Landing gear structure topology optimization method and system with non-proportional load fatigue constraint
Patent Information
- Application Number
- CN202611039096.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-14
- Publication Date
- 2026-08-18
AI Technical Summary
现有的拓扑优化方法多针对恒定载荷或等效静载荷，难以准确表征非比例载荷下的疲劳损伤演化规律
本发明公开一种非比例载荷疲劳约束的起落架结构拓扑优化方法及系统，建立高信度刚柔耦合多体动力学模型，提取构件在完整起降过程中的时域非比例载荷谱。解决了非比例载荷下海量设计变量的疲劳灵敏度求解难题，实现了结构寿命导向的拓扑构型演化。采用本发明方法获得的设计结构，在显著降低构件重量的同时，有效强化了关键承载路径并提升了疲劳寿命，实现了结构轻量化与服役可靠性的协同优化。
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Figure CN122595478A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of aerospace structural design and optimization technology, and in particular to a method and system for topology optimization of landing gear structures under non-proportional load fatigue constraints. Background Technology
[0002] As a critical system supporting the airframe and transmitting loads, carrier-based aircraft landing gear endures extremely high-intensity and complex loads during catapult launch, landing impact, and ground taxiing. Traditional design methods based on static strength criteria (primarily ensuring the structure's load-bearing capacity under maximum ultimate load) often exhibit low material utilization and neglect of fatigue damage. Currently, static strength design struggles to achieve lightweighting, and components endure alternating cyclic loads during long-term service; considering only static strength may lead to fatigue failure at stress levels far below the yield strength. Furthermore, in actual service, the load amplitude on landing gear components (such as the upper torsion arm) varies independently over time in all spatial directions, exhibiting significant non-proportionality. Existing topology optimization methods primarily target constant loads or equivalent static loads, failing to accurately characterize the fatigue damage evolution under non-proportional loads. Summary of the Invention
[0003] To address the shortcomings of existing technologies, the present invention aims to provide a landing gear structure topology optimization method and system under non-proportional load fatigue constraints. By accurately simulating service conditions and establishing a fatigue damage sensitivity analysis model, the method aims to minimize the weight of landing gear components while meeting fatigue life requirements.
[0004] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a method for topology optimization of landing gear structures under non-proportional load fatigue constraints, comprising the following steps: A multi-stage dynamic evolution model was established for each stage of the catapult takeoff process, including a rigid-flexible coupled multibody dynamic model of the landing gear during the preparation stage, a landing gear dynamic model during the catapult takeoff run, and a mechanical model of the dual-cavity oil-gas buffer. The equivalent flow area of the oil hole at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer was iteratively searched and corrected using a parameter inversion correction strategy based on decoupling of multi-condition test data, so as to obtain the benchmark model for landing gear dynamic analysis. Based on the landing gear dynamics analysis benchmark model, the catapult takeoff process of the landing gear on the aircraft carrier deck is simulated to extract the non-proportional load spectrum in the whole time domain, and the dynamic evolution characteristics of the three-dimensional load on the time axis are obtained. The initial assessment of non-proportional fatigue life is performed using dynamic evolution characteristics to obtain the fatigue life constraint threshold. Based on the fatigue life constraint threshold, a fatigue performance-oriented topology optimization model is constructed and solved using non-proportional load characteristics.
[0005] Furthermore, the catapult launch process includes the preparation phase, the catapult rollout phase, and the catapult takeoff phase.
[0006] Furthermore, the specific steps for iteratively searching and correcting the equivalent flow area of the oil holes at different stroke positions in the mechanical model of the dual-cavity oil-gas buffer using a parameter inversion correction strategy based on decoupling from multi-condition test data are as follows: For the positive compression stroke of the buffer, the buffer power curve extracted from the drop test is used as the target benchmark to establish an optimization model with the objective function of minimizing the relative error between the simulated power and the test power. For the rebound reverse stroke of the buffer, an optimization model is established with the maximum extension speed curve in the extension test as the target benchmark, and the objective function is to minimize the relative speed error. Subsequently, using optimization algorithms, the equivalent flow area of the oil holes at different stroke positions of each optimization model is iteratively searched and corrected, thereby obtaining the damping variation law under real physical conditions and establishing a highly reliable landing gear dynamic analysis benchmark model.
