Search Results (103)

The aircraft nose-wheel steering system serves as a critical component for ensuring ground taxiing safety and maneuvering efficiency. However, its dynamic control stability faces significant challenges under complex operational conditions. Existing research predominantly focuses on single-discipline modeling, with insufficient in-depth analysis of the coupling effects between hydraulic system dynamics and mechanical dynamics. Traditional PID controllers exhibit limitations in scenarios involving nonlinear time-varying conditions caused by normal load fluctuations of the landing gear buffer strut during high-speed landing phases, including increased control overshoot and inadequate adaptability to abrupt load variations. These issues severely compromise the stability of high-speed deviation correction and overall aircraft safety. To address these challenges, this study constructs a digital twin model based on real aircraft data and innovatively implements multidisciplinary co-simulation via Simcenter 3D, AMESim 2021.1, and MATLAB R2020a. A fuzzy adaptive PID controller is specifically designed to achieve adaptive adjustment of control parameters. Comparative analysis through co-simulation demonstrates that the proposed mechanical–electrical–hydraulic collaborative control strategy significantly reduces response delay, effectively minimizes control overshoot, and decreases hydraulic pressure-fluctuation amplitude by over 85.2%. This work provides a novel methodology for optimizing steering stability under nonlinear interference scenarios, offering substantial engineering applicability and promotion value. Full article

Addressing the urgent need for lightweight and reusable energy-absorbing materials in aviation impact resistance, this study introduces an innovative multi-directional braided metamaterial design enabled by 4D printing technology. This approach overcomes the dual challenges of intricate manufacturing processes and the limited functionality inherent to traditional textile preforms. Six distinct braided structural units (types 1–6) were devised based on periodic trigonometric functions (Y = A sin(12πX)), and integrated with shape memory polylactic acid (SMP-PLA), thereby achieving a synergistic combination of topological architecture and adaptive response characteristics. Compression tests reveal that reducing strip density to 50–25% (as in types 1–3) markedly enhances energy absorption performance, achieving a maximum specific energy absorption of 3.3 J/g. Three-point bending tests further demonstrate that the yarn amplitude parameter A is inversely correlated with load-bearing capacity; for instance, the type 1 structure (A = 3) withstands a maximum load stress of 8 MPa, representing a 100% increase compared to the type 2 structure (A = 4.5). A multi-branch viscoelastic constitutive model elucidates the temperature-dependent stress relaxation behavior during the glass–rubber phase transition and clarifies the relaxation time conversion mechanism governed by the Williams–Landel–Ferry (WLF) and Arrhenius equations. Experimental results further confirm the shape memory effect, with the type 3 structure fully recovering its original shape within 3 s under thermal stimulation at 80 °C, thus addressing the non-reusability issue of conventional energy-absorbing structures. This work establishes a new paradigm for the design of impact-resistant aviation components, particularly in the context of anti-collision structures and reusable energy absorption systems for eVTOL aircraft. Future research should further investigate the regulation of multi-stimulus response behaviors and microstructural optimization to advance the engineering application of smart textile metamaterials in aviation protection systems. Full article

The shock absorbers in the landing gear absorb and dissipate a significant amount of kinetic energy generated from impacts during the landing and taxiing phases to ensure the stability and safety of the aircraft. The nitrogen–oil binary system is a commonly used energy absorption medium in these shock absorbers. Nevertheless, the interplay of interfacial mass transfer dynamics, microscopic dissolution behavior, and pressure drop in the aviation hydraulic oil–N₂ system under landing conditions necessitates further elucidation. Thus, we investigated the interfacial mass transfer characteristics of the oil–gas mixing process using molecular dynamics (MD) for analyzing the dissolution mechanism of N₂ in the aviation hydraulic oil system. The results show that as system pressure and temperature increase, the degree of oil–gas mixing intensifies. Under conditions of 373 K, 35 MPa and 433 K, 20 MPa, the diffusion coefficient, interfacial thickness, and system energy reach their maximum values. An increase in system pressure facilitates the occurrence of oil–gas mixing until the interface disappears at the minimum miscibility pressure (MMP), with the obtained MMP value being 107 MPa. Finally, the solubility of N₂ molecules in aviation hydraulic oil under different conditions was statistically analyzed, which is identified as the root cause of the pressure drop in the shock absorber’s gas chamber. This study innovatively applies molecular dynamics simulations to unveil, for the first time, the dissolution mechanism of N₂ in aviation hydraulic oil at the molecular scale, overcoming experimental limitations in observing extreme pressure–temperature conditions. This research elucidates the behavior of aviation hydraulic oil and N₂ under different thermodynamic conditions, making it easier to capture the patterns of phenomena that are difficult to observe in extreme environments. The research findings not only enhance the microscopic understanding of oil–gas mixing within the shock absorber but also provide valuable guidance for optimizing energy dissipation efficiency, improving damping characteristics, and enhancing safety in aircraft landing gear systems. Full article

