Reliability-based undercarriage key structure weight reduction optimization design method

Abstract

The invention discloses an undercarriage key structure weight reduction optimization design method based on reliability, and the method comprises the steps: carrying out the precise modeling and simulation analysis of key parts of an undercarriage through ANSYS, and achieving the geometric parameterization process through the command stream writing of APDL; the reliability weight reduction optimization design is completed in combination with MATLAB software and the established reliability optimization model, and the purpose of weight reduction is achieved while the reliability and strength requirements are met. According to the method, the blank in the prior art is filled, and a new thought and method are provided for lightweight design of undercarriages and other aircraft key components.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft, and in particular relates to a reliability-based weight reduction optimization design method for key landing gear structures. Background Art

[0002] Landing gear is a vital component of an aircraft, bearing all loads during takeoff, landing, taxiing, and parking. Its performance directly impacts the safety and economic efficiency of the aircraft. With the rapid development of the aviation industry, aircraft design requirements for landing gear are increasing, particularly in terms of lightweighting, reliability, and strength. Lightweight design not only reduces the overall weight of the aircraft and reduces fuel consumption, but also improves its maneuverability and payload capacity. Reliability and strength are key to ensuring safe operation under complex operating conditions. Therefore, achieving weight reduction while ensuring reliability and strength has become a key research topic in aeronautical engineering. Currently, landing gear design primarily focuses on structural configuration optimization and deterministic weight reduction optimization. However, these approaches have the following shortcomings: Most existing patents employ deterministic optimization methods based on fixed design parameters and load conditions, failing to consider uncertainties such as material properties and manufacturing errors. This can lead to reliability issues in practical applications. Secondly, key components of the landing gear, such as the strut outer tube, rocker arm, and locking arm, are crucial to its overall performance. However, prior research on weight reduction optimization of these components is limited, failing to fully exploit their weight reduction potential. Existing patents mostly focus on optimizing a single aspect, such as the optimization of the structural configuration design, and lack a comprehensive optimization method that comprehensively considers reliability, strength and weight. This makes it difficult to meet the comprehensive requirements of modern aircraft for high performance, high reliability and lightweight landing gear. Summary of the Invention

[0003] To overcome the shortcomings of existing technologies, this paper provides a reliability-based method for optimizing the weight reduction of key landing gear structures. This method utilizes ANSYS to accurately model and simulate key landing gear components. This method then implements geometric parameterization through APDL command flow programming. This method, combined with MATLAB software and the established reliability optimization model, achieves a reliability-based weight reduction optimization design, ensuring that both reliability and strength requirements are met while achieving weight reduction. This invention not only fills a gap in the existing technology but also provides new ideas and methods for the lightweight design of landing gear and other key aircraft components.

[0004] The technical solutions adopted by the present invention to solve the technical problems are as follows:

[0005] Step 1: Accurate modeling and simulation of the pillar outer cylinder based on ANSYS;

[0006] Utilize ANSYS to accurately model and simulate key landing gear components to ensure model accuracy. Then, program APDL command streams to implement geometric parametric modeling of key components, facilitating subsequent optimization design.

[0007] Step 2: Reliability weight reduction optimization design;

[0008] Based on the simulation model of the landing gear strut outer tube, the APDL command stream is used to execute the parametric simulation process, and a structural reliability optimization design model for the strut outer tube is established to achieve weight reduction.

[0009] Preferably, the step 1 is specifically:

[0010] Step 1-1: Prepare for modeling;

[0011] Select the coordinate system and unify the units; the global coordinate system in the modeling process is directly consistent with the coordinate system of the CATIA software; set a unified unit system, where the model length unit is mm, the stress unit is MPa, and the density unit is t / mm 3 ;

[0012] Step 1-2: Establish finite element model;

[0013] In CATIA software, unnecessary parts of the model were simplified, and the landing gear strut outer tube, which was the object for analysis and research, was separated;

[0014] The model consists of two parts: the main body of the pillar outer tube and the lug connection parts on the pillar outer tube. First, create the main body of the pillar outer tube, or the cylinder, and then model the lugs on the pillar outer tube. Use straight surfaces instead of curved surfaces to shear the upper end of the outer tube, and simplify the large hole at the upper end of the outer tube.

