Abstract
A multifaceted exploration of the NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge Problem aimed at examining the suitability of a probabilistic characterization of the epistemic uncertainties included with the problem statement is pursued. In the process, subproblems A through Dare treated, and the opportunities and challenges associated with a probabilistic description are delineated as they pertain to each uncertainty characterization, uncertainty propagation, and uncertainty management, as well as to sensitivity analysis. All epistemic variables are replaced with random variables, and an equivalent effective uncertainty model with no epistemic component is identified. A Bayesian approach for parameter inference and an update that is applied directly on the probability densities of the various uncertainty variables are pursued, and sampling techniques for uncertainty propagation are used. A conditional expectation approach and a method based on the reduction of epistemic uncertainty are pursued for sensitivity analysis and uncertainty propagation.