Cabin section reinforcement optimization design method

Abstract

The invention provides a cabin reinforcement design method, which specifically comprises four modules: a cabin grid parameterization module for mapping a cabin grid to a unit square to form a parameterization grid; designing a variable characterization module: constructing a rib distribution form by using a piecewise linear function mapping mode; the parameter grid reconstruction module mainly aims at parameterizing grid information, the parameterization grid information comprises parameterization bottom grids and rib grids, and the parameterization bottom grids and the rib grids are mapped back to a cabin section domain; and the global optimization algorithm module is used for constructing a target and constraint function, updating a design variable by using a multi-point convex optimization algorithm, and obtaining an optimal rib configuration. According to the method, the mapping relation between the cabin section grid and the parameterized domain grid is constructed by using the curved surface parameterization algorithm, tedious hexahedral grid division is avoided, and only the triangular surface grid needs to be divided on the surface of the cabin section.

Description

Technical Field

[0001] The invention relates to the technical field of structural optimization design, and in particular to a cabin section reinforcement optimization design method. Background Art

[0002] Cabin structure optimization is an important means to improve the comprehensive load-bearing performance of aircraft. Limited by the processing technology, the topological optimization design has better performance, but the manufacturing is complex and the manufacturing cost is high. The combination of barrel and longitudinal and transverse ribs is more compatible with the existing cabin manufacturing methods. Therefore, it is necessary to optimize the design of the longitudinal and transverse ribs of the cabin to reduce the weight and improve the comprehensive load-bearing performance of the cabin. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a cabin reinforcement design method. The method specifically includes four modules: (1) cabin grid parameterization module; (2) parameter grid reconstruction module; (3) design variable characterization module; (4) design variable global optimization module;

[0004] Module 1: Cabin grid parameterization module: This module maps the cabin grid to a unit square to form a parameterized grid;

[0005] Step 1.1: Obtain the number of a ring of adjacent points of each grid node in the cabin, obtain the number of the unit to which each grid node belongs, calculate the normal vector of each unit, and calculate the normal vector of each node based on the average normal vector of the units around the grid node;

[0006] Step 1.2: Map the grid nodes on the four sides of the cabin to the four sides of the unit square. After mapping, the node position ratio remains unchanged. Use the Tutte surface parameterization algorithm or the Floater surface parameterization algorithm to map the nodes on the cabin to the unit square. The grid on the unit square is called a parameterized grid. Construct the mapping relationship between the coordinates of the parameterized grid nodes and the cabin grid nodes.

[0007] Module 2: Design variable characterization module: The typical design variables selected are rib height, rib thickness, and rib distribution, and the rib distribution form is constructed using piecewise linear function mapping;

[0008] Module 3: Parameter mesh reconstruction module: The main purpose of this module is to map the parameterized mesh information, including the parameterized bottom mesh and rib mesh, back to the cabin domain;

[0009] Step 3.1: Based on the design variable values, generate ribs in the normal direction of the corresponding position on the parameter plane, and divide the mesh based on this;

[0010] Step 3.2: Based on the mapping relationship between the cabin mesh and the parameter mesh obtained in module 2, use the three-dimensional linear interpolation algorithm to map the parameter domain mesh back to the cabin domain; also based on linear interpolation, obtain the normal vector of the cabin reinforcement position, and generate ribs based on the design variable information.

[0011] Module 4: Global optimization algorithm module: Construct objective and constraint functions, use multi-point convex optimization algorithm to update design variables, and obtain the optimal rib configuration.

[0012] Compared with the prior art, the present invention has the following advantages:

[0013] (1) The present invention proposes to use a surface parameterization algorithm to construct a mapping relationship between the cabin mesh and the parameterized domain mesh, avoiding cumbersome hexahedral mesh division and only dividing the cabin surface into triangular surface meshes.

[0014] (2) The present invention proposes to use normal vectors to achieve cabin mesh reinforcement, which can also avoid cumbersome hexahedral mesh division.

[0015] (3) The present invention proposes to use piecewise linear function mapping to characterize the distribution of ribs. The number of optimization variables is reduced from the number of ribs to the number of segments of the piecewise linear function minus one, which greatly reduces the optimization variables and improves the design efficiency.

[0016] (4) The present invention proposes to use a multi-point convex optimization algorithm to achieve global optimization, which improves efficiency compared to pure search algorithms such as genetic algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The included drawings are used to provide a further understanding of the embodiments of the present invention, which constitute a part of the specification, are used to illustrate the embodiments of the present invention, and together with the text description, explain the principles of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a flow chart of a cabin section reinforcement optimization design method in an embodiment of the present invention.

[0019] Figure 2 This is the triangular mesh division of the cabin half-mold in the embodiment of the present invention.

[0020] Figure 3 It is a schematic diagram of adjacent points of a ring in an embodiment of the present invention.

[0021] Figure 4 It is a schematic diagram of the grid to which the node belongs in the embodiment of the present invention.

[0022] Figure 5It is the grid distribution of the cabin section grid mapped to the parameter domain after the Tutte surface parameterization algorithm in the embodiment of the present invention.

[0023] Figure 6 is the mesh distribution after parameter domain reinforcement in the embodiment of the present invention.

[0024] Figure 7 In the embodiment of the present invention Figure 4 Meshing of the parameter domain mesh after back-mapping to the cabin.

[0025] Figure 8 It is an example of the piecewise linear mapping function used in the embodiment of the present invention, wherein (a) and (b) are respectively the distribution of ribs under different slopes when three-segment linear functions are selected; (c) and (d) are respectively the distribution of ribs under different slopes when four-segment linear functions are selected.

