Optimization of Landing Gear Mechanism using Generative Design

Abstract

Combining evolutionary algorithms with additive manufacturing (AM) techniques, new material approaches, in aerospace and industrial applications can result in advanced design procedures. This combination adds extra degrees of flexibility to the final design concept, enabling multifunctional designs. Aerospace, which is heavily focused on customised production, is a perfect fit for AM due to its effects on economies of scale and scope. These technologies are prepared to be included within the generative design process for safety-critical contexts, including the aerospace, thanks to novel structural materials and advanced AM processes. The three primary phases of conventional aircraft design are conceptual design, preliminary design, and detailed design. Multidisciplinary optimization processes are currently being developed to support designer in assessing the optimal solution. Generative Design is a novel form-finding process that takes into account structural performance, material properties and ergonomic demand. Evolutionary design approaches limits to numerical optimization, while Topology Optimization seeks to find an optimal structural configuration within a given design domain for specified objectives, constraints, loads and boundary conditions. This paper focuses on creating appropriate generative design models which can sustain same amount of stresses as of the original model. In the current study the optimization of Boeing 747’s nose landing gear is depicted using solidworks and fusion 360. Static structural analysis is utilized to evaluate the effects of stresses and failure mode produced by various materials, in order to figure out a materials characteristic as well as for material selection. Additionally, this paper examines original and generative design models