[0007] Furthermore, the non-proportional load spectrum in the entire time domain is extracted using the extraction and mapping mechanism of the non-proportional time-domain load spectrum. Specifically, a local orthogonal coordinate system is first constructed and the three-dimensional load is decoupled. Then, the non-proportional multi-axis dynamic characteristics are captured. Finally, the quasi-static analysis of the dynamic load direction is mapped.
[0008] Furthermore, the specific steps for initial assessment of non-proportional fatigue life using dynamic evolution characteristics are as follows: The dynamic evolution characteristics are superimposed with the extracted time-varying load amplitude function in the time domain through linear mapping; After introducing equivalent stress, the stress amplitude and average stress corresponding to the stress cycle are extracted, and then corrected using a stress correction model. Fatigue life assessment is performed based on stress analysis results, and fatigue life constraint thresholds are set.
[0009] Furthermore, based on the fatigue life constraint threshold, the specific steps for constructing and solving a fatigue performance-oriented topology optimization model through non-proportional load characteristics are as follows: Based on the assembly and force transmission requirements, the upper torque arm structure area is divided, and a topology optimization mathematical model is constructed. A sensitivity expression for global fatigue damage to design variables is derived for non-proportional load characteristics. The relative density of each element in the design domain is continuously updated through the MMA algorithm using the adjoint vectors of each load direction and the sensitivity information obtained from the solution, and finally a lightweight topology configuration that meets the fatigue life requirements is output.
[0010] A second aspect of the present invention provides a landing gear structure topology optimization system under non-proportional load fatigue constraints, comprising: The dynamic modeling and correction module is configured to build multi-stage dynamic evolution models for each stage of the catapult takeoff process, including the rigid-flexible coupled multibody dynamic model of the landing gear in the preparation stage, the landing gear dynamic model in the catapult takeoff process, and the mechanical model of the dual-cavity oil-gas buffer. It also uses a parameter inversion correction strategy based on decoupling from multi-condition test data to iteratively search and correct the equivalent flow area of the oil holes at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer, thus obtaining the benchmark model for landing gear dynamic analysis. The load feature extraction module is configured to extract the non-proportional load spectrum in the entire time domain based on the landing gear dynamic analysis benchmark model to simulate the catapult takeoff process of the landing gear on the aircraft carrier deck and obtain the dynamic evolution characteristics of the three-dimensional load on the time axis. The fatigue life prediction parameter setting module is configured to use dynamic evolution characteristics to perform an initial assessment of non-proportional fatigue life and obtain a fatigue life constraint threshold. The topology optimization implementation module is configured to construct and solve a fatigue performance-oriented topology optimization model based on fatigue life constraint thresholds and non-proportional load characteristics.
[0011] A third aspect of the present invention provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and to execute steps in the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in the first aspect of the present invention.
[0012] A fourth aspect of the present invention provides a computer device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in the first aspect of the present invention.
[0013] A fifth aspect of the present invention provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform steps in the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in the first aspect of the present invention.
[0014] The above one or more technical solutions have the following beneficial effects: This invention discloses a method and system for topology optimization of landing gear structures under fatigue constraints with non-proportional loads. A high-confidence rigid-flexible coupled multibody dynamics model is established to extract the time-domain non-proportional load spectrum of the components during a complete takeoff and landing process. This solves the problem of fatigue sensitivity calculation for massive design variables under non-proportional loads and achieves life-oriented topology evolution. The design structure obtained using this method significantly reduces component weight while effectively strengthening critical load-bearing paths and improving fatigue life, achieving synergistic optimization of structural lightweighting and service reliability.
[0015] This invention presents a fatigue damage constraint calculation method based on quasi-static finite element method and associated sensitivity analysis, which can accurately characterize the damage evolution law of landing gear under complex non-proportional time-varying loads and effectively solve the problem of difficulty in solving fatigue sensitivity under massive design variables. It has the characteristics of high computational efficiency and robust convergence, and can be seamlessly integrated into the topology optimization model of continuum structure.
[0016] The design structure obtained using the method established in this invention achieves significant weight reduction while effectively strengthening critical load-bearing paths and reducing cumulative damage in local areas. This ensures that the fatigue life of the components fully meets or even exceeds the initial design requirements during a complete takeoff and landing cycle, realizing a synergistic design of lightweight structure and long service life, which is of great significance for improving the sortie efficiency and structural safety of carrier-based aircraft.
