Abstract
Abstract The probabilistic characterization of uncertainty can be problematic in circumstances where there is a paucity of supporting data and limited experience on which to base engineering judgement. Information theory provides a framework in which to address this issue through reliance upon entropy-related principles of uncertainty maximization. We describe an application of such principles in the USNRC-sponsored program QUASAR (Quantification and Uncertainty Analysis of Source Terms for Severe Accidents in Light Water Reactors).
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