[0015] Use Boolean operations to modify the preliminarily built model; after the model is built, use the working plane to divide the line surface of the model into grids;

[0016] Steps 1-3: Set loads and boundary conditions;

[0017] After meshing is complete, loads and boundary conditions are applied to solve for the maximum stress. The lug at the upper end of the entire strut outer tube is connected to the landing gear upper joint, and the lug at the lower end is connected to the landing gear anti-torsion arm.

[0018] The load on the entire pillar outer tube structure is measured by ADAMS, and then the force at the point of action is converted to the entire action plane;

[0019] Steps 1-4: Finite element analysis results;

[0020] The maximum stress σ obtained by finite element analysis of the outer tube of the pillarmax The dangerous points with maximum stress are the restraining ends of the upper and lower ears and the connection between the ears and the transmission cylinder near the pressure application point.

[0021] Preferably, the step 2 is specifically as follows:

[0022] Step 2-1: Take the average of the thickness of the outer tube wall of the pillar and the thickness of the lugs at different positions on the outer tube of the pillar is the design variable; when the maximum stress in the pillar outer tube during operation reaches the maximum allowable stress, it is determined that the pillar outer tube has failed. Therefore, the following function is established:

[0023] g(H)=g(h,h2,…,h4)=σ max (h,h2,…,h4)-σ0 (1)

[0024] Among them, σ max (h, h2,…, h4) is the maximum stress of the landing gear strut outer tube structure obtained by ANSYS finite element analysis, which is related to the input variables, and σ0 is the maximum allowable stress;

[0025] Yield stress σ of the pillar outer tube structural material b The maximum allowable stress σ0 is 1580 MPa, and the safety factor n is 1.88.

[0026] σ0=σ b / n=838Mpa (2)

[0027] Step 2-2: Taking the minimum weight of the entire structure as the reliability optimization design goal, establish the reliability optimization design model of the landing gear strut outer tube structure as shown below:

[0028]

[0029] Where, the target failure probability of the pillar outer tube structure is P f =5×10 -4 ; V(μ) represents the optimization objective function, that is, the weight function of the structure, g(μ) represents the functional function defined based on strength failure, and P{g(μ)≤0} represents the failure probability of the functional function;

[0030] Step 2-3: Based on the adaptive Kriging surrogate model, the reliability optimization design method is used to solve the problem. The steps are as follows:

[0031] 1) Initialization setting, let k = 0, Indicates the design point of the current iteration;

[0032] 2) Generate sample pool S, use Latin square sampling LHS, through the initial design point and the probability density function of its random variable to generate N samples (X1, X2, ..., X N );

[0033] 3) Generate N initial Initial samples And calculate the output response values ​​of the functional functions corresponding to the m constraints respectively

[0034] 4) Using the generated initial training samples and output response values, construct i initial Kriging models

[0035] 5) Estimate the response corresponding to the samples in the sample pool S through the constructed initial Kriging model, and thus obtain the predicted values ​​corresponding to different constraints and standard deviation

[0036] 6) Pass Calculate the learning function U of the sample pool S i (X j )(i=1,2,...m,j=1,2,...,N), then by Find the updated sample points and add them to the i Kriging models until the convergence criterion minU i (X j )≥2 satisfied;

[0037] 7) Estimate the failure probability corresponding to each constraint using the currently updated Kriging model;

[0038] 8) After updating the probability constraint calculation results, perform optimization design iteration to obtain the iterative design point

[0039] 9) Determine whether convergence is achieved; if the optimized convergence conditions are met, the optimal design point is output. Otherwise, add 1 to k and return to step 7).

[0040] Preferably, in the steps 1-2, the units of the model are SOLID186 type, and tetrahedral 6-node units are uniformly used when dividing the finite element mesh. The finite element model is divided into a total of 60,372 units and 117,568 unit nodes.

[0041] Preferably, the outer layer of the reliability optimization design method is a sequence decoupling algorithm, and the inner layer is an AK-MCS algorithm.

[0042] A computer program that enables a computer to execute the above-mentioned method for optimizing the weight reduction design of key landing gear structures.

[0043] An electronic device comprises: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the above-mentioned landing gear key structure weight reduction optimization design method.

[0044] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for optimizing the weight reduction design of key landing gear structures.

[0045] A chip includes: a processor for calling and running a computer program from a memory, so that a device equipped with the chip executes the above-mentioned method for optimizing the weight reduction of a key landing gear structure.

[0046] A computer program product includes a computer storage medium storing a computer program, wherein the computer program includes instructions executable by at least one processor, and when the instructions are executed by the at least one processor, the above-mentioned landing gear key structure weight reduction optimization design method is implemented.

