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http://dx.doi.org/10.7734/COSEIK.2018.31.4.183

Cross-sectional Optimization of a Human-Powered Aircraft Main Spar using SQP and Geometrically Exact Beam Model  

Kang, Seung-Hoon (Department of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.)
Im, Byeong-Uk (Department of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.)
Cho, Hae-Seong (Institute of Advanced Machines and Design, Seoul Nat'l Univ)
Shin, Sang-Joon (Department of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.31, no.4, 2018 , pp. 183-190 More about this Journal
Abstract
This paper presents optimization of the main spar of Human-Powered Aircraft (HPA) wing. Mass minimization was attempted, while considering large torsional deformation of the beam. Sequential Quadratic Programming (SQP) method was adopted as a relevant tool to conduct structural optimization algorithm. An inner diameter and ply thicknesses of the main spar were selected as the design variables. The objective function includes factors such as mass minimization, constant tip bending displacement, and constant tip twist of the beam. For estimation of bending and torsional deformation, the geometrically exact beam model, which is appropriate for large deflection, was adopted. Properties of the cross sectional area which the geometrically exact beam model requires were obtained by Variational Asymptotic Beam Sectional Analysis (VABS), which is a cross sectional analysis program. As a result, maintaining tip bending displacement and tip twist within 1.45%, optimal design that accomplished 7.88% of the mass reduction was acquired. By the stress and strain recovery, structural integrity of the optimal design and validity of the present optimization procedure were authenticated.
Keywords
human-powered aircraft; structural optimization; sequential quadratic programming; geometrically exact beam model; VABS; stress/strain recovery;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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