Inherent and Epistemic Uncertainty Analysis for Computational Fluid Dynamics Simulations of Synthetic Jet Actuators


A mixed uncertainty quantification method was applied to computational fluid dynamics (CFD) modeling of a synthetic jet actuator. A test case, flow over a hump model with synthetic jet actuators, was selected from the CFDVAL2004 workshop to apply the second-order probability framework implemented with a stochastic response surface obtained from quadrature-based nonintrusive polynomial chaos. Three uncertainty sources were considered: (1) epistemic uncertainty in turbulence model, (2) inherent uncertainty in free stream velocity, and (3) inherent uncertainty in actuation frequency. Uncertainties in both long-time averaged and phase averaged quantities were quantified using a fourth-order polynomial chaos expansion. 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 coefficients at three selected locations. The mixed uncertainty results for phase-averaged x-velocity distributions at three selected locations showed that the 95% confidence interval could generally envelop the experimental data. The Sobol indices showed that near the wall, the uncertainty in turbulence model had a main influence on the x-velocity. While approaching the main stream, the uncertainty in free stream velocity became a larger contributor. The mixed uncertainty quantification approach demonstrated in this study can also be applied to other CFD problems with inherent and epistemic uncertainties.


Mechanical and Aerospace Engineering

Research Center/Lab(s)

Center for High Performance Computing Research

Keywords and Phrases

Computational Fluid Dynamics; Polynomial Chaos; Stochastic Response Surface; Synthetic Jet Actuators; Uncertainty Quantification

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


File Type





© 2014 Begell House Inc., All rights reserved.

Publication Date

01 Jan 2014