[0047] The beneficial effects of the present invention are as follows:

[0048] 1. This paper takes key components such as the landing gear strut outer tube, rocker arm, and locking arm as research objects. By introducing a reliability optimization model and combining ANSYS and MATLAB software, it achieves accurate modeling, simulation analysis, and weight reduction optimization of key components, ensuring that the weight reduction of the landing gear is achieved while meeting reliability and strength requirements.

[0049] 2. Compared to existing deterministic structural weight reduction optimization methods, this invention incorporates a reliability optimization model, taking uncertainty into account and ensuring the reliability of the design results. Through precise modeling and simulation analysis, combined with MATLAB software, this reliability weight reduction optimization design significantly reduces the weight of key components. By comprehensively considering reliability, strength, and weight, this method achieves comprehensive optimization design of key components, improving the overall performance and weight reduction of the landing gear.

[0050] 3. This method is not only applicable to key components such as landing gear strut outer tubes, rocker arms, and locking arms, but can also be extended to the weight reduction and optimization design of other key aircraft components. Overall, this method offers advantages such as meeting reliability requirements, significant weight reduction, comprehensive optimization, and wide application, making it suitable for the weight reduction and optimization design of key aircraft components. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic diagram of the overall solid model of the landing gear;

[0052] Figure 2 It is a simplified process diagram of the outer cylinder of the support;

[0053] Figure 3 This is a schematic diagram of the overall simplified model of the pillar outer cylinder;

[0054] Figure 4 This is a schematic diagram of the final mesh division results of the model;

[0055] Figure 5 Schematic diagram of constraint application, (a) clamped constraint of the lower end ear piece (b) clamped constraint of the upper end ear piece;

[0056] Figure 6 Schematic diagram of load application, (a) pressure application at the connection between the support outer tube and the lock arm (b) pressure application at the connection between the support outer tube and the rocker arm;

[0057] Figure 7 This is the finite element analysis result diagram;

[0058] Figure 8 Schematic diagram of the specific location of design variables, (a) (b)

[0059] Figure 9 Flowchart for solving RBDO problem based on efficient Kriging surrogate model;

[0060] Figure 10 A flow chart of the reliability-based weight reduction optimization design method for key landing gear structures;

[0061] Figure 11 This is the finite element analysis result diagram of the rocker arm;

[0062] Figure 12 Schematic diagram of the specific positions of the design variables of the rocker arm;

[0063] Figure 13 This is the finite element analysis result diagram of the locking arm;

[0064] Figure 14 Schematic diagram of the specific positions of the design variables of the locking arm;

[0065] Figure 15 The results of weight reduction optimization design for key landing gear components based on reliability are presented.

[0066] Figure markings: 1-upper joint, 2-rocker arm, 3-pillar outer tube, 4-pillar inner tube, 5-retraction mechanism, 6-locking arm, 7-anti-torsion arm. DETAILED DESCRIPTION

[0067] The present invention will be further described below with reference to the accompanying drawings and examples.

[0068] This paper proposes a reliability-based weight reduction optimization design method for key landing gear components, including the outer tube, rocker arm, and locking arm. This method utilizes ANSYS for precise modeling and simulation analysis of key landing gear components. This method then implements geometric parameterization through APDL command flow programming. This method, combined with MATLAB software and the established reliability optimization model, completes the reliability-based weight reduction optimization design, ensuring that weight reduction is achieved while meeting reliability and strength requirements. This invention not only fills a gap in the existing technology but also provides new ideas and methods for the lightweight design of landing gear and other key aircraft components.

[0069] The specific plan is as follows:

[0070] 1. Accurate modeling and simulation of the pillar outer cylinder based on ANSYS;

[0071] ANSYS was used to accurately model and simulate the key components of the landing gear to ensure model accuracy. APDL command streams were then written to implement geometric parametric modeling of key components, facilitating subsequent optimization design.

