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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| Veröffentlicht in: | International Journal of Aerospace Engineering Jg. 2019; H. 2019; S. 1 - 14 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Cairo, Egypt
Hindawi Publishing Corporation
2019
Hindawi John Wiley & Sons, Inc Wiley |
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| ISSN: | 1687-5966, 1687-5974 |
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| Abstract | 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. |
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| AbstractList | 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. 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 [C.sup.3/2.sub.L]/[C.sub.D] is the objective function, while level flight condition at maximum [C.sup.3/2.sub.L]/[C.sub.D] 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. 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 C L 3 / 2 / C D is the objective function, while level flight condition at maximum C L 3 / 2 / C D 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. |
| Audience | Academic |
| Author | Kanat, Öztürk Özdemir Körpe, Durmuş Sinan |
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| Cites_doi | 10.1177/1045389x17704521 10.2514/1.42362 10.1371/journal.pone.0153755 10.1061/(ASCE)AS.1943-5525.0000812 10.1155/2016/4098275 10.1016/j.jtherbio.2017.11.002 10.4050/jahs.62.012002 10.1063/1.4992769 10.1016/0098-1354(83)80005-2 10.2514/3.44690 10.2514/1.39016 10.1260/1756-8293.6.1.29 10.2514/1.c032074 10.2514/3.9394 10.1177/0954410015587725 10.1016/j.renene.2012.10.007 10.2514/3.9789 10.1115/1.2184352 |
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| Copyright | Copyright © 2019 Durmuş Sinan Körpe and Öztürk Özdemir Kanat. COPYRIGHT 2019 John Wiley & Sons, Inc. Copyright © 2019 Durmuş Sinan Körpe and Öztürk Özdemir Kanat. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | 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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| Title | Aerodynamic Optimization of a UAV Wing subject to Weight, Geometric, Root Bending Moment, and Performance Constraints |
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