This paper proposed a deep learning on-board health monitoring method for landing gear shock-absorbing systems based on dynamic responses during landing. A deep learning model is developed to conduct health monitoring for faults in shock absorbers. A certain general aviation aircraft is focused on in this paper, and a multi-body dynamic model of the nose landing gear is developed to simulate dynamic responses during landing under various health states and various landing conditions for developing a database for the proposed LDGNet. The simulated database is used to conduct model training and to test the performance of the proposed method. The feasibility and effectiveness of the proposed method are verified. Full article

This study investigates the ground reaction force of lever-spring landing gear (LSLG) equipped with compressible elastomer shock absorbers (ESA) during the landing process. First, a numerical dynamic model of the LSLG was developed in MATLAB/Simulink, revealing that runway roughness exerts a negligible influence on the ground reaction force during landing. The load characteristics established fundamental references for subsequent FEA-based structural design. Furthermore, an FEA model integrating the LSLG and the aircraft was developed with parameters calibrated for elastic units. The multibody dynamics simulation (MBDS) quantified the vertical ground reaction force and the structural stresses of LSLG, demonstrating two critical relationships: (1) the overload coefficient correlated with the sinking velocity yet exhibits no correlation with aircraft mass and (2) the peak of oscillating force attenuated faster with heavier landing weight at higher sinking velocities. A nonlinear multi-variables function was fitted to predict the maximum vertical ground reaction force. Subsequently, experimental validation via a landing gear drop test (LGDT) showed a maximum error of 8.39% between the results of the LGDT and the MBDS, confirming the accuracy of simulation and the fitting surface function for force prediction. The study further validates the feasibility and reliability of using the MBDS to model and study the LSLG with ESAs. Full article

The angular motion of aircraft landing gear retraction and extension must be accurate to ensure flight safety. Therefore, this study experimentally evaluated the motion accuracy of the landing gear retraction and extension processes associated with a specific aircraft to construct a reliability evaluation model for the landing gear angle. Considering the limitations of data acquisition in practical applications, the Bayesian method, which combines prior knowledge with experimentally measured data to reasonably estimate the variable parameters in the evaluation model, was applied to obtain more accurate parameter distributions. The constructed Bayesian-updated iterative model was shown to effectively expand upon limited test data to provide a novel approach for accurately evaluating landing gear angle reliability. The results of this study not only enrich the theoretical basis underpinning aircraft landing gear reliability assessment but also provide a valuable reference for technical support and decision-making in related engineering practice. Full article

The landing gear of an aircraft plays a crucial role in ensuring the safe takeoff and landing of the aircraft. Several defects in landing gear press molding may occur, including cross-section distortion, wall thickness thinning, and the springback phenomenon. These defects can significantly impact the quality of the molded product. This study employs a combination of finite element simulation and ML models to predict the springback angle of 7075 high-strength aluminum alloy pipes. The ABAQUS 2021 software was used to simulate the deformation behavior in the bending process based on the large deformation elastoplasticity theory. By utilizing the entropy method and analysis of variance (ANOVA), the significant factors affecting the forming quality were determined in the following order: pipe diameter > mandrel and pipe clearance > material properties > wall thickness > speed. The training set was augmented to improve the model generalization ability to build a multi-stage prediction model based on Lasso regression. The results show that the R² score of the ridge model reaches 0.9669, which is significantly better than other common machine learning methods. Finally, the model was applied to a real experimental dataset example through a transfer learning technique, showing obvious improvement compared with the control group. This study effectively predicts the springback angle of large-diameter thin-walled pipes and significantly improves the molding quality of bent fittings. Full article

