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Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine ? ScramjetUQ ?

Najm, H.N.; Debusschere, Bert D.; Safta, Cosmin S.; Sargsyan, Khachik S.; Huan, Xun H.; Oefelein, Joseph C.; Lacaze, Guilhem M.; Vane, Zachary P.; Eldred, Michael S.; Geraci, Gianluca G.; Knio, Omar K.; Sraj, I.S.; Scovazzi, G.S.; Colomes, O.C.; Marzouk, Y.M.; Zahm, O.Z.; Menhorn, F.M.; Ghanem, R.G.; Tsilifis, P.T.

Abstract not provided.

Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine

Najm, H.N.; Debusschere, Bert D.; Safta, Cosmin S.; Sargsyan, Khachik S.; Huan, Xun H.; Oefelein, Joseph C.; Lacaze, Guilhem M.; Vane, Zachary P.; Eldred, Michael S.; Geraci, G.G.; Knio, O.K.; Sraj, I.S.; Scovazzi, G.S.; Colomes, O.C.; Marzouk, Y.M.; Zahm, O.Z.; Augustin, F.A.; Menhorn, F.M.; Ghanem, R.G.; Tsilifis, P.T.

Abstract not provided.

Quantification of Uncertainty in Extreme Scale Computations

Debusschere, Bert D.; Jakeman, John D.; Chowdhary, Kamaljit S.; Safta, Cosmin S.; Sargsyan, Khachik S.; Rai, P.R.; Ghanem, R.G.; Knio, O.K.; La Maitre, O.L.; Winokur, J.W.; Li, G.L.; Ghattas, O.G.; Moser, R.M.; Simmons, C.S.; Alexanderian, A.A.; Gattiker, J.G.; Higdon, D.H.; Lawrence, E.L.; Bhat, S.B.; Marzouk, Y.M.; Bigoni, D.B.; Cui, T.C.; Parno, M.P.

Abstract not provided.

Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem

Journal of Aerospace Information Systems

Safta, Cosmin S.; Sargsyan, Khachik S.; Najm, H.N.; Chowdhary, Kenny; Debusschere, Bert D.; Swiler, Laura P.; Eldred, Michael S.

In this paper, a series of algorithms are proposed to address the problems in the NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge. A Bayesian approach is employed to characterize and calibrate the epistemic parameters based on the available data, whereas a variance-based global sensitivity analysis is used to rank the epistemic and aleatory model parameters. A nested sampling of the aleatory-epistemic space is proposed to propagate uncertainties from model parameters to output quantities of interest.

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Results 26–50 of 70
Results 26–50 of 70