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No AccessFull-Length Paper

Probabilistic Methods for Sensitivity Analysis and Calibration in the NASA Challenge Problem

Published Online:6 Feb 2015https://doi.org/10.2514/1.I010256

Abstract

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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