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Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing

S. Rajagopal1, Ranjan Ganguli2
Corresponding author; E-mail: raja@aero.iisc.ernet.in; Address: CTC Division, ADE, DRDO, Govt of India, New Thippasandra Post, Bangalore-560075, India; Phone: +918025057242; Fax:+918025283188.
Email: ganguli@aero.iisc.ernet.in; Phone: +918022933017; Fax: +918023600134

Computer Modeling in Engineering & Sciences 2011, 81(1), 1-34. https://doi.org/10.3970/cmes.2011.081.001

Abstract

The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The first step performs a single objective aerodynamic optimization and the second step involves a coupled dual objective aerodynamic and structural optimization. During the first step, airfoil geometry is optimized to get maximum endurance parameter at a 2D level with maximum thickness to chord ratio and maximum camber as design variables. Leading edge curvature, trailing edge radius, zero lift drag coefficient and zero lift moment coefficient are taken as constraints. Once the airfoil geometry is finalized, the wing planform parameters are optimized with minimization of wing weight and maximization of endurance. Four design variables from aerodynamics discipline namely taper ratio, aspect ratio, wing loading and wing twist are considered. Also, four more design variables from the structures discipline namely the upper and lower skin thicknesses at root and tip of the wing are added. Constraints are stall speed, maximum speed, rate of climb, strength and stiffness. The 2D airfoil and 3D wing aerodynamic analysis is performed by the XFLR5 panel method code and the structural analysis is performed by the MSC-NASTRAN finite element code. In the optimization process, a multi-objective evolutionary algorithm named NSGA-II (non-dominated sorting genetic algorithm) is used to discover the full Pareto front for the dual objective problem. In the second step, in order to reduce the time of computation, the analysis tools are replaced by a Kriging meta-model. For this dual objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the preliminary design of UAV wing.

Keywords

Unmanned Aerial Vehicle, Multidisciplinary design optimization, multi-objective optimization, genetic algorithm, Pareto front, Kriging

Cite This Article

Rajagopal, S., Ganguli, R. (2011). Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing. CMES-Computer Modeling in Engineering & Sciences, 81(1), 1–34.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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