[0017] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1A schematic diagram of the various stages of an aircraft catapult launch; Figure 2 This is a schematic diagram of the catapult launch model of the front landing gear in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the landing gear skid travel time curve in the ejection condition according to Embodiment 1 of the present invention; Figure 4 This is a schematic diagram illustrating the establishment of the local coordinate system of the upper torque arm in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the load in the X direction at the lower hinge point Marker 2 of the torsion arm under the ejection condition in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the Y-direction load at the lower hinge point Marker 2 of the torsion arm in the ejection condition according to Embodiment 1 of the present invention; Figure 7 This is a schematic diagram of the load in the Z direction at the lower hinge point Marker 2 of the torsion arm under the ejection condition in Embodiment 1 of the present invention; Figure 8 This is a schematic diagram of the optimization target iteration curve in Embodiment 1 of the present invention; Figure 9 This is a schematic diagram of the optimization results in Embodiment 1 of the present invention; Figure 10 This is a schematic diagram of the geometric reconstruction model in Embodiment 1 of the present invention. Detailed Implementation
[0020] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0021] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0022] Example 1: Embodiment 1 of the present invention provides a landing gear structure topology optimization method under non-proportional load fatigue constraints, comprising the following steps: S1: Construct a multi-stage dynamic evolution model for each stage of the catapult takeoff process, and use a parameter inversion correction strategy based on decoupling of multi-condition test data to iteratively search and correct the equivalent flow area of the oil hole at different stroke positions of the dual-cavity oil-gas buffer mechanical model to obtain the landing gear dynamic analysis benchmark model.
[0023] S1.1: Construct a multi-stage dynamic evolution model for each stage of the catapult takeoff process.
[0024] In one specific implementation, such as Figure 1 As shown, the catapult launch process based on the constraint state is divided into several stages, including the preparation stage, the catapult roll-off stage, and the launch-off stage.
[0025] In the preparation phase, the catapult stick and the traction stick are connected to the nose landing gear, and the catapult system is in takeoff preparation mode. During the catapult roll-off phase, catapult force is applied, and the engine provides thrust. When the load on the traction stick reaches a set threshold, the connection between the traction stick and the landing gear is released, and the carrier-based aircraft accelerates and rolls along the deck under the traction of the catapult trolley. In the takeoff phase, after the catapult trolley has rolled to a predetermined distance, the connection between the catapult stick and the nose landing gear is broken, and the aircraft completes its takeoff and leaves the ship under the influence of inertia and lift. To accurately characterize the multi-stage evolution characteristics under the above complex conditions, this embodiment constructs a multi-stage dynamic evolution model of nose landing gear catapult takeoff. This model encompasses the rigid-flexible coupled multibody dynamics model of the landing gear during the preparation phase, the landing gear dynamics model during the catapult roll-off process, and the mechanical model of the dual-cavity oil-gas buffer, achieving accurate extraction of the sequential forces during the catapult takeoff phase.
[0026] First, considering the coupled influence of the flexible deformation of the landing gear structure on the system's dynamic response under complex operating conditions, key load-bearing components such as the upper torsion arm and outer cylinder are discretized and made flexible using the finite element method. Based on the Lagrange equations, the dynamic differential equations of the system's flexible body are established to create a rigid-flexible coupled multibody dynamic model of the nose landing gear.
[0027] (1).
[0028] Where, ξ, and Let be the global coordinates of the elastic body and its time-domain derivative; M is the mass matrix of the elastic body; Let be the time-domain derivative of the mass matrix of the elastic body; Let be the time-domain partial derivative of the elastic body mass matrix with respect to the global coordinates; K is the global stiffness matrix; ψ is gravity; D is the modal damping matrix; ψ is the algebraic constraint equation; λ is the Lagrange multiplier with respect to the constraints; Q is the total force.
[0029] Meanwhile, when establishing the landing gear dynamics model for the catapult launch process, special consideration was given to the unique multi-constraint dynamic switching mechanism and variable damping hydrodynamic effects of the catapult takeoff phase: during the preparation and acceleration phases, the model incorporates catapult traction force. With restraint The dynamic logic discrimination mechanism simulates the evolution of constraint states under real working conditions by setting virtual force / displacement sensors: during the takeoff preparation phase, the model applies boundary constraints through the traction rod; when the traction force... As the ejection force increases and reaches the preset release threshold, the model automatically triggers the constraint release mechanism, cuts off the restraint connection, and allows the landing gear system to enter the free acceleration and taxiing phase.