[0072] (1) Prepare for modeling;

[0073] It mainly includes the selection of coordinate system and the unification of units. In order to facilitate the application of loads and constraints, the global coordinate system in the modeling process is directly consistent with the coordinate system of CATIA software; since there is no clear unit in ANSYS, a set of unified units is set, in which the model length unit is mm, the stress unit is MPa, and the density unit is t / mm 3 . ;

[0074] (2) Establish a finite element model;

[0075] The overall model of the landing gear is relatively complex, such as Figure 1 As shown, directly performing finite element analysis on the entire strut outer cylinder model would complicate meshing and incur high computational costs. Therefore, to reduce the computational cost of finite element simulation, the entire model needs to be simplified without compromising the results. In CATIA, unnecessary model components are simplified, and the landing gear strut outer cylinder, the target for analysis, is isolated.

[0076] The whole model is mainly composed of two parts, one is the main part of the pillar outer tube, and the other is some connecting parts such as lugs on the pillar outer tube. The modeling idea is to first create the main body of the pillar outer tube, that is, the cylinder part. Figure 2As shown, the lugs on the outer tube of the strut are then modeled. In order to simplify the model, some problems were encountered during the modeling process, such as the presence of some small chamfers and several lugs on the transmission tube that bear less pressure. In order to simplify the modeling process, the small chamfers and some lugs were ignored. Also, for the sake of simplicity in the modeling process, a straight surface was used instead of a curved surface to shear the upper end of the outer tube, and the large hole at this location was simplified to a certain extent. Finally, a simplified model of the landing gear strut outer tube was established in the ANSYS finite element analysis software as shown below. Figure 3 shown.

[0077] Finally, in order to facilitate meshing and final simulation calculations, the preliminarily built model was modified several times using Boolean operations to delete extremely small lines and surfaces that appeared due to the design to prevent serious impact on the quality of the mesh, or even to prevent the mesh from being unable to be divided. After the model was built, the lines and surfaces of the model were divided using the work plane to generate high-quality meshes. The model unit was selected as SOLID186 type, and the tetrahedron 6-node unit was uniformly used when dividing the finite element mesh. The mesh division is as follows: Figure 4 As shown in the figure, the finite element model is divided into 60372 units and 117568 unit nodes.

[0078] (3) Set loads and boundary conditions;

[0079] After meshing is complete, loads and boundary conditions need to be applied to solve for the maximum stress. The lugs at the upper end of the entire strut outer tube are connected to the landing gear upper joint, and the lugs at the lower end are connected to the landing gear anti-torsion arm. The lugs in the middle of the strut outer tube bear a greater pressure, so the constraints of the entire structure and the application of pressure are mainly concentrated on these surfaces. The constraints applied are as follows: Figure 5 shown.

[0080] The load on the entire pillar outer tube structure can be measured by ADAMS, and then the force at the point of action is converted to the entire action plane. The load is applied as follows: Figure 6 shown.

[0081] After the overall constraints and loads are applied, the finite element analysis of the outer cylinder of the support can be performed.

[0082] (4) Finite element analysis results;

[0083] The finite element analysis results of the pillar outer tube are as follows Figure 7 As shown, the maximum stress σ max It is 889.755Mpa, and the dangerous points with maximum stress are the restraining ends of the upper and lower ears and the connection between the ears and the transmission cylinder near the pressure application point.

[0084] 2. Reliability and weight reduction optimization design;

[0085] Based on the above simulation model of the landing gear strut outer tube, the APDL command stream is used to execute the parametric simulation process, and a structural reliability optimization design model for the strut outer tube is established to achieve the purpose of weight reduction. The average value of the strut outer tube wall thickness and the lug thickness on the strut outer tube is taken. is the design variable, and its specific location is Figure 8 According to the structural functional requirements of the pillar outer tube, it will be subjected to large external forces during operation. When the maximum stress of the pillar outer tube during operation reaches the maximum allowable stress, it can be considered that the pillar outer tube has failed. Therefore, the following functional function can be established:

[0086] g(H)=g(h,h2,…,h4)=σ max (h,h2,…,h4)-σ0 (1)

[0087] Among them, σ max (h, h2, ..., h4) is the maximum stress of the landing gear strut outer tube structure obtained by ANSYS finite element analysis, which is related to the input variables, and σ0 is the maximum allowable stress. The yield stress σ of the strut outer tube structure material b is 1580Mpa, and the safety factor n is 1.88. Then the maximum allowable stress σ0 is

[0088] σ0=σ b / n=838Mpa (2)

[0089] Taking the minimum weight of the entire structure as the reliability optimization design goal (the overall density of the structure is the same, therefore, the minimum structure volume is the reliability optimization design goal), the reliability optimization design model of the landing gear strut outer tube structure is established as shown below

[0090]

[0091] Where, the target failure probability of the pillar outer tube structure is P f =5×10 -4 .

