Some Aspects of Airfoil Optimization Process for Small Size Unmanned Aerial Vehicles Application

Aviation technologies


Аuthors

Parkhaev E. S.*, Semenchikov N. V.**

Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

*e-mail: EgorParhaev@yandex.ru
**e-mail: semenchikovnv@rambler.ru

Abstract

Recently, aircraft scheme mini — and micro- unmanned aerial vehicles (UAV) are considered to be a new promising direction of advancement of UAV. The increased interest in this class of aircraft is due to simultaneous appearance of new advances in the aircraft components miniaturization and new concepts of such devices application.

The purpose of the present study is to design and to solve small size unmanned aerial vehicles airfoil optimization problem for better performance. Analysis of obtained results and conclusions for further research are presented.

In the presented paper method of direct numeral airfoil optimization is used. As far as the method of direct numeral airfoil optimization implies the calculation of airfoil flow and airfoil performance, the calculation method (aerodynamic model) considers the aspects of airfoil flow at low Reynolds Numbers due to laminar-turbulent transition and separation bubble. Additionally this method and used technique is economical and efficient. Xfoil code is one of the few aerodynamic models that solves viscous-inviscid interaction problem in airfoil analysis.

So called genetic algorithm was used for optimization process. Genetic algorithm refers to stochastic method of numerical optimization.

In case of multiobjective optimization the method, based on homogeneous criteria comprising to one overall (integral) criteria was used. This method involves sum of criteria weighted by coefficients drawn up according to relative importance and other weights. It is so called weighted sum method.

Examples for numerical calculations of the airfoil optimization process using direct numerical method for one or more objectives at low Reynolds Numbers are presented. It was shown, that in order to design practical airfoil the optimization process should be multiobjective.

Numerical results in application of small size aerial vehicle were obtained, some important notice and conclusions was made, necessity and practical value of multiobjective approach were shown.

Keywords:

airfoil, direct numerical optimization (DNO), small size unmanned aerial vehicles, low Reynolds numbers

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