[0030] A mechanical model of a dual-chamber oil-air damper is established, where the axial load is composed of the superposition of air spring force, hydraulic damping force, and structural restraint force. Specifically, due to the influence of the variable cross-section hydraulic needle on the hydraulic damping force, a factor varying with the compression stroke is introduced into its physical equations. Nonlinearly varying equivalent flow area parameters of main / return oil holes ( and (Among them, the equivalent flow area of the main oil hole) This represents the actual area of the "annular gap" left between the oil orifice and the needle valve as the aircraft plunges downwards (compression stroke). The equivalent flow area of the return oil orifice... This represents the area of the gap where oil flows back to the original chamber when the aircraft is pushed upward by high-pressure gas (rebound / extend reverse stroke).
[0031] S1.2: The equivalent flow area of the oil hole at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer is iteratively searched and corrected by using a parameter inversion correction strategy based on decoupling of multi-condition test data.
[0032] Due to actual manufacturing and assembly errors, the equivalent flow area of the variable cross-section oil hole ( , Since these parameters are difficult to determine precisely through theoretical formulas, this embodiment proposes a parameter inversion correction strategy based on decoupling from multi-condition test data. Specifically, it includes the following steps: S1.2.1: For the positive compression stroke of the buffer, the buffer power curve extracted from the drop test is used as the target benchmark to establish an optimization model with the objective function of minimizing the relative error between the simulated power and the test power.
[0033] S1.2.2: For the rebound reverse stroke of the buffer, an optimization model is established with the maximum extension speed curve in the extension test (simulating the instant of ejection release) as the target benchmark, and the objective function is to minimize the relative speed error.
[0034] S1.2.3: Subsequently, using optimization algorithms, the equivalent flow area of the oil holes at different stroke positions of each optimization model is iteratively searched and corrected, thereby obtaining the damping variation law under real physical conditions and establishing a highly reliable landing gear dynamic analysis benchmark model.
[0035] Specifically, this embodiment employs a multi-island genetic algorithm (Multi-Island GA) to optimize the calculations with the goal of minimizing the relative error between simulation results and experimental data. During the correction of the equivalent flow area of the oil holes in the reverse stroke, considering the need to simultaneously consider multiple operating conditions, a non-dominated sorting genetic algorithm II (NSGA-II) is used for multi-objective optimization, with the goal of minimizing the relative error between the three sets of simulation results and corresponding experimental data, thereby achieving comprehensive parameter optimization. The equivalent flow area of the oil holes at different stroke positions in the above model is iteratively searched and corrected to obtain the damping variation law under real physical conditions, establishing a highly reliable landing gear dynamics analysis benchmark model.
[0036] Final model as follows Figure 2 As shown, a drop-shock condition with an equivalent mass of 6000 kg and a maximum sinking velocity of 7 m / s was adopted, in which key load-bearing components such as the upper torsion arm and the outer cylinder were made of A-100 steel. Subsequently, using the ISIGHT platform, with the goal of minimizing the simulation and experimental errors of the drop-shock power curve and the sudden velocity curve, the equivalent flow area of the variable oil hole structure was corrected, and finally the dynamic model was constructed.
[0037] S2: Based on the landing gear dynamics analysis benchmark model, the non-proportional load spectrum in the entire time domain is extracted from the catapult takeoff process of the landing gear on the aircraft carrier deck during catapult takeoff. The dynamic evolution characteristics of the three-dimensional load on the time axis are obtained.
[0038] In one specific implementation, based on the completion of the multi-stage dynamic evolution model, and addressing the inherent defects in the load application method of traditional landing gear static topology optimization, a non-proportional time-domain load spectrum extraction and mapping mechanism is used to extract the full-time-domain non-proportional load spectrum. This mapping mechanism avoids the enormous computational burden of directly solving transient nonlinear dynamics, while perfectly preserving the true time-domain characteristics of the non-proportional load, laying a data foundation for subsequent calculations of local transient stress history and full-life-cycle fatigue cumulative damage.
[0039] Specifically, the following steps are included: S2.1: First, construct a local orthogonal coordinate system and decouple the three-dimensional loads.
