Evolving Statistical Methodologies for Safeguards

Statistical methodologies for safeguards were developed at an early stage of safeguards’ history and are rooted in the criteria-driven, facility-based approach which has long underpinned the International Atomic Energy Agency’s (IAEA) conclusions. While their principles and approaches remain generally valid in the framework of a State-level evaluation, their scope, previously restricted to material balance areas (MBA) within facilities, needs to be expanded to include the analysis of nuclear material flows, inventories and balances for a whole State, taking into account the increasing use of random inspection schemes in State-level approaches (SLA) and the implications for the statistical analysis of data collected according to these patterns. In addition to this undertaking, which poses a number of methodological challenges, new approaches are needed to address increasingly large and diversified data flows, to optimize the distribution of limited statistical analysis resources, to align them with the State-level technical objectives (TO) identified through the acquisition path analysis (APA) performed by the State evaluation groups (SEGs) and to develop probabilistic methods for the quantification of their targeted and achieved attainment. In addition, statistical evaluation results of State declared and verification data need to be consolidated and compared to information from other sources. Last but not least, considerable progress was made in the field of information technology (IT) and statistical methodologies since they were first applied to safeguards several decades ago. The current migration of the IAEA safeguards IT platform under the Modernization of Safeguards Information technology (MOSAIC) project has provided a unique opportunity to adapt and evolve methodologies and to integrate them into new software tools. This paper reviews the efforts undertaken in recent years by the Nuclear Fuel Cycle Information Analysis Section within the Safeguards Department Division of Information Management to review, upgrade, consolidate, and evolve safeguards statistical methodologies and describes the progress accomplished to date