A Best-Estimate Plus Uncertainty Type Analysis for Computing Accurate Critical Channel Power Uncertainties

Abstract

This paper provides a Critical Channel Power (CCP) uncertainty analysis methodology based on a Monte-Carlo approach. This Monte-Carlo method includes the identification of the sources of uncertainty and the development of error models for the characterization of epistemic and aleatory uncertainties associated with the CCP parameter. Furthermore, the proposed method facilitates a means to use actual operational data leading to improvements over traditional methods (e.g., sensitivity analysis) which assume parametric models that may not accurately capture the possible complex statistical structures in the system input and responses.