Main landing gear shimmy is jointly affected by tire forces, structural elasticity, damping, and geometric coupling. To investigate the influence of side stay angular coupling on shimmy stability, this article establishes a shimmy dynamic model of a dual-wheel main landing gear considering side stay angular coupling. Numerical continuation bifurcation analysis, Hopf bifurcation frequency mapping, and local sensitivity analysis are then employed to study its influence mechanism on stability boundaries, dominant modes, and multistable behavior. The results show that the horizontal inclination angle of the side stay introduces additional structural coupling between strut torsion and longitudinal bending, causing the longitudinal motion to evolve from a passive response into an important mode participating in shimmy instability. A small horizontal inclination angle can induce the coexistence of multiple stable periodic responses, whereas a larger inclination angle changes the connectivity of Hopf bifurcation curves and forms a new instability branch involving longitudinal motion. Further analysis indicates that adjusting the orientation angle to make the local horizontal inclination angle approach zero can weaken the direct structural coupling between torsion and longitudinal motion and reduce the sensitivity of the longitudinal response to variations in the horizontal inclination angle. These results indicate that the angular design of the side stay should comprehensively consider the coupling effect between the horizontal inclination angle and the orientation angle, so as to avoid multistability and mode transition induced by the side stay angular arrangement.
Effective shock absorption is essential for maintaining stability during landing events. Aerospace systems traditionally rely on oleo-pneumatic struts, while robotic platforms utilize lightweight compliant joints for impact mitigation. Recent advances have shifted attention toward adaptive solutions, including magnetorheological and electrorheological dampers, which can adjust their damping characteristics in real time through sensor feedback and control algorithms. By integrating established mechanical design principles with advanced materials and intelligent control strategies, modern landing systems can achieve improved energy dissipation and enhanced performance under variable and unpredictable conditions. This work evaluates the transition from passive to adaptive shock absorption technologies by examining landing dynamics, the mechanical architectures of conventional and semi-active systems, and the control strategies that enable adaptive damping. The findings indicate that, although passive systems offer reliability and simplicity, they lack the adaptability required for highly variable environments, while semi-active systems provide enhanced performance through real-time modulation enabled by advanced control algorithms. However, challenges related to power requirements, system complexity, material durability, and long-term reliability continue to limit widespread implementation of adaptive technologies. Overall, this review highlights the limitations of passive designs, evaluates the tradeoffs between MR and ER damping technologies, examines the evolution of semi-active control strategies, and identifies the key technical barriers that must be addressed before adaptive shock absorption systems achieve broader operational adoption.
Aerodynamicists around the globe are developing mechanisms and structures inspired by nature that enable variable camber morphing (VCM) for aerodynamic surfaces. The implementation of the VCM mechanism in an airplane wing enhances the performance and stability during various flight segments. The present review article is focused mainly on the up-to-date VCM methods in a qualitative as well as quantitative approach that are specific to Aircraft/unmanned aerial vehicle (UAV) wing configurations. Initial literature discussions are confined to the conventional mechanisms that enable VCM in different aircraft configurations and the added aerodynamic advantages such as lift enhancement, drag reduction, boundary layer separation, and flow control. However, those designs need either external shape optimization or internal structural refinements to ensure the factor of safety (FoS). The modern aviation industry is also focused on bioinspired technology because of the adaptive flying capabilities and stall-delay characteristics. Therefore, a review of bioinspired VCM methods that are assessed based on the aerodynamic potentials is sequentially organized in the article. Additionally, considerations are motivated by the application of various compliant structural patterns for VCM in the aircraft industry. The discussion indicates the prospective benefits of morphing toward the future of the Green Aviation industry.
Investigating high-speed aerodynamics and aerothermodynamics presents a significant challenge for manned re-entry missions. The thermal effects on the surface of the re-entry vehicle and atmospheric stresses are primarily influenced by re-entry type and flight trajectory. This study investigates the monostability characteristics and aerothermodynamics of the Orion re-entry vehicle by incorporating static fins onto the aft fuselage of the vehicle, ensuring the lift-to-drag ratio remains unaffected throughout the numerical simulations. The study evaluated two different Mach numbers of 7 and 9 at various altitudes. The models were analyzed at different angles of attack from 0° to 90° in increments of 15°. The model with static fins exhibits a displacement in the monostable trim point, a reduction in the heat-shield pressure coefficient, and enhanced heat transfer throughout the re-entry vehicle.
The landing gear, as a crucial component of an aircraft, is pivotal for maintaining the safety and reliability of air travel. This study introduces a data-driven structural optimization method aimed at mitigating the peak strain on the landing gear’s rocker arm. The initial phase involves selecting nine design variables for parametric modeling to generate an initial dataset. Subsequently, the Maximum Information Coefficient (MIC) technique is used to conduct a parameter sensitivity analysis, enabling the identification and elimination of variables with minimal influence. A comparative analysis between the Genetic Algorithm–Backpropagation Neural Network (GA-BPNN) and BPNN reveals that GA-BPNN has a superior fitting capability on the enhanced dataset. By applying Particle Swarm Optimization (PSO), the optimal solution for GA-BPNN is identified. The implementation of this optimized method results in a 38.16% reduction in peak strain, validating its feasibility and reliability in enhancing aircraft safety.