[0040] Specifically, a local orthogonal coordinate system is established for key load-bearing components (such as the upper and lower hinge points of the upper torsion arm), for example... Figure 4 As shown, using virtual force sensors in a multibody dynamics model, the system tracks and records in real time the change in spatial force of the landing gear node under transient conditions such as catapult takeoff preparation, acceleration run, sudden extension from the ship, and landing impact. This process is then decoupled into a sequence of continuous loads along the three local coordinate directions of X, Y, and Z.
[0041] S2.2: Secondly, capture non-proportional multi-axis dynamic features.
[0042] Specifically, unlike the simplified static treatment in traditional designs that only extracts the ultimate peak load and scales the loads in each direction by a fixed ratio, the load spectrum extracted in this embodiment shows that the load amplitudes in the X, Y, and Z directions have independent and significant dynamic evolution characteristics on the time axis (i.e., non-proportional multi-axis loading effect). When the landing gear experiences landing impact or catapult launch, the forces in each direction do not reach their peak values synchronously.
[0043] In this embodiment, a local orthogonal coordinate system is established in the multibody dynamics model of the landing gear, with the lower hinge point of the upper torsion arm as the origin. During the simulation of full service conditions (catapult launch and landing impact), virtual force sensors are set at the corresponding kinematic pairs in the model to continuously read the dynamic contact reaction force of the node in the entire simulation time domain at a fixed time step. Finally, the spatial reaction force is projected onto the local coordinate system to extract the time-series load data of the node along the X, Y, and Z directions, which is defined as a three-dimensional time-varying load amplitude function. Where q=1,2,3 represent the X, Y, and Z directions, respectively. Unlike the simplified static treatment in traditional designs that only extracts the ultimate peak load and scales the loads in each direction by a fixed ratio, the load spectrum extracted in this embodiment shows that the load amplitudes in the X, Y, and Z directions have independent and significant dynamic evolution characteristics on the time axis (i.e., non-proportional multi-axis loading effect). During landing impact or catapult launch, the forces in each direction do not reach their peak values synchronously. This embodiment utilizes the non-proportional load spectrum (i.e., the i.e., the variable load amplitude function) extracted across the entire time domain as described above. It retains the true load phase difference, thus enabling precise capture of the differential and multiaxial coupled fatigue damage caused by load fluctuations to the structure under complex alternating stress conditions; S2.3: Quasi-static analysis of the final mapping of dynamic load direction.
[0044] Specifically, the extracted triaxial non-proportional time-varying load amplitude sequence is used as a discrete load step input into the finite element simulation environment. First, in the upper torsion arm finite element model, a unit load of 1N is independently applied along the three local coordinate directions of X, Y, and Z. Through static solution, the stress response results of each discrete element under the unit load in the corresponding direction are extracted and defined as the quasi-static element stress field vector. .
[0045] Subsequently, based on the quasi-static non-proportional superposition principle, the quasi-static element stress field vector obtained above is... The time-varying load amplitude function in the corresponding direction extracted in step S2.2 above. The reconstructed transient stress vector is obtained by performing time-domain mapping and linear superposition. .
[0046] Based on the revised model, the catapult launch process during catapult takeoff on an aircraft carrier deck is simulated, such as... Figure 3 As shown. For the catapult launch scenario, the catapult roll distance is set to 92.5m, and at the end of the roll, the horizontal velocity of the fuselage's center of gravity reaches 81.713m / s. For the landing impact scenario, the initial horizontal velocity is 66.7m / s, the sinking velocity is 7m / s, and the equivalent mass is 6000kg. The tires experience a severe impact upon first contact with the deck, with the vertical load on the tires reaching a peak of 463.34kN at t=0.798s. Based on the above specific parameters, a local coordinate system is established at the upper torsion arm hinge point using the method described in this step, and the triaxial force load spectrum is extracted. (See figure...) Figure 5 , Figure 6 and Figure 7 As shown, the extracted triaxial loads exhibit independent and significant dynamic evolution characteristics on the time axis, verifying the effectiveness of this method in capturing non-proportional load combination relationships.
[0047] S3: Utilize dynamic evolution characteristics to perform an initial assessment of non-proportional fatigue life and obtain the fatigue life constraint threshold.
[0048] In one specific implementation, traditional static strength-based assessment methods cannot reflect the damage accumulation process under real alternating stress, while directly performing full-time-domain nonlinear transient finite element fatigue analysis faces enormous and unacceptable computational costs. This embodiment establishes a fatigue assessment algorithm that balances computational efficiency with the preservation of non-proportional features. The specific steps are as follows: S3.1: Utilize the dynamic evolution characteristics and the extracted time-varying load amplitude function to perform time-domain linear mapping superposition.
