Publications

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

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.