Problem Formulations and Treatment of Uncertainties in Aerodynamic Design

Recently, optimization has become an integral part of the aerodynamic design process chain. Besides standard optimization routines, which require some multitude of the computational effort necessary for the simulation only, fast optimization methods based on one-shot ideas are also available, which are only 4 to 10 times as costly as one forward flow simulation computation. However, the full potential of mathematical optimization can only be exploited, if optimal designs can be computed, which are robust with respect to small (or even large) perturbations of the optimization set-point conditions. That means the optimal designs computed should still be good designs, even if the input parameters for the optimization problem formulation are changed by a nonnegligible amount. Thus even more experimental or numerical effort can be saved. In this paper, we aim at an improvement of existing simulation and optimization technology, developed in the German collaborative effort MEGADESIGN, so that numerical uncertainties are identified, quantized, and included in the overall optimization procedure, thus making robust design in this sense possible. These investigations are part of the current German research program MUNA