Methods for Characterizing Uncertainty Effects in Key Input Parameters Used in the 2-Dimensional Monte-Carlo Simulation of Dryout Power

Abstract

A 2-dimensional Monte-Carlo simulation of dryout power has been developed. A requisite of the probabilistic analysis is a clear discrimination of the two fundamental types of uncertainty effects that impacts on the interpretation and estimation of the model predictions of dryout powers. These uncertainty effects are aleatory, which is a property of the system itself, and epistemic uncertainty, which describes the lack of knowledge of the system. In this paper, we present the development of statistical error models and methods used to characterize the aleatory and epistemic uncertainties in the key input parameters used in predicting dryout power.