Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range
INSTITUTE FOR COMPUTER APPLICATIONS IN SCIENCE AND ENGINEERING HAMPTON VA
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We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method called the profile optimization method is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages a it prevents severe degradation in the off -design performance by using a smart descent direction in each optimization iteration, b there is no random airfoil shape distortion for any iterate it generates, and c it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler ow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.