Bulletin of the American Physical Society
70th Annual Meeting of the APS Division of Fluid Dynamics
Volume 62, Number 14
Sunday–Tuesday, November 19–21, 2017; Denver, Colorado
Session Q34: Computational Fluid Dynamics: Uncertainty Quantification
12:50 PM–3:26 PM,
Tuesday, November 21, 2017
Room: 102
Chair: Jorge Sousa, Stanford University
Abstract ID: BAPS.2017.DFD.Q34.9
Abstract: Q34.00009 : Machine Learning Algorithms for prediction of regions of high Reynolds Averaged Navier Stokes Uncertainty*
2:34 PM–2:47 PM
Preview Abstract Abstract
Authors:
Aashwin Mishra
(Center for Turbulence Research, Stanford University)
Gianluca Iaccarino
(Center for Turbulence Research, Stanford University)
*This research was supported by the Defense Advanced Research Projects Agency under the Enabling Quantification of Uncertainty in Physical Systems (\emph{EQUiPS}) project (technical monitor: Dr Fariba Fahroo)
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2017.DFD.Q34.9
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