A mixed (aleatory and epistemic) uncertainty quantification (UQ) method was applied to computational uid dynamics (CFD) modeling of a synthetic jet actuator. A test case, (ow over a hump model with synthetic jet actuator control) from the CFDVAL2004 work-shop was selected to apply the Second-Order Probability framework implemented with a stochastic response surface obtained from Quadrature-Based Non-Intrusive Polynomial Chaos (NIPC). Three uncertainty sources were considered: (1) epistemic (model-form) uncertainty in turbulence model, (2) aleatory (inherent) uncertainty in free stream veloc-ity and (3) aleatory uncertainty in actuation frequency. Uncertainties in both long-time averaged and phase averaged quantities were quantified using a fourth order polynomial chaos expansion (PCE). A global sensitivity analysis with Sobol indices was utilized to rank the importance of each uncertainty source to the overall output uncertainty. The results indicated that for the long-time averaged separation bubble size, the uncertainty in turbulence model had a dominant contribution, which was also observed in the long-time averaged skin friction coeficients at three selected locations. The mixed uncertainty results for phase averaged x-velocity distributions at three selected locations showed that the 95% confidence interval (CI) could generally envelope the experimental data. The Sobol indices showed that near the wall, the uncertainty in turbulence model had a main inuence on the x-velocity, while approaching the main stream, the uncertainty in free stream velocity be-came a larger contributor. The mixed uncertainty quantification approach demonstrated in this study can also be applied to other computational uid dynamics problems with inherent and model-form input uncertainities.