This paper examines various sensitivity analysis methods which can be used to determine the relative importance of input epistemic uncertainties on the uncertainty quantified performance estimate. The results from such analyses would then indicate which input uncertainties would merit additional study. The following existing sensitivity analysis methods are examined and described: local sensitivity analysis by finite difference, scatter plot analysis, variance-based analysis, and p-box-based analysis. As none of these methods are ideally suited for analysis of dynamic systems with epistemic uncertainty, an alternate method is proposed. This method uses aspects of both local sensitivity analysis and p-box-based analysis to provide improved computational speed while removing dependence on the assumed nominal model parameters.

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