UMAN – a pluralistic view of uncertainty management
Institute for Nuclear Research, RATEN ICN, 115400 Mioveni, Romania
2 BELV, 1070 Brussels, Belgium
3 Bundesgesellschaft für Endlagerung mbH (BGE), 31224 Peine, Germany
4 Nuclear Transparency Watch (NTW), 75011 Paris, France
5 Gesellschaft für Anlagen- und Reaktorsicherheit (GRS), 50667 Köln, Germany
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Received in final form: 17 October 2022
Accepted: 4 November 2022
Published online: 10 January 2023
Decisions associated with Radioactive Waste (RW) Management programmes are made in the presence of irreducible and reducible uncertainties. Responsibilities and roles of each actor, the nature of the RW disposal programme and the stage in its implementation influence the preferences of each category of actors in approaching uncertainty management. UMAN (UMAN – Uncertainties Management Multi-Actor Network is a Work Package of the European Radioactive Waste Management Programme – EURAD) carries out a strategic study about the management of uncertainties based on extended exchanges among actors representing Waste Management Organisations, Technical Support Organisations, Research Entities and Civil Society, a review of knowledge generated by past and ongoing R&D projects, and findings of international organisations. UMAN discusses the classification schemes and approaches applied in uncertainty management, and identifies possible actions to be considered in the uncertainty treatment. The relevance for the safety of the uncertainties associated with waste inventory, including spent fuel, near-field, site and geosphere and human aspects, as perceived by each type of actors, and approaches used in their management are explored with the aim to reach either a common understanding on how uncertainties relate to risk and safety and how to deal with them along the programme implementation, or at least arrive at a mutual understanding of each individual view. Finally, uncertainties assessed as highly significant and the associated R&D issues that can be further investigated are being identified.
© D. Diaconu et al., Published by EDP Sciences, 2023
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