Aerodynamic Optimization of a UAV Wing subject to Weight, Geometric, Root Bending Moment, and Performance Constraints

In this study, the optimization of a low-speed wing with functional constraints is discussed. The aerodynamic analysis tool developed by the coupling of the numerical nonlinear lifting-line method to Xfoil is used to obtain lift and drag coefficients of the baseline wing. The outcomes are compared w...

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Bibliographic Details
Published in:International journal of aerospace engineering 2019, Vol.2019 (2019), p.1-14
Main Authors: Körpe, Durmuş Sinan, Kanat, Öztürk Özdemir
Format: Article
Language:English
Subjects:
Aerodynamics
Aerospace engineering
Aircraft
Algorithms
Angle of attack
Aviation
Bending moments
Constraints
Drag coefficients
Engineers
Fuel consumption
Investigations
Low speed
Optimization techniques
Quadratic programming
Reynolds number
Shape optimization
Shear stress
Turbulence models
Unmanned aerial vehicles
Velocity
Weight
Wing planforms
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Summary:In this study, the optimization of a low-speed wing with functional constraints is discussed. The aerodynamic analysis tool developed by the coupling of the numerical nonlinear lifting-line method to Xfoil is used to obtain lift and drag coefficients of the baseline wing. The outcomes are compared with the results of the solver based on the nonlinear lifting-line theory implemented into XLFR5 and the transition shear stress transport model implemented into ANSYS-Fluent. The agreement between the results at the low and moderate angle of attack values is observed. The sequential quadratic programming algorithm of the MATLAB optimization toolbox is used for the solution of the constrained optimization problems. Three different optimization problems are solved. In the first problem, the maximization of CL3/2/CD is the objective function, while level flight condition at maximum CL3/2/CD is defined as a constraint. The functional constraints related to the wing weight, the wing planform area, and the root bending moment are added to the first optimization problem, and the second optimization problem is constructed. The third optimization problem is obtained by adding the level flight condition and the available power constraints at the maximum speed and the level flight condition at the minimum speed of the baseline unmanned air vehicle to the second problem. It is demonstrated that defining the root bending moment, the wing area, and the available power constraints in the aerodynamic optimization problems leads to more realistic wing planform and airfoil shapes.
ISSN:1687-5966
1687-5974
DOI:10.1155/2019/3050824