![]() Pehlivanoglu YV (2009) Representation method effects on vibrational genetic algorithm in 2-d airfoil design. Li W, Huyse L, Padula S (2002) Robust airfoil optimization to achieve drag reduction over a range of mach numbers. Selig MS, Maughmer MD (1992) Multipoint inverse airfoil design method based on conformal mapping. 169–190ĭrela M (1988) Low-reynolds-number airfoil design for the mit daedalus prototype-a case study. Fixed and flapping wing aerodynamics for micro air vehicle applications, pp. Lutz T, Würz W, Wagner S (2001) Numerical optimization and wind-tunnel testing of low reynolds number airfoils. Liebeck RH, Ormsbee AI (1970) Optimization of airfoils for maximum lift. Hicks RM, Vanderplaats GN (1975) Application of numerical optimization to the design of low speed airfoils. In: IOP Conference Series: Materials Science and Engineering, vol. Hoyos J, Jímenez JH, Echavarría C, Alvarado JP (2021) Airfoil shape optimization: Comparative study of meta-heuristic algorithms, airfoil parameterization methods and reynolds number impact. In: 31st Congress of the International Council of the Aeronautical Sciences, Belo Horizonte Aerosp Sci Technol 70:600–614īravo-Mosquera PD, Botero-Bolivar L, Acevedo-Giraldo D, Cerón-Muñoz HD, Catalano FM Experimental and computational analysis of a uav for superficial volcano surveillance. ![]() J Aircr 29(6):1106–1113īravo-Mosquera PD, Botero-Bolivar L, Acevedo-Giraldo D, Cerón-Muñoz HD (2017) Aerodynamic design analysis of a uav for superficial research of volcanic environments. Annu Rev Fluid Mech 15(1):223–239ĭrela M (1992) Transonic low-reynolds number airfoils. Lissaman P (1983) Low-reynolds-number airfoils. Int J Res Electr Electron Commun Eng 4:1–12 Islam MR, Bashar LB, Saha DK, Rafi N (2019) Comparison and selection of airfoils for small wind turbine between naca and nrel’s s series airfoil families. Finally, the optimal airfoils are compared against the S1223 and E423 airfoils for low and medium Reynolds, showing better aerodynamic characteristics. A linear relationship was found between the target lift coefficient and the maximum camber of the optimal airfoil, in addition to an impact of the target lift coefficient on the maximum achievable aerodynamic efficiency. The fits from XFOIL and CFD are compared and discussed. The results provide insights into the thickness, maximum camber and its position and their relation to aerodynamic efficiency. The obtained analytical expressions are helpful for straightforwardly getting the optimal airfoil shape during a design process. Several Optimizations with lift coefficients from 0.2 to 1.8 and Reynolds numbers from 80,000 to 500,000 are employed to be fitted by polynomial regressions, describing the best airfoil shape given the target lift coefficient and Reynolds number condition. ![]() The particle swarm optimization method is implemented and coupled with XFOIL and the open-source CFD OpenFOAM to optimize the airfoil shape parameterized by the NACA 4-digit equations. This work presents the airfoil shape equations, which achieve the best lift-drag ratio fulfilling specific lift coefficient and Reynolds number targets. ![]() The lift coefficient and Reynolds number are usually the main constraints in the aerodynamic platform design during the design process. ![]()
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