Uncertainty quantification of separation control with synthetic jet actuator over a NACA0025 airfoil

Abstract

A compressed sensing method based on polynomial chaos expansion (CS-PCE) is used to study separation control over an airfoil with a synthetic jet actuator (SJA). Uncertainty quantification (UQ) of a two-dimensional cavity driven flow model based on a Monte Carlo (MC) method with a sample size of 3000 is used as the indicator to evaluate the applicability and accuracy of four different probability collocation (PRC) methods. The sample points corresponding to the chosen model are used in a three-dimensional SJA control model. The effects of input factors on the aerodynamic performance and flow field parameters of airfoil are studied and show that a 5% coefficients of variation of stochastic input variables result in a roughly 30% fluctuation of lift-to-drag ratio. High uncertainty mainly exists in the middle and downstream regions of the upper surface corresponding to high vorticity regions. As sample size is increased, the accuracy of the CS-PCE model is improved. Compared with traditional methods, the CS-PCE method reduces computing costs up to 70% for similar results.