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International Journal for Uncertainty Quantification

Publicou 6 edições por ano

ISSN Imprimir: 2152-5080

ISSN On-line: 2152-5099

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Indexed in

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

Volume 4, Edição 6, 2014, pp. 511-533
DOI: 10.1615/Int.J.UncertaintyQuantification.2014010659
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RESUMO

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.

CITADO POR
  1. Schaefer John, Hosder Serhat, West Thomas, Rumsey Christopher, Carlson Jan-Renee, Kleb William, Uncertainty Quantification of Turbulence Model Closure Coefficients for Transonic Wall-Bounded Flows, AIAA Journal, 55, 1, 2017. Crossref

  2. Schaefer John, Cary Andrew, Mani Mori, Krakos Joshua, Hosder Serhat, Grid Influence on Turbulence Model Coefficient Uncertainties in Transonic Wall-Bounded Flows, AIAA Journal, 56, 8, 2018. Crossref

  3. Bruneel Stijn, Verhelst Pieterjan, Reubens Jan, Baetens Jan M., Coeck Johan, Moens Tom, Goethals Peter, Quantifying and reducing epistemic uncertainty of passive acoustic telemetry data from longitudinal aquatic systems, Ecological Informatics, 59, 2020. Crossref

  4. He Xiao, Zhao Fanzhou, Vahdati Mehdi, Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features, Journal of Fluids Engineering, 142, 9, 2020. Crossref

  5. Granados-Ortiz F.-J., Ortega-Casanova J., Quantifying & analysing mixed aleatoric and structural uncertainty in complex turbulent flow simulations, International Journal of Mechanical Sciences, 188, 2020. Crossref

  6. Erb Aaron, Hosder Serhat, Analysis and comparison of turbulence model coefficient uncertainty for canonical flow problems, Computers & Fluids, 227, 2021. Crossref

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