wing spars into a region array with m rows and k columns along the width and length directions, respectively. Determine the upper and lower limits of the target parameters to be optimized for the hollow airfoil structure and the overall allowable maximum deformation constraint. The target parameters include: the thickness of each skin region unit, the number of wing spars, their positions and thicknesses; the width direction is parallel to the centerline of the aircraft, and the skin thickness of the opposite region units at both ends of the wing spars is consistent.

[0056] Step S2: Construct an optimized representation and parameterized model of the hollow structure of the airfoil, and constrain the relationships between similar target parameters in the optimized representation as follows: the thickness of each spar is taken at equal intervals from the first cubic spline curve according to the arrangement order; assuming that the column order of each skin region unit increases with the increase of the distance from the centerline of the aircraft, the thickness of the m regions with k=1 is taken at equal intervals from the second cubic spline curve according to the arrangement order; the thickness of the subsequent k-1 region units is uniformly taken as the product of the thickness of the region unit with k=1 in the same row and the scaling factor, wherein the scaling factor of the m region units with the same k is consistent, and the value range of the k-1 scaling factor is all greater than 0 and less than 1, and is taken at equal intervals from the third cubic spline curve according to the arrangement order.

[0057] Step S3: During the optimization iteration of the target parameters, the mechanical properties of each solution under the target load are simulated based on the parameterized model of the hollow structure of the airfoil. When the iteration termination condition is reached, the iteration is terminated and the optimal solution that satisfies the optimization objective and constraint conditions is obtained.

[0058] In a specific simulation experiment, the hollow structure of the airfoil was made of aluminum alloy material of grade 2A14-T6, with an elastic modulus of 70 GPa, a Poisson's ratio of 0.3, and a density of 2.8 g / cm3. A fixed constraint was applied to the airfoil's shaft hole, and an equivalent aerodynamic load of 1 g was applied to the airfoil's skin surface. Based on the optimized solution obtained using the method in this embodiment, compared to the traditional uniformly distributed method that does not distinguish between the spars and skin regions, the mass was reduced by 22.1%, and the maximum Mises stress was reduced by 3.87%.

[0059] Example 2

[0060] This embodiment discloses a system for coordinated optimization of the layout and size of hollow structures of airborne equipment airfoils based on parametric modeling, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method corresponding to the above embodiment.

[0061] In summary, the methods and systems disclosed in the two embodiments of the present invention, while performing more refined optimization of the skin regions, also simultaneously optimize the number, position, and thickness of the spars, achieving coordinated optimization of layout and dimensions, and have the following beneficial effects:

[0062] By constraining the relationships between similar target parameters, the thickness of each spar is determined by taking equidistant points from the first cubic spline curve in the order of arrangement; the thickness of the m regions with k=1 is determined by taking equidistant points from the second cubic spline curve in the order of arrangement; the thickness values ​​of the subsequent k-1 region elements are uniformly determined by multiplying the thickness of the region element with k=1 in the same row by the scaling factor, and the scaling factors of the m region elements with the same k are consistent, and the k-1 scaling factors are taken equidistantly from the third cubic spline curve in the order of arrangement. Since cubic spline curve functions can be determined using fewer control points, this invention selects three cubic spline curves to describe the collaborative relationship of airfoil skin thickness in different regions and the thickness collaborative relationship between different spars, effectively reducing the dimensionality of optimization variables and enriching the optimization design space. This allows for rapid optimization of each target parameter while ensuring the overall performance reliability of weight reduction and efficiency improvement.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for parameterized modeling based layout and sizing optimization of a wing-shaped airborne equipment hollow structure, characterized in that, The method comprises the following steps: Step S1, determining the aerodynamic shape parameters and material types of the wing hollow structure, minimizing the overall mass of the wing hollow structure as the optimization target, dividing the skin at both ends of the wing spar into an array of regions in m rows and k columns along the width and length directions respectively, determining the upper and lower limits of the target parameters to be optimized of the wing hollow structure and the overall allowable maximum deformation constraint, the target parameters including the thickness of each regional unit of the skin, the number, position and thickness of the wing spars; the width direction is parallel to the center axis of the aircraft, and the skin thickness of the opposite position regional units at both ends of the wing spar is consistent; Step S2, constructing an optimization list and a parameterized model of the wing hollow structure, and constraining the relationship between target parameters of the same type in the optimization list as follows: The thickness of each wing spar is equally spaced from a first cubic spline curve in arrangement order; Supposing that the column sequence of each regional unit of the skin increases with the increase of the distance from the center axis of the aircraft, the thickness of the m regions with k being 1 is equally spaced from a second cubic spline curve in arrangement order; the thickness of the subsequent k-1 regional units is the product of the thickness of the regional unit with k being 1 in the same row and a proportional coefficient, wherein the proportional coefficients of the m regional units with the same k are consistent, and the value range of the k-1 proportional coefficients is greater than 0 and less than 1 and is equally spaced from a third cubic spline curve in arrangement order; Step S3, in the optimization iteration process of the target parameters, simulating the mechanical properties of each solution under the action of the target load based on the parameterized model of the wing hollow structure, and terminating the iteration and obtaining the optimal solution satisfying the optimization target and the constraint condition when the iteration termination condition is reached.

2. The parameterized modeling based layout and sizing optimization method of a wing-shaped airborne equipment hollow structure according to claim 1, characterized in that, The position of the wing spar satisfies the following relationship: ； wherein denotes the length of the airfoil section, is the position of the root airfoil, is a dimensionless variable related to the distance of the respective root airfoil, and is the target parameter to be optimized, is the number of airfoils.

3. The parametric modeling based layout and sizing optimization method of a wing-shaped airborne equipment hollow structure according to claim 1 or 2, characterized in that, Each cubic spline curve consists of three nodes: ( , ), ( , )and( , ) to determine, among which, and These are the constants 0 and 1 given by normalization, respectively. , , and Design variables; The calculation formula and equation set of each cubic spline curve are as follows: ； ； wherein the values of a, b, c, d, e, f, g, h, i, j, k, 1, m, n, o, p, q, r, s, t, u, v, w, x, y, z, and w include 0 and 1, is represented as a cubic polynomial segment on the interval is represented as a cubic polynomial segment on the interval , , and are represented as coefficients of the cubic polynomial segment; wherein the three cubic spline curves describe the normalized skin thickness or spar thickness based on the selected y-axis coordinate values, respectively.

4. An airborne equipment wing-shape hollow structure layout and size co-optimization system based on parameterized modeling, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method of any one of claims 1 to 3 when executing the computer program.

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