Enhanced Evolutionary-Based Optimization Techniques Applied to a Nonlinear Landing Gear Design Problem

Abstract

Engineering design processes often use optimization strategies, which aim to minimize multi-objective functions. The analysis should consider the uncertainty in a system, which may cause signicant changes in its behaviour. The inclusion of the uncertainty in the design process makes the identication of an optimum design more challenging. In this paper, two novel optimization methods (Iterative Dierential Evolutionary Algorithm-I.D.E.A. and Reliable & Robust Evolutionary Algorithm-R.R.E.A.) are presented. These optimization strategies aim to solve problems that are very time demanding and for which it is dicult (and expensive) to determine derivatives and to identify and dene the optimum set of parameters. The approaches are validated considering as a test case the optimization of a landing gear system in order to avoid the onset of shimmy, assuring a reliable design.

Analysis of the Synchronized Locking Dynamic Characteristics of a Dual-Sidestay Main Landing Gear Retraction Mechanism

“…The landing gear retraction system is closely related to the take-off and landing safety and flight performance of the aircraft [1,2]. Most modern aircraft use retraction mechanisms to reduce aerodynamic drag during flight [3].…”

“…The collision force model is an important part of the multi-body dynamic model with clearance and serves as the foundation for research on the dynamic response of joint effects to the multi-body system. The collision contact force model in this section is established by Equation (1).…”