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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.

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TYPE Conference Poster YEAR 2015
OSTI

CSPlib - A Software Toolkit for the Analysis of Dynamical Systems and Chemical Kinetic Models

Diaz-Ibarra, Oscar H.; Kim, Kyungjoo K.; Safta, Cosmin S.; Najm, H.N.

CSPlib is an open source software library for analyzing general ordinary differential equation (ODE) systems and detailed chemical kinetic ODE systems. It relies on the computational singular perturbation (CSP) method for the analysis of these systems. The software provides support for: General ODE models (gODE model class) for computing source terms and Jacobians for a generic ODE system; TChem model (ChemElemODETChem model class) for computing source term, Jacobian, other necessary chemical reaction data, as well as the rates of progress for a homogenous batch reactor using an elementary step detailed chemical kinetic reaction mechanism. This class relies on the TChem [2] library; A set of functions to compute essential elements of CSP analysis (Kernel class). This includes computations of the eigensolution of the Jacobian matrix, CSP basis vectors and co-vectors, time scales (reciprocals of the magnitudes of the Jacobian eigenvalues), mode amplitudes, CSP pointers, and the number of exhausted modes. This class relies on the Tines library; A set of functions to compute the eigensolution of the Jacobian matrix using Tines library GPU eigensolver; A set of functions to compute CSP indices (Index Class). This includes participation indices and both slow and fast importance indices.

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TYPE SAND Report YEAR 2021
OSTIDOI

Global sensitivity analysis and estimation of model error, toward uncertainty quantification in scramjet computations

AIAA Journal

Huan, Xun H.; Safta, Cosmin S.; Geraci, Gianluca G.; Eldred, Michael S.; Vane, Zachary P.; Lacaze, Guilhem M.; Oefelein, Joseph C.; Najm, H.N.

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertainparameters involvedandthe high computational costofflow simulations. These difficulties are addressedin this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying themin the current studyto large-eddy simulations ofajet incrossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system's stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. These methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

AIAA Journal

Huan, Xun H.; Safta, Cosmin S.; Sargsyan, Khachik S.; Geraci, Gianluca G.; Eldred, Michael S.; Vane, Zachary P.; Lacaze, Guilhem L.; Oefelein, Joseph C.; Najm, H.N.

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system’s stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. Finally, these methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

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TYPE Journal Article YEAR 2018
OSTIDOI
Results 1–25 of 60
Results 1–25 of 60