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International Journal for Uncertainty Quantification
Facteur d'impact: 3.259 Facteur d'impact sur 5 ans: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Imprimer: 2152-5080
ISSN En ligne: 2152-5099

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International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2014010659
pages 511-533

INHERENT AND EPISTEMIC UNCERTAINTY ANALYSIS FOR COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF SYNTHETIC JET ACTUATORS

Daoru Han
Laboratory for Astronautical Plasma Dynamics, Department of Astronautical Engineering, 233 Robert Glenn Rapp Engineering Research Building, University of Southern California, Los Angeles, California 90089-1192, USA
Serhat Hosder
Aerospace Simulations Laboratory, Department of Mechanical and Aerospace Engineering, 290B Toomey Hall, Missouri University of Science and Technology, Rolla, Missouri 65409-0500, USA

RÉSUMÉ

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.


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