Table of Contents Author Guidelines Submit a Manuscript
International Journal of Chemical Engineering
Volume 2012, Article ID 193021, 9 pages
http://dx.doi.org/10.1155/2012/193021
Research Article

Optimization of Wind Turbine Airfoil Using Nondominated Sorting Genetic Algorithm and Pareto Optimal Front

1Department of Mechanical Engineering, Prairie View A&M University, P.O. Box 519, Mail Stop 2525, Prairie View, TX 77446, USA
2Center for Energy and Environmental Sustainability, Prairie View A&M University, P.O. Box 519, Mail Stop 2500, Prairie View, TX 77446, USA
3Department of Civil and Environmental Engineering, Prairie View A&M University, P.O. Box 519, Mail Stop 2510, Prairie View, TX 77446, USA

Received 9 January 2012; Revised 13 February 2012; Accepted 13 February 2012

Academic Editor: Mahesh T. Dhotre

Copyright © 2012 Ziaul Huque et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A Computational Fluid Dynamics (CFD) and response surface-based multiobjective design optimization were performed for six different 2D airfoil profiles, and the Pareto optimal front of each airfoil is presented. FLUENT, which is a commercial CFD simulation code, was used to determine the relevant aerodynamic loads. The Lift Coefficient () and Drag Coefficient () data at a range of 0° to 12° angles of attack () and at three different Reynolds numbers (, 479, 210, and 958, 422) for all the six airfoils were obtained. Realizable turbulence model with a second-order upwind solution method was used in the simulations. The standard least square method was used to generate response surface by the statistical code JMP. Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to determine the Pareto optimal set based on the response surfaces. Each Pareto optimal solution represents a different compromise between design objectives. This gives the designer a choice to select a design compromise that best suits the requirements from a set of optimal solutions. The Pareto solution set is presented in the form of a Pareto optimal front.