Narzędzia help

Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
first previous next last
cannonical link button

http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-1cd6d770-6440-4c4f-8a3e-0d9a3d78b0bd

Czasopismo

Journal of KONES

Tytuł artykułu

Propeller optimization for small unmanned aerial vehicles

Autorzy Kusznir, T.  Smoczek, J. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Small-unmanned aerial vehicle propellers usually have a low figure of merit due to operating in the low Reynold’s number region due to their size and velocity. The airflow on the airfoil becomes increasingly laminar in this region thus increasing the profile drag and consequently reducing the figure of merit of the rotor. In the article, the airfoil geometries are parameterized using the Class/Shape function transformation. Particle swarm optimization is used to design an airfoil, operating in a Reynolds number of 100,000, which has a high lift to drag ratio. To avoid exceeding geometric constraints of the airfoil, a deterministic box constraint is added to the algorithm. The optimized airfoil is then used for a preliminary design of a rotor; given some design, constraints on the tip chord the rotor radius and the blade root chord, with parameters that achieve the highest theoretical figure of merit. The rotor parameters are obtained using a combination of momentum theory and blade element theory. The figure of merit of an optimal propeller with the same geometric parameters is then compared using the optimized airfoil and the Clark Y airfoil. The optimization is done in MATLAB while the aerodynamic coefficients are obtained from XFOIL. The results of the numerical simulation are presented in the article.
Słowa kluczowe
EN unmanned aerial vehicles   particle swarm optimization   airfoil modelling  
Wydawca Institute of Aviation
Czasopismo Journal of KONES
Rocznik 2017
Tom Vol. 24, No. 2
Strony 125--132
Opis fizyczny Bibliogr. 18 poz., rys.
Twórcy
autor Kusznir, T.
  • AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics 30 Mickiewicza Av. 30, 30-059 Krakow, Poland, tkusznir@agh.edu.pl
autor Smoczek, J.
  • AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics 30 Mickiewicza Av. 30, 30-059 Krakow, Poland, smoczek@agh.edu.pl
Bibliografia
[1] Ambroziak, L., Gosiewski, Z., Kondratiuk, M., Aerodynamics characteristics identification of micro air vehicle, Transactions of the Institute of Aviation, No. 216, pp. 17-29, 2011.
[2] Carrese, R., Winatro, H., Watmuff, J., User-preference particle swarm algorithm for airfoil design architecture, in 27th Congress of the International Council of the Aeronautical Sciences, Nice 2010.
[3] Drela, M., XFOIL: an analysis and design system for low Reynolds number airfoils, Lecture Notes in Engineering, Vol. 54, pp. 1-12, 1989.
[4] Eberhart, R. C., Shi, Y., Comparing inertia weights and constriction factors in particle swarm optimization, Congress on Evolutionary Computation, San Diego, CA, Vol. 1, pp. 84-88, 2000.
[5] Helwig, S., Branke, J., Mostaghim, S., Experimental analysis of bound handling techniques in particle swarm optimization, IEEE Transactions on Evolutionary Computation, Vol. 17, No. 2, pp. 259-271, 2013.
[6] Kennedy, J., Eberhart, R. C., Particle swarm optimization, in IEEE International Conference on Neural Networks, Vol. 4, pp. 1942-1948, Perth, WA 1995.
[7] Kulfan, B., Universal parametric geometry representation method, Journal of Aircraft, Vol. 45, No. 1, pp. 142-158, 2008.
[8] Leishman, J., Principles of helicopter aerodynamics, 2nd ed., Cambridge Univ. Press, New York 2008.
[9] Ma, R., Zhong, B., Liu, P., Wang, W., Multi-objective optimization design of low-Reynoldsnumber airfoil in Near Space, 3rd International Symposium on Systems and Control in Aeronautics and Astronautics, 2010.
[10] Nemec, M., Zingg, D., Pulliam, T., Multipoint and multi-objective aerodynamic shape optimization, AIAA Journal, Vol. 42, Vo. 6, pp. 1057-1065, 2004.
[11] Prouty, R., Helicopter performance, stability, and control, 5th ed. Malabar: Krieger Pub., 2005.
[12] Ram, K., Lal, S., Ahmed M. R., Low Reynolds number airfoil optimization for wind turbine applications using genetic algorithm, Journal of Renewable and Sustainable Energy, Vol. 5, pp. 1-15, 2013.
[13] Ribeiro, A., Awruch, A., Gomes, H., An airfoil optimization technique for wind turbines, Applied Mathematical Modelling, Vol. 36, No. 10, pp. 4898-4907, 2012.
[14] Serani, A., Diez, M., Leotardi, C., Campana, E., On the use of synchronous and asynchronous single-objective deterministic particle swarm optimization in ship design problems, in 1st International Conference on Engineering and Applied Sciences Optimization, Kos 2014.
[15] Sripawadkul, V., Padulo, M., Guenov, M., A comparison of airfoil shape parameterization techniques for early design optimization, 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, 2010.
[16] Stepniewski, W., Keys, C., Rotary-wing aerodynamics, 1st ed., Dover Publ., New York 1984.
[17] Zyluk, A., Sibilski, K., Kowalski, M., Wisniowski, W., Aerodynamic measurements micro air vehicle, Journal of KONES Powertrain and Transport, Vol. 22, No. 4, pp. 343-353, 2015.
[18] M-selig.ae.illinois.edu. [online]. available: http://m-selig.ae.illinois.edu/ads/coord/clarky.dat.
Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-1cd6d770-6440-4c4f-8a3e-0d9a3d78b0bd
Identyfikatory
DOI 10.5604/01.3001.0010.2909