When the Details Matter – Sensitivities in PRA Calculations That Could Affect Risk-Informed Decision-Making

As the U.S. Nuclear Regulatory Commission (NRC) continues its efforts to increase its use of risk information in decision making, the detailed, quantitative results of probabilistic risk assessment (PRA) calculations are coming under increased scrutiny. Where once analysts and users were not overly concerned with figure of merit variations that were less than an order of magnitude, now factors of two or even less can spark heated debate regarding modeling approaches and assumptions. The philosophical and policy-related aspects of this situation are well-recognized by the PRA community. On the other hand, the technical implications for PRA methods and modeling have not been as widely discussed. This paper illustrates the potential numerical effects of choices as to the details of models and methods for parameter estimation with three examples: 1) the selection of the time period data for parameter estimation, and issues related to component boundary and failure mode definitions; 2) the selection of alternative diffuse prior distributions, including the constrained noninformative prior distribution, in Bayesian parameter estimation; and 3) the impact of uncertainty in calculations for recovery of offsite power