Modeling and design optimization of a two stage oleo-pneumatic landing gear

Date

2025-6-16

Author

Canıtez, Barış

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This thesis presents a comprehensive investigation into the dynamic response optimization of a helicopter landing gear system equipped with a two-stage, valve-metered oleo-pneumatic shock absorber. The landing gear model is formulated as a system of first-order ordinary differential equations (ODEs), derived from Newton’s second law and the continuity equation in the hydraulic chambers, and solved using MATLAB's stiff ODE solver ode15s(). A preliminary landing gear design is developed in accordance with aerospace standards for a 10-ton class helicopter, followed by a global sensitivity analysis using Sobol’s method to identify the most influential design parameters. Three optimization algorithms—numerical barrier method with backtracking line-search, Convex Response Surface Methodology (Convex RSM), and a genetic algorithm—are employed to maximize shock absorber efficiency while ensuring compliance with stroke constraints. A comparative assessment of the resulting designs is conducted based on performance metrics and computational cost. The genetic algorithm yielded the most efficient design but with a considerable computational demand. In contrast, Convex RSM achieved competitive results with significantly reduced computational cost. The numerical barrier method, although rudimentary, demonstrated notable improvements but with the highest computational cost. The findings suggest that Convex RSM and the numerical barrier method hold promise for efficient black-box optimization. Future research directions including a multi-objective optimization framework to consider a range of landing attitudes, enhancing surrogate model fidelity while preserving convexity, and applying the methods to other complex engineering problems to assess their general applicability.

Subject Keywords

Landing gear optimization, Numerical simulation of dynamic systems, Black-box optimization, Convex optimization, Global sensitivity analysis

URI

https://hdl.handle.net/11511/115101

Collections

Graduate School of Natural and Applied Sciences, Thesis