Multi-Objective Optimization of Helicopter Airfoils Using Surrogate-Assisted Memetic Algorithms

solver. First, the peculiar features of the algorithm are described with particular attention to its advantages when compared with more traditional evolutionary or gradient-based algorithms. Finally, the results of the optimizations carried out using different operating conditions are presented; starting from the optimal Pareto fronts, several solutions are selected and compared in terms of shapes and performance.

[1]  William G. Bousman,et al.  Aerodynamic Characteristics of SC1095 and SC1094 R8 Airfoils , 2003 .

[2]  David W. Zingg,et al.  Aerodynamic Optimization Under a Range of Operating Conditions , 2006 .

[3]  T. Pulliam,et al.  Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm , 2001 .

[4]  Vu,et al.  Aerodynamic Design Optimization of Helicopter Rotor Blades Including Airfoil Shape , 2010 .

[5]  J. Trépanier,et al.  Airfoil shape optimization using a nonuniform rational B-splines parameterization under thickness constraint , 2006 .

[6]  Bernhard Sendhoff,et al.  Generalizing Surrogate-Assisted Evolutionary Computation , 2010, IEEE Transactions on Evolutionary Computation.

[7]  Domenico Quagliarella,et al.  Inverse and Direct Airfoil Design Using a Multiobjective Genetic Algorithm , 1997 .

[8]  Ernesto Tarantino,et al.  Evolutionary Algorithms for Aerofoil Design , 1998 .

[9]  P. Spalart A One-Equation Turbulence Model for Aerodynamic Flows , 1992 .

[10]  Martin T. Hagan,et al.  Neural network design , 1995 .

[11]  Soogab Lee,et al.  Response surface approach to aerodynamic optimization design of helicopter rotor blade , 2005 .

[12]  Mark Drela,et al.  Pros & Cons of Airfoil Optimization , 1998 .

[13]  F. Guibault,et al.  Optimized Nonuniform Rational B-Spline Geometrical Representation for Aerodynamic Design of Wings , 2001 .

[14]  Beckett Yx Zhou,et al.  Airfoil Optimization Using Practical Aerodynamic Design Requirements , 2010 .

[15]  M. Drela XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils , 1989 .

[16]  Bernhard Sendhoff,et al.  A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation , 2007, GECCO '07.

[17]  Ernesto Benini,et al.  Genetic Diversity as an Objective in Multi-Objective Evolutionary Algorithms , 2003, Evolutionary Computation.

[18]  William G. Bousman,et al.  Airfoil Design and Rotorcraft Performance , 2002 .

[19]  Tapabrata Ray,et al.  Swarm algorithm for single- and multiobjective airfoil design optimization , 2004 .

[20]  J. Désidéri,et al.  Multi-Objective Optimization in CFD by Genetic Algorithms , 1999 .

[21]  Kyriakos C. Giannakoglou,et al.  Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence , 2002 .

[22]  D. Zingg,et al.  Newton-Krylov Algorithm for Aerodynamic Design Using the Navier-Stokes Equations , 2002 .

[23]  D. F. Rogers Rational B-spline curves , 2001 .

[24]  D. F. Rogers,et al.  An Introduction to NURBS: With Historical Perspective , 2011 .