Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

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In this paper, uncertainty quantification approaches are applied to an aerodynamic uncertainty quantification problem with a far-field drag breakdown approach. Two uncertainty quantification approaches, a non-intrusive polynomial chaos approach and an inexpensive Monte-Carlo simulation approach on a response surface model are compared and investigated for more advanced aerodynamic uncertainty quantification. Using the drag breakdown approach, total drag of a body can be decomposed into three physical and one unphysical drag components: wave, viscous, induced and spurious drag components. The drag source distribution can also be visualized on the flowfield using this approach. An uncertainty quantification problem of two-dimensional airfoil with four uncertain input variables is analyzed with the drag breakdown approach to extract more aerodynamic design information about its uncertainty propagation.

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