[0026] Fig. 9 This is the optimized cabin section rib distribution configuration in the embodiment of the present invention. DETAILED DESCRIPTION

[0027] It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0029] Unless otherwise specifically stated, the relative arrangement of the parts and steps described in these embodiments, numerical expressions and numerical values ​​do not limit the scope of the present invention. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, method and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0030] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. It is hereby stated that the enumerated embodiment is only an example application of the present invention, used to explain the present invention, and other applications that do not deviate from the framework of the principles described in the present invention are all within the protection scope of the present invention.

[0031] This embodiment describes a method for optimizing the design of cabin reinforcement. The main process is as follows: Figure 1 As shown in the figure, it includes the following modules: (1) cabin grid parameterization; (2) parameter grid reconstruction; (3) design variable representation; (4) design variable global optimization

[0032] Module 1: Tank Grid Parameterization Module. The main purpose of this module is to map the tank grid to a unit square to form a parameterized grid.

[0033] Step 1.1: Choose Figure 2 The half-model of the cabin is divided into triangular meshes. The number of the adjacent points of each mesh node in the cabin is obtained. The definition of the adjacent points of the first ring is as follows: Figure 3 Get the unit number of each grid node in the compartment. The unit to which the node belongs is shown as follows: Figure 4 As shown. Calculate the normal vector of each unit. Calculate the normal vector of each node based on the average of the normal vectors of the units around the grid node.

[0034] Step 1.2: Map the grid nodes on the four sides of the cabin to the four sides of the unit square. After mapping, the node position ratio remains unchanged. Use the Tutte surface parameterization algorithm or the Floater surface parameterization algorithm to map the nodes on the cabin to the unit square. The grid on the unit square is called a parameterized grid. Figure 2 The obtained parameterized grid is Figure 5 As shown in the figure, the mapping relationship between the parameterized grid nodes and the compartment grid node coordinates is constructed.

[0035] Module 2: Design variable characterization module. The typical design variables selected are rib height, rib thickness, rib distribution, etc. In order to reduce the design variables and improve the optimization efficiency, the rib distribution form is constructed using piecewise linear function mapping. The piecewise linear function mapping is shown in the figure below: Figure 6 As shown in the figure, (a) and (b) are the distribution of ribs with different slopes when three linear functions are selected; (c) and (d) are the distribution of ribs with different slopes when four linear functions are selected. The curve formed by the piecewise linear function must meet the monotonic condition. Assuming that n linear functions are used, the slopes of each segment k1, k2, ... k n Need to satisfy: k1+k2+…+k n =n, and k i >0,i=1,2,…,n.

[0036] Module 3: Parameterized mesh reconstruction module. The main purpose of this module is to map the parameterized mesh (including parameterized bottom mesh and rib mesh) back to the cabin domain.

[0037] Step 3.1: Based on the design variable values, generate ribs in the normal direction of the corresponding position on the parameter plane. And divide the mesh based on this. The mesh of the parameter domain after reinforcement is as follows: Figure 7 shown.

[0038] Step 3.2: Based on the mapping relationship between the cabin mesh and the parameter mesh obtained in module 2, the parameter domain mesh is back-mapped to the cabin domain using a three-dimensional linear interpolation algorithm. Also based on linear interpolation, the normal vector of the cabin reinforcement position is obtained, and the reinforcement strips are generated based on the design variable information. Figure 7 The model after the parameter domain is mapped back to the cabin domain is as follows Figure 8 shown.

[0039] Module 4: Global optimization algorithm module. Construct the objective and constraint functions, use the multi-point convex optimization algorithm to update the design variables, and obtain the optimal rib configuration. The optimized cabin rib configuration is as follows: Fig. 9 shown.

[0040] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. 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

1. A cabin reinforcement design method, characterized in that: The method specifically includes four modules: (1) cabin grid parameterization module; (2) parameter grid reconstruction module; (3) design variable representation module; (4) design variable global optimization module; Module 1: Cabin grid parameterization module: This module maps the cabin grid to a unit square to form a parameterized grid; Module 2: Design variable characterization module: The typical design variables selected are rib height, rib thickness and rib distribution, and the rib distribution form is constructed using piecewise linear function mapping; Module 3: Parameter mesh reconstruction module: The purpose of this module is to parameterize mesh information, including parameterized bottom mesh and rib mesh, and map it back to the cabin domain; Module 4: Global optimization algorithm module: Construct objective and constraint functions, use multi-point convex optimization algorithm to update design variables, and obtain the optimal rib configuration.

2. A cabin reinforcement design method according to claim 1, characterized in that: The module 1 comprises the following steps: Step 1.1: Obtain the number of a ring of adjacent points of each grid node in the cabin, obtain the number of the unit to which each grid node belongs, calculate the normal vector of each unit, and calculate the normal vector of each node based on the average normal vector of the units around the grid node; Step 1.2: Map the grid nodes on the four sides of the cabin to the four sides of the unit square. After mapping, the proportional relationship of the node positions remains unchanged. Use the Tutte surface parameterization algorithm or the Floater surface parameterization algorithm to map the nodes on the cabin to the unit square. The grid on the unit square is called a parameterized grid. Construct the mapping relationship between the coordinates of the parameterized grid nodes and the cabin grid nodes.

3. A cabin reinforcement design method according to claim 2, characterized in that: The module 3 comprises the following steps: Step 3.1: Based on the design variable values, generate ribs in the normal direction of the corresponding position on the parameter plane, and divide the mesh based on this; Step 3.2: Based on the mapping relationship between the cabin mesh and the parameter mesh obtained in module 2, use the three-dimensional linear interpolation algorithm to map the parameter domain mesh back to the cabin domain; also based on linear interpolation, obtain the normal vector of the cabin reinforcement position, and generate ribs based on the design variable information.

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