[0049] Specifically, the stress field vectors of the quasi-static element under unit load in the X, Y, and Z axes are obtained. , and the extracted time-varying load amplitude function Perform time-domain linear mapping superposition.
[0050] The transient stress vector of any element at time t can be quickly reconstructed as: (2).
[0051] in, This is the reconstructed transient stress vector.
[0052] S3.2: After introducing equivalent stress, extract the stress amplitude and average stress corresponding to the stress cycle, and then correct them using the stress correction model.
[0053] Specifically, since the conventional Mises equivalent stress is always positive, it is impossible to distinguish between the local tension and compression states of the structure. To accurately perform fatigue counting, the equivalent stress was reconstructed with a "signed" value, introducing a signed equivalent stress. To capture the specific contribution of stress to fatigue life: (3).
[0054] In the formula, This represents the Mises equivalent stress at time t in element . The principal stresses are specifically identified as the first principal stress (maximum principal stress), the second principal stress (intermediate principal stress), and the third principal stress (minimum principal stress) in the local area of the element. Subsequently, the four-point rainflow counting method is used to analyze the signed equivalent stresses. The stress time history is used for cyclic identification, and the stress amplitude corresponding to the j-th stress cycle is extracted. With average stress .
[0055] Considering the significant non-zero mean characteristic of the non-proportional alternating load on the landing gear, and the fact that mean stress has a great influence on fatigue life, the Goodman mean stress correction model is selected to equate the non-zero mean stress to the zero mean stress amplitude under symmetrical cyclic loading. : (4).
[0056] S3.3: Based on the stress analysis results, assess fatigue life and set fatigue life constraint thresholds.
[0057] Specifically, before optimization, a fatigue life assessment was conducted on the original structure, and A-100 steel was selected, with a tensile strength of... The equivalent zero-mean stress amplitude obtained in step S3.2 above As the final input of the stress analysis, the fatigue life corresponding to the j-th stress cycle is calculated by substituting it into the standard SN fatigue life curve of the material. Then, based on the Minor linear cumulative damage criterion, the total fatigue cumulative damage of the element was calculated. : (5).
[0058] In the formula, This represents the actual number of cycles corresponding to the stress level. The single-cycle life is obtained from the SN fatigue life curve.
[0059] The above algorithm was used to perform a full-domain scan calculation on the original upper torsion arm structure. The results show that, under the synthesized non-proportional landing load spectrum, the extreme fatigue damage region of the original upper torsion arm appears in a locally narrow transition zone (i.e., a fatigue weak point) near the lower hinge point. Its maximum cumulative fatigue damage... The corresponding minimum fatigue life This is the second iteration. Using these parameters as a baseline, fatigue life constraint thresholds are set in subsequent lightweight topology optimization designs. This is to ensure that the fatigue life of the structure after topology optimization and weight reduction is not lower than that of the original structure.
[0060] S4: Based on the fatigue life constraint threshold, a fatigue performance-oriented topology optimization model is constructed and solved through non-proportional load characteristics.
[0061] S4.1: Divide the upper torsion arm structure region according to assembly and force transmission requirements, and construct a topology optimization mathematical model.
[0062] Specifically, based on assembly and force transmission requirements, the upper torsion arm structure is divided into a non-design domain and a design domain. The non-design domain includes areas such as the connecting hinge points, where the geometry remains unchanged to ensure assembly properties. The design domain includes the central main load-bearing area, serving as a space for material density iteration. A function is constructed with the overall structural volume V as the objective to satisfy the global fatigue cumulative damage index. Mathematical Model for Variable Density Method (SIMP) Topology Optimization with Constraints : .
[0063] in, This is the fatigue life constraint threshold. The elastic modulus of the material, This is the set minimum value, typically 10⁻⁶. .
[0064] S4.2: Derive the sensitivity expression of global fatigue damage to design variables for non-proportional load characteristics.
[0065] Specifically, to avoid numerical singularities and enormous computational costs caused by local fatigue damage in thousands of discrete elements during optimization calculations, a P-norm condensation function is introduced. This consolidates the local fatigue damage of each unit into a unique global cumulative fatigue damage index. Subsequently, considering the characteristics of non-proportional loads, the adjoint method was used to construct the Lagrangian function: .