The aircraft landing gear system is vital in ensuring the aircraft’s functional completeness and operational safety. The mechanical structures of the landing gear must withstand significant operational forces, including repeated high-intensity impact loads, throughout their service life. At the same time, they must resist environmental degradation, such as corrosion, temperature fluctuations, and humidity, to ensure structural integrity and long-term reliability. Under this premise, investigating material-related mechanical failures in the landing gear is of great significance for preventing landing gear failures and ensuring aviation safety. Compared to failure investigations, structural health monitoring (SHM) plays a more active role in failure prevention for aircraft landing gears. SHM technologies identify the precursors of potential failures and continuously monitor the operational or health conditions of landing gear structures, which facilitates condition-based maintenance. This paper reviews various landing gear material-related failure investigations. The review suggests a significant portion of these failures can be attributed to material fatigue, which is either induced by abnormal high-stress concentration or corrosion. This paper also reviews a series of load monitoring-based landing gear SHM studies. It is revealed that weight and balance measurement, hard landing detection, and structure load monitoring are the most typical monitoring activities in landing gears. An analytical discussion is also presented on the correlation between reviewed landing gear failures and SHM activities, a comparison of sensors, and the potential shift in load-based landing gear SHM in response to the transition of landing gear design philosophy from safe life to damage tolerance. Full article

This manuscript presents a new approach to describe aircraft landing gear systems equipped with magnetorheological (MR) dampers, integrating a reinforcement learning-based neural network control strategy. The main target of the proposed system is to improve the shock absorber efficiency in the touchdown phase, in addition to reducing the vibration due to rough ground in the taxing phase. The dynamic models of the aircraft landing system in the taxing phase with standard landing ground roughness, one-point touchdown, two-point touchdown, and third-point touchdown are built as the first step. After that, Q-learning-based reinforcement learning is developed. In order to verify the effectiveness of the controller, the co-simulations based on RECURDYN V8R4-MATLAB R2019b of the proposed system and the classical skyhook controller are executed. Based on the simulation results, the proposed controller provides better performance compared to the skyhook controller. The proposed controller provided a maximum improvement of 16% in the touchdown phase and 10% in the taxing phase compared to the skyhook controller. Full article

Aircraft brake discs undergo rapid temperature rises during braking, critically impacting safety, lifespan, and adjacent components. Therefore, it is particularly important to study the heat transfer mechanism during the braking process and predict the temperature distribution of the brake disc. To address challenges in experimental studies (e.g., high costs and extreme conditions), this study employs full-scale numerical simulations to investigate heat transfer behaviours in medium-sized passenger aircraft brake discs. In the numerical simulation process, a coupling model that comprehensively considers the friction heat generation of the brake disc, the solid heat transfer between the discs, and the heat dissipation of the outer surface of the disc and the surrounding air is constructed to accurately describe the heat transfer characteristics of the brake disc under dynamic conditions. The study shows that the surface temperature of the brake disc rises sharply during the braking process, resulting in a significant increase in the temperature gradient; at the same time, the surrounding air flow state significantly affects the heat dissipation efficiency of the brake disc and affects its temperature distribution. Finally, the effectiveness of the numerical simulation was verified by experiments, and the maximum relative error between the experimental results and the simulation results was about 4.5%. This study provides a research basis for optimizing the structural design of the brake disc, improving its heat dissipation performance and operating safety. Full article

This study aims to develop an integrated monitoring system using a fiber Bragg grating sensor network to record the structural response of a landing gear system under operational loads to detect hard landing conditions on soils with different absorbing characteristics and to differentiate between soil types during landings. This paper refers to drop tests carried out at a drop tower of the test article, an integrated leaf spring landing gear with fiber Bragg grating sensors, measuring strain to evaluate landings from different heights on different soil types: hard soil, sand, and gravel. Cross-correlation and fast Fourier transform analyses can help to assess the repeatability of the impact tests, to assess the developed system as very reliable in detecting landing conditions and ensure very low error in the accuracy of the sensor placement, or to assess whether different impacts under different conditions produce consistent responses. Full article