[0092] Based on the adaptive Kriging agent model, an efficient reliability optimization design method (the outer layer is the sequential decoupling algorithm, the inner layer is the AK-MCS algorithm) is used to solve the problem. The specific flow chart is as follows: Figure 9 As shown, the steps are as follows:

[0093] 1) Initialization setting, let k = 0,

[0094] 2) Generate sample pool S, use Latin square sampling (LHS), through the initial design point and the probability density function of its random variable to generate N samples (X1, X2, ..., X N ).

[0095] 3) Generate N initial Initial samples And calculate the output response values ​​of the functional functions corresponding to the m constraints respectively

[0096] 4) Using the generated initial training samples and output response values, construct i initial Kriging models

[0097] 5) Estimate the response corresponding to the samples in the sample pool S through the constructed initial Kriging model, and thus obtain the predicted values ​​corresponding to different constraints and standard deviation

[0098] 6) Pass To calculate the learning function U of the sample pool S i (X j )(i=1,2,...m,j=1,2,...,N), then by Find the updated sample points and add them to the i Kriging models until the convergence criterion minU i (X j )≥2 is satisfied.

[0099] 7) Use the currently updated Kriging model to estimate the failure probability corresponding to each constraint.

[0100] 8) After updating the probability constraint calculation results, perform optimization design iteration to obtain the iterative design point

[0101] 9) Determine whether it converges. If the optimization convergence conditions are met, the optimal design point is output. Otherwise, add 1 to k and return to step 7).

[0102] Example:

[0103] The initial values ​​of the design variables are x0 = [10.7, 20.01, 21, 55.912, 16]. The initial parameter settings for reliability optimization are shown in Table 1, and the reliability optimization results are shown in Table 2. During the iterative process of the reliability weight reduction optimization design, it was clearly seen that the main influencing parameter for the pillar outer tube weight reduction was the pillar outer tube thickness, which accounted for over 90% of the overall weight reduction. Therefore, in the iterative design, h was selected as the primary variable, increasing its importance, while appropriately reducing the importance of lug thicknesses such as h2 and h3 to ensure more efficient program execution.

[0104] Table 1 Initial values ​​and distribution types of design variables

[0105] random variable Distribution type mean Coefficient of variation Cylinder wall thickness h(mm) normal distribution 10.7 0.01 <![CDATA[Inclination thickness h1 (mm)]]> normal distribution 20.01 0.01 <![CDATA[Ear piece thickness h2 (mm)]]> normal distribution 21 0.01 <![CDATA[Thickness h3 (mm) of round cake]]> normal distribution 55.912 0.01 <![CDATA[Aperture h4 (mm)]]> normal distribution 16 0.01

[0106] Table 2 Reliability optimization results

[0107] Design variables Before optimization After optimization Cylinder wall thickness h(mm) 10.7 9.87 <![CDATA[Inclination thickness h1 (mm)]]> 20.01 19.7 <![CDATA[Ear piece thickness h2 (mm)]]> 21 20.6 <![CDATA[Thickness h3 of round cake (mm)]]> 55.912 55.5 <![CDATA[Thickness h4 of the cylinder wall (mm)]]> 16 15.9 Failure probability 4e-5 6e-5 <![CDATA[Total volume V (mm 3 )]]> 1.9482e07 1.8624e7

[0108] The reliability optimization results show that the optimized design variables have values ​​of (9.87, 19.70, 20.60, 55.50, and 15.90). The volume of the strut outer tube after optimization is 1.8624e7, a decrease compared to the pre-optimization model. The failure probability corresponding to the optimized static reliability analysis model for the landing gear retraction mechanism is 6e-5, which is within the acceptable failure probability range. The optimization results in a 4.60% weight reduction.

[0109] The strut outer tube is a large and heavy component of the landing gear. We have carried out precise modeling and simulation analysis on it, and carried out reliability weight reduction optimization design. The above details the specific implementation details. For this purpose, we have summarized a reliability-based landing gear key structure weight reduction optimization design method process as follows: Figure 10 As shown. Similarly, this method can be applied to other key components of the landing gear, the rocker arm and the locking arm. As a relatively large component connected to the outer tube of the strut, it bears a larger load. Due to design errors and manufacturing generated during the design and manufacturing process, the possibility of structural strength failure increases. To this end, with the goal of reducing the weight (volume) of the landing gear rocker arm and locking arm, an optimized design is carried out while ensuring that the failure probability meets the requirements. Due to space limitations, only some key steps of the rocker arm and locking arm are shown here. Figure 11-14 The data results are shown in Tables 4 to 7. Similar to the outer cylinder of the pillar, other details are not repeated here.

