Prioritizing Nuclear Data Needs Using Uncertainty Analysis

Year
2018
Author(s)
Ian C. Gauld - Oak Ridge National Laboratory
William Wieselquist - Oak Ridge National Laboratory
Abstract
Nuclear security modeling applications can often depend on very different types of lower fidelity data with significant gaps and inconsistencies. Analyzing the impact of these uncertainties on specific nuclear materials, configurations, and detection technologies provides valuable insight when determining where data improvements are needed the most. This paper describes the development and application of emerging uncertainty analysis tools that can be used to perform nuclear data uncertainty analysis and to identify and rank the impacts of individual nuclear data on national security applications. These tools constitute the framework of a comprehensive data uncertainty analysis capability that can provide improved quantitative and objective information on nuclear data needs. This information can be used to augment subject matter expert judgement. This cross-cutting research and development (R&D) capability can be applied to identify gaps and weaknesses in nuclear data to help prioritize future data investments. This in turn can help maximize benefits for specific agency missions. Lessons learned from the analysis of an illustrative example problem involving the measurement of plutonium in a neutron multiplicity counter are described herein, and areas for further methods and nuclear data uncertainty data development are provided.