Analysis of uncertainties associated with the numerical results evaluated by interactive computational PRA models

Probabilistic risk assessments (PRAs) have been widely used in nuclear, chemical, petrochemical, and several other industries. The probability and/or frequency results of most PRAs are based on average component unavailabilities during the mission of interest. While these average results are useful, they provide no indication of the significance of the facility´s current status when one or more components are known to be out of service. Recently, several interactive computational models have been developed for nuclear power plants to allow the user to specify the plant´s status at a particular time and then to receive updated PRA information. As with conventional PRA results, there are uncertainties associated with the numerical updated results. These uncertainties stem from a number of sources, including parameter uncertainty. The paper presents an analysis of the impact of parameter uncertainties on the updated PRA results for nuclear power plants