[0110] Table 4 Initial values ​​and distribution types of design variables of rocker arm

[0111] random variable Distribution type mean Coefficient of variation Rotation angle θ(°) normal distribution 2.47 0.01 <![CDATA[Groove depth h1 (mm)]]> normal distribution 9.5 0.02 <![CDATA[Groove depth h2 (mm)]]> normal distribution 10.6 0.02 <![CDATA[Groove depth h3 (mm)]]> normal distribution 13.8 0.01

[0112] Table 5 Reliability optimization results of rocker arm

[0113] Design variables Before optimization After optimization Rotation angle θ(°) 2.47 2.3778 <![CDATA[Groove depth h1 (mm)]]> 9.5 9.2792 <![CDATA[Groove depth h2 (mm)]]> 10.6 10.3786 <![CDATA[Groove depth h3 (mm)]]> 13.8 13.8243 Failure probability 3e-6 4.193e-4 <![CDATA[Total volume V (mm 3 )]]> 1.5397e6 1.4661e6

[0114] Table 6 Initial values ​​of design variables of the locking arm

[0115] random variable Distribution type mean Coefficient of variation <![CDATA[Left platform height h1 (mm)]]> normal distribution 190 0.003 <![CDATA[Height h2 (mm) of the right platform]]> normal distribution 60 0.01 <![CDATA[Thickness h3 (mm) of the middle connection]]> normal distribution 40 0.01 <![CDATA[Hole depth h4 (mm)]]> normal distribution 0 0.05

[0116] Table 7 Reliability optimization results of locking arm

[0117] Design variables Before optimization After optimization <![CDATA[Left platform height h1 (mm)]]> 190 192 <![CDATA[Height h2 (mm) of the right platform]]> 60 57 <![CDATA[Thickness h3 (mm) of the middle connection]]> 40 32 <![CDATA[Hole depth h4 (mm)]]> 0 20 Failure probability 0.00015 0.00006 <![CDATA[Total volume V (mm 3 )]]> 1.0326e7 0.97173e7

[0118] Figure 15A comparison chart of the weight reduction optimization results of key landing gear components was presented. After optimization, the strut outer tube was reduced by 4.60%, the rocker arm by 4.06%, and the locking arm by 5.89%. Through reliability-based weight reduction optimization of the landing gear strut outer tube, rocker arm, and locking arm, the overall weight of the landing gear was significantly reduced while ensuring its reliability and strength in practical applications, providing important technical support for the high-performance design of modern aircraft.

Claims

1. A reliability-based weight reduction optimization design method for key landing gear structures, characterized in that: The steps include: Step 1: Accurate modeling and simulation of the pillar outer cylinder based on ANSYS; Utilize ANSYS to accurately model and simulate key landing gear components to ensure model accuracy. Then, program APDL command streams to implement geometric parametric modeling of key components, facilitating subsequent optimization design. Step 2: Reliability weight reduction optimization design; Based on the simulation model of the landing gear strut outer tube, the APDL command stream is used to execute the parametric simulation process, and a structural reliability optimization design model for the strut outer tube is established to achieve weight reduction.

2. The reliability-based weight reduction optimization design method for key landing gear structures according to claim 1, characterized in that: The step 1 is specifically as follows: Step 1-1: Prepare for modeling; Select the coordinate system and unify the units; the global coordinate system in the modeling process is directly consistent with the coordinate system of the CATIA software; set a unified unit system, where the model length unit is mm, the stress unit is MPa, and the density unit is t / mm 3 ; Step 1-2: Establish finite element model; In CATIA software, unnecessary parts of the model were simplified, and the landing gear strut outer tube, which was the object for analysis and research, was separated; The model consists of two parts: the main body of the pillar outer tube and the lug connection parts on the pillar outer tube. First, create the main body of the pillar outer tube, or the cylinder, and then model the lugs on the pillar outer tube. Use straight surfaces instead of curved surfaces to shear the upper end of the outer tube, and simplify the large hole at the upper end of the outer tube. Use Boolean operations to modify the preliminarily built model; after the model is built, use the working plane to divide the line surface of the model into grids; Steps 1-3: Set loads and boundary conditions; After meshing is complete, loads and boundary conditions are applied to solve for the maximum stress. The lug at the upper end of the entire strut outer tube is connected to the landing gear upper joint, and the lug at the lower end is connected to the landing gear anti-torsion arm. The load on the entire pillar outer tube structure is measured by ADAMS, and then the force at the point of action is converted to the entire action plane; Steps 1-4: Finite element analysis results; The maximum stress σ obtained by finite element analysis of the outer tube of the pillar max The dangerous points with maximum stress are the restraining ends of the upper and lower ears and the connection between the ears and the transmission cylinder near the pressure application point.

