G MANIKANDAN et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 3, Issue No. 2, 078 - 088
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R2= User specified parameter which controls the probability test of global random number mutation operator R (0, 1) = Random number generator which returns a random value between 0 and 1. ith gene from the jth chromosome from the nth GA generation. jth chromosome from nth GA generation User specified maximum limits on th the i gene User specified minimum limits on th the i gene Ďľ = User specified parameter which controls the size of perturbation mutation parameters Subscripts i = Gene Index j = Chromosome Index k = Objective function index m = No of scalar objective function Superscripts n = Population Index t = Temporary chromosome and gene values obtained after initial selection and before modification operator.
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Abstract - Shape optimization of airfoil for the aerodynamic analysis of a low speed and low Reynolds number unmanned aerial vehicle wing is performed using parallel Genetic Algorithm. NACA 2412 chambered airfoil is chosen as zero generation airfoil. Real number coding is implemented for inputting seed value. Four modification operators are applied in this design space search method. The design space genes are control points of airfoil. Multiple fitness functions are utilized. Genetic Algorithm optimized airfoil profiles are used for the fabrication of composite material wing and are tested in the subsonic wind tunnel. The aerodynamic characteristics gleaned from experimental analysis are compared with base line airfoil and genetic algorithm optimized airfoil.
Nomenclature
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Keywords: Parallel Genetic Algorithm; Cambered Aerofoil; Fitness Function; Composite Material; Wind Tunnel; Aerodynamic characteristics.
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A = Set of Scalar Chromosome L = Set of Vector Lift values L/D = Lift by Drag ratio F – Set of Scalar Objective Function f = Scalar Objective Function No = nth GA generation M= User specified vector with four elements that controls modification operators mpt = Pass through operator mc = Random average cross over operator mpm= Perturbation mutation operator mm = Random mutation operator R1= User specified parameter which controls the probability test of perturbation mutation operator
ISSN: 2230-7818
I Introduction The objective of airfoil design optimization is to enhance the lift and L/D ratio and minimize the drag. There is a tradeoff between drag and lift because one of the drag components called Induced drag increases in proportion to the square of lift. Therefore the design airfoil profile is a challenging problem. Very precise shape optimization using very sensitive control points is needed. Aerodynamic evaluation using high fidelity model using Navier Stroke equation leads to very expensive function evolution. Gradient based numerical method for optimizing the airfoil shape was in practice for many years. The efficiency of gradient based optimization generally requires a smooth design space
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