Main outcomes and findings of the MUSA WP2 - identification and quantification of uncertainty sources

The Management and Uncertainties of Severe Accident (MUSA) project aimed to establish a harmonised approach for applying BEPU methods in severe accident analyses, with particular focus on the source term. The second work package “ Identification & Quantification of Uncertainty Sources” addressed one of the most crucial steps in BEPU analysis applying forward uncertainty propagation. Its main outcome is a knowledge-based matrix compiling over 600 uncertain input parameters related to source term assessment, including their associated models, phenomena, and (partial) quantifications. It was utilised and continuously updated in subsequent calculation work packages (Phebus FPT1, reactor and SFP case). First a consistent set of Figure of Merits, such as iodine and caesium release, was established. A systematic backward selection and characterisation approach of the associated uncertain input parameters was established, considering among others influencing phenomena, modelling choices, code capabilities, etc. While some parameters, such as shape factors, were common across codes - though different characterisations depending on code/user were provided - others were code-specific, appearing in only one or few codes. Establishing physically justifiable distributions proved challenging largely due to the scarcity of data and consequently heavy reliance on expert judgement and code-specific knowledge. Nevertheless, each parameter's characterisation had to be defendable on scientific grounds. In the absence of direct evidence, the characterisation was justified based on physical behaviour, while where direct association was not possible due to system complexity, on reasonable indirect evidence. This paper presents an overview of the work, main findings and conclusions, including the data base, and highlights key challenges and future research needs identified during the project. • Identification and quantification of uncertainty sources related to source term. • Systematic backward approach to select and quantify uncertain input parameters associated with the source term. • Comprehensive data base consisting of over 600 uncertain input parameters, including their quantification. • Scientifically defendable characterisation including justification. • Identification of future needs: further harmonisation, cross comparison as well as extension of the data base.