[0066] in, This is a global fatigue cumulative damage index based on P-norm aggregation. Let F be the adjoint vector corresponding to the q-th load case, i.e., the X, Y, and Z directions, where K is the overall stiffness matrix, U is the nodal displacement vector, and F is the external load vector.
[0067] Derive the effect of global fatigue damage on design variables The sensitivity expression for (unit relative density): .
[0068] This enables the optimization algorithm to accurately identify fatigue-weak areas under non-proportional cyclic loads.
[0069] S4.3: The relative density of each element in the design domain is continuously updated through the MMA algorithm using the combined load direction vectors and sensitivity information obtained from the solution, and finally a lightweight topology configuration that meets the fatigue life requirements is output.
[0070] Specifically, the adjoint vectors and sensitivity information of each load direction obtained from S4.2 are input into the Moving Asymptote Method (MMA) optimizer. The MMA algorithm iteratively updates the relative density of each element within the design domain, such as... Figure 8 As shown, this continues until the rate of change of the objective function (volume) satisfies the convergence condition.
[0071] The final output is a lightweight topology that meets fatigue life requirements, such as... Figure 9 and Figure 10 As shown, geometric reconstruction is carried out based on the manufacturing process to achieve a synergistic improvement in the weight reduction and fatigue resistance of the upper torsion arm.
[0072] Example 2: Embodiment 2 of the present invention provides a landing gear structure topology optimization system with non-proportional load fatigue constraints, comprising: The dynamic modeling and correction module is configured to build multi-stage dynamic evolution models for each stage of the catapult takeoff process, including the rigid-flexible coupled multibody dynamic model of the landing gear in the preparation stage, the landing gear dynamic model in the catapult takeoff process, and the mechanical model of the dual-cavity oil-gas buffer. It also uses a parameter inversion correction strategy based on decoupling from multi-condition test data to iteratively search and correct the equivalent flow area of the oil holes at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer, thus obtaining the benchmark model for landing gear dynamic analysis. The load feature extraction module is configured to extract the non-proportional load spectrum in the entire time domain based on the landing gear dynamic analysis benchmark model to simulate the catapult takeoff process of the landing gear on the aircraft carrier deck and obtain the dynamic evolution characteristics of the three-dimensional load on the time axis. The fatigue life prediction parameter setting module is configured to use dynamic evolution characteristics to perform an initial assessment of non-proportional fatigue life and obtain a fatigue life constraint threshold. The topology optimization implementation module is configured to construct and solve a fatigue performance-oriented topology optimization model based on fatigue life constraint thresholds and non-proportional load characteristics.
[0073] Example 3: Embodiment 3 of the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor and executing the steps in the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in Embodiment 1 of the present invention.
[0074] Example 4: Embodiment 4 of the present invention provides a computer device, the device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the steps in the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in Embodiment 1 of the present invention.
[0075] Example 5: Embodiment 5 of the present invention provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in Embodiment 1 of the present invention.
[0076] The steps and methods involved in Examples 2, 3, 4 and 5 above correspond to those in Example 1. For specific implementation methods, please refer to the relevant description section of Example 1.
[0077] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0078] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.
[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A topology optimization method for landing gear structures under non-proportional load fatigue constraints, characterized in that, Includes the following steps: A multi-stage dynamic evolution model was established for each stage of the catapult takeoff process, including a rigid-flexible coupled multibody dynamic model of the landing gear during the preparation stage, a landing gear dynamic model during the catapult takeoff run, and a mechanical model of the dual-cavity oil-gas buffer. The equivalent flow area of the oil holes at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer was iteratively searched and corrected using a parameter inversion correction strategy based on decoupling of multi-condition test data, so as to obtain the benchmark model for landing gear dynamic analysis. Based on the landing gear dynamics analysis benchmark model, the catapult takeoff process of the landing gear on the aircraft carrier deck is simulated to extract the non-proportional load spectrum in the whole time domain, and the dynamic evolution characteristics of the three-dimensional load on the time axis are obtained. The initial assessment of non-proportional fatigue life is performed using dynamic evolution characteristics to obtain the fatigue life constraint threshold. Based on the fatigue life constraint threshold, a fatigue performance-oriented topology optimization model is constructed and solved using non-proportional load characteristics.
