A Computational Fluid Dynamics (CFD) and response surface-based multiobjective design optimization were performed for\r\nsix different 2D airfoil profiles, and the Pareto optimal front of each airfoil is presented. FLUENT, which is a commercial CFD\r\nsimulation code, was used to determine the relevant aerodynamic loads. The Lift Coefficient (CL) and Drag Coefficient (CD) data\r\nat a range of 0? to 12? angles of attack (a) and at three different Reynolds numbers (Re = 68, 459, 479, 210, and 958, 422) for\r\nall the six airfoils were obtained. Realizable k-e turbulence model with a second-order upwind solution method was used in the\r\nsimulations. The standard least square method was used to generate response surface by the statistical code JMP. Elitist Nondominated\r\nSorting Genetic Algorithm (NSGA-II) was used to determine the Pareto optimal set based on the response surfaces.\r\nEach Pareto optimal solution represents a different compromise between design objectives. This gives the designer a choice to\r\nselect a design compromise that best suits the requirements from a set of optimal solutions. The Pareto solution set is presented in\r\nthe form of a Pareto optimal front.
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