Due to the complexity of the landing gear’s (LG) structural integrity and its loads under various static or dynamic working conditions, the fatigue life assessment for LG is a highly challenging task. On the basis of the whole geometric model of a large passenger aircraft’s main landing gear (MLG), the quasi-static finite element model (FEM) of the whole MLG is established, and the high-cycle fatigue issue of the Main Fitting (MF) is studied by considering the variation in shock absorber travel (SAT). Firstly, the ground loads under actual fatigue conditions are equivalently converted into the forces acting on the center of the left and right axles of the MLG, and based on these spatial force decompositions, the magnitude and direction of the load for 12 different basic unit load cases (ULC) are obtained. That is, the stress of the MLG under actual fatigue conditions can be obtained by superimposing these ULCs. Then, considering that the SAT of the MLG varies under different fatigue conditions, and to reduce the number of finite element (FE) simulations, this article simplifies all the SAT experienced by the MLG into seven specific values, so as to establish seven quasi-static FEMs of the MLG with the specified stroke of the shock absorber. In this way, the fatigue stress of the MLG with any actual SAT can be obtained by interpolating the stress components of the seven FEMs. Only 84 FE simulations are needed to efficiently obtain the fatigue stress spectra from the ground load spectra. Finally, according to the material S-N curve and Miner’s damage accumulation criterion, evaluate the fatigue life of the Main Fitting. The results of the stress component interpolation and superposition method show that at least five different SATs of the whole MLG’s FEM are needed to effectively convert the fatigue loads into a stress spectrum. The fatigue life prediction results indicate that the minimum lifespan of the MF is 53164 landings, which means that the fatigue life meets the requirement design. Full article

In this study, a titanium alloy torsional spring used in aviation was taken as the research subject. Aiming at the fatigue life prediction problem of this spring, the life analysis of the titanium alloy torsional spring was performed using a customized UMAT subroutine based on the theory of continuous damage mechanics. Several sets of life prediction models and tests were compared. The fatigue lives of the springs at 60, 80, 100, and 120 degrees were 45,070, 65,067, 99,677, and 181,322 cycles, respectively. Compared with other fatigue life prediction methods, the fatigue life calculated by the customized subroutine was the most consistent with the fatigue life of the titanium alloy torsion spring tests. The average relative error between the measured experimental life value and the predicted value was 2.04%, which is less than 5%, meeting engineering measurement requirements. The effectiveness and applicability of the proposed model and method were verified, and the time and economic cost caused by excessively long experimental cycles were reduced. This helps improve the accuracy of fatigue life prediction for this titanium alloy torsional spring and provides analysis support for subsequent structural optimization and improvement. Full article

When using point cloud technology to measure the dimension and geometric error of aircraft landing gear components, the point cloud data obtained after scanning may have certain differences because of the sophistication and diversity of the components that make up the landing gear. However, when using traditional point cloud registration algorithms, if the initial pose between point clouds is poor, it can lead to significant errors in the final registration results or even registration failure. Furthermore, the significant difference in registration results between point clouds can affect the final measurement results. Adopting Teaching-Learning-Based Optimization (TLBO) to solve some optimization problems has unique advantages such as high accuracy and good stability. This study integrates TLBO with point cloud registration. To increase the probability of using TLBO for point cloud registration to search for the global optimal solution, adaptive learning weights are first introduced during the learner phase of the basic TLBO. Secondly, an additional tutoring phase has been designed based on the symmetry and unimodality of the normal distribution to improve the accuracy of the solution results. In order to evaluate the performance of the proposed algorithm, it was first used to solve the CEC2017 test function. The comparison results with other metaheuristics showed that the improved TLBO has excellent comprehensive performance. Then, registration experiments were conducted using the open point cloud dataset and the landing gear point cloud dataset, respectively. The registration results showed that the point cloud registration method proposed in this paper has strong competitiveness. Full article

AerMet 100 steel is a new type of double-hardened high-strength steel, which is often used as landing gear material in amphibious aircraft. In the present paper, the corrosion fatigue behavior and mechanism of AerMet 100 high-strength steel in a 3.5% NaCl solution was studied by stress-controlled fatigue tests and a series of subsequent characterizations of the fracture surface, microstructure, and cracks. The results indicated that the fatigue life of AerMet 100 high-strength steel decreased with a decrease in the stress level in a 3.5% NaCl solution, satisfying the relationship lgN = −2.69 × 10⁻³ σ + 6.49. The corrosion fatigue crack usually initiated from the corrosion pit and propagated across the martensitic flat noodles. Meanwhile, the corrosion fatigue crack tip was filled with Cr₂O₃, Fe₂O₃, and amorphous material; it propagated in the transgranular mode by a slip dissolution mechanism. This study provides some engineering significant for the fatigue performance of AerMet 100 steel in a 3.5% NaCl solution. Full article