2. The landing gear structure topology optimization method under non-proportional load fatigue constraints as described in claim 1, characterized in that, The catapult launch process consists of several phases, including the preparation phase, the catapult roll-off phase, and the catapult takeoff phase.
3. The landing gear structure topology optimization method under non-proportional load fatigue constraints as described in claim 1, characterized in that, The specific steps for iteratively searching and correcting the equivalent flow area of the oil hole at different stroke positions in the mechanical model of the dual-cavity oil-gas buffer using a parameter inversion correction strategy based on decoupling from multi-condition test data are as follows: For the positive compression stroke of the buffer, the buffer power curve extracted from the drop test is used as the target benchmark to establish an optimization model with the objective function of minimizing the relative error between the simulated power and the test power. For the rebound reverse stroke of the buffer, an optimization model is established with the maximum extension speed curve in the extension test as the target benchmark, and the objective function is to minimize the relative speed error. Subsequently, using optimization algorithms, the equivalent flow area of the oil holes at different stroke positions of each optimization model is iteratively searched and corrected, thereby obtaining the damping variation law under real physical conditions and establishing a highly reliable landing gear dynamic analysis benchmark model.
4. The landing gear structure topology optimization method under non-proportional load fatigue constraints as described in claim 1, characterized in that, The non-proportional load spectrum in the entire time domain is extracted using the extraction and mapping mechanism of non-proportional time-domain load spectrum. Specifically, a local orthogonal coordinate system is first constructed and three-dimensional load decoupling is performed. Then, the non-proportional multi-axis dynamic characteristics are captured. Finally, the quasi-static analysis of the dynamic load direction is mapped.
5. The landing gear structure topology optimization method under non-proportional load fatigue constraints as described in claim 1, characterized in that, The specific steps for initial assessment of non-proportional fatigue life using dynamic evolution characteristics are as follows: The dynamic evolution characteristics are superimposed with the extracted time-varying load amplitude function in the time domain through linear mapping; After introducing equivalent stress, the stress amplitude and average stress corresponding to the stress cycle are extracted, and then corrected using a stress correction model. Fatigue life assessment is performed based on stress analysis results, and fatigue life constraint thresholds are set.
6. The landing gear structure topology optimization method under non-proportional load fatigue constraints as described in claim 1, characterized in that, Based on the fatigue life constraint threshold, the specific steps for constructing and solving a fatigue performance-oriented topology optimization model using non-proportional load characteristics are as follows: Based on the assembly and force transmission requirements, the upper torque arm structure area is divided, and a topology optimization mathematical model is constructed. A sensitivity expression for global fatigue damage to design variables is derived for non-proportional load characteristics. The relative density of each element in the design domain is continuously updated through the MMA algorithm using the adjoint vectors of each load direction and the sensitivity information obtained from the solution, and finally a lightweight topology configuration that meets the fatigue life requirements is output.
7. A landing gear structure topology optimization system under non-proportional load fatigue constraints, characterized in that, include: The dynamic modeling and correction module is configured to build multi-stage dynamic evolution models for each stage of the catapult takeoff process, including the rigid-flexible coupled multibody dynamic model of the landing gear in the preparation stage, the landing gear dynamic model in the catapult takeoff process, and the mechanical model of the dual-cavity oil-gas buffer. It also uses a parameter inversion correction strategy based on decoupling from multi-condition test data to iteratively search and correct the equivalent flow area of the oil holes at different stroke positions of the mechanical model of the dual-cavity oil-gas buffer, thus obtaining the benchmark model for landing gear dynamic analysis. The load feature extraction module is configured to extract the non-proportional load spectrum in the entire time domain based on the landing gear dynamic analysis benchmark model to simulate the catapult takeoff process of the landing gear on the aircraft carrier deck and obtain the dynamic evolution characteristics of the three-dimensional load on the time axis. The fatigue life prediction parameter setting module is configured to use dynamic evolution characteristics to perform an initial assessment of non-proportional fatigue life and obtain a fatigue life constraint threshold. The topology optimization implementation module is configured to construct and solve a fatigue performance-oriented topology optimization model based on fatigue life constraint thresholds and non-proportional load characteristics.
8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed by the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in any one of claims 1-6.
10. A computer device, characterized in that, include: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the landing gear structure topology optimization method with non-proportional load fatigue constraints as described in any one of claims 1-6.