3. The reliability-based weight reduction optimization design method for key landing gear structures according to claim 2, characterized in that: The step 2 is specifically as follows: Step 2-1: Take the average of the thickness of the outer tube wall of the pillar and the thickness of the lugs at different positions on the outer tube of the pillar is the design variable; when the maximum stress in the pillar outer tube during operation reaches the maximum allowable stress, it is determined that the pillar outer tube has failed. Therefore, the following function is established: g(H)=g(h,h2,…,h4)=σ max (h,h2,…,h4)-σ0 (1) Among them, σ max (h, h2,…, h4) is the maximum stress of the landing gear strut outer tube structure obtained by ANSYS finite element analysis, which is related to the input variables, and σ0 is the maximum allowable stress; Yield stress σ of the pillar outer tube structural material b The pressure is 1580 MPa, and the safety factor n is 1.88, then the maximum allowable stress σ0 is: σ0=σ b / n=838Mpa (2) Step 2-2: Taking the minimum weight of the entire structure as the reliability optimization design goal, establish the reliability optimization design model of the landing gear strut outer tube structure as shown below: Where, the target failure probability of the pillar outer tube structure is P f =5×10 -4 ; V(μ) represents the optimization objective function, that is, the weight function of the structure, g(μ) represents the functional function defined based on strength failure, and P{g(μ)≤0} represents the failure probability of the functional function; Step 2-3: Based on the adaptive Kriging surrogate model, the reliability optimization design method is used to solve the problem. The steps are as follows: 1) Initialization setting, let k = 0, Indicates the design point of the current iteration; 2) Generate sample pool S, use Latin square sampling LHS, through the initial design point and the probability density function of its random variable to generate N samples (X1, X2, ..., X N ); 3) Generate N initial Initial samples And calculate the output response values ​​of the functional functions corresponding to the m constraints respectively 4) Using the generated initial training samples and output response values, construct i initial Kriging models 5) Estimate the response corresponding to the samples in the sample pool S through the constructed initial Kriging model, and thus obtain the predicted values ​​corresponding to different constraints and standard deviation 6) Pass Calculate the learning function U of the sample pool S i (X j )(i=1,2,...m,j=1,2,...,N), then by Find the updated sample points and add them to the i Kriging models until the convergence criterion minU i (X j )≥2 satisfied; 7) Estimate the failure probability corresponding to each constraint using the currently updated Kriging model; 8) After updating the probability constraint calculation results, perform optimization design iteration to obtain the iterative design point 9) Determine whether it converges; if the optimized convergence conditions are met, the optimal design point is output Otherwise, add 1 to k and return to step 7).

4. The reliability-based weight reduction optimization design method for key landing gear structures according to claim 3 is characterized in that: In the steps 1-2, the units of the model are SOLID186 type, and tetrahedral 6-node units are uniformly used when dividing the finite element mesh. The finite element model is divided into a total of 60,372 units and 117,568 unit nodes.

5. The reliability-based weight reduction optimization design method for key landing gear structures according to claim 4, characterized in that: The outer layer of the reliability optimization design method is a sequence decoupling algorithm, and the inner layer is an AK-MCS algorithm.

6. A computer program, characterized in that The computer program enables a computer to execute the method according to any one of claims 1 to 5.

7. An electronic device, characterized in that: include: processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

9. A chip, characterized in that: include: A processor, configured to call and run a computer program from a memory, so that a device equipped with the chip executes the method according to any one of claims 1 to 5.

10. A computer program product, characterized in that The computer program product comprises a computer storage medium storing a computer program, wherein the computer program comprises instructions executable by at least one processor, and when the instructions are executed by the at least one processor, the method according to any one of claims 1 to 5 is implemented.

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