Defence of doctoral thesis in the field of systems and operations research, M.Sc. Edoardo Tosoni
This dissertation develops probabilistic methodologies for strengthening the systematization of scenario analysis for the safety assessment of nuclear waste management facilities. From the perspective of the Finnish and European nuclear waste community, it contains novel results as, traditionally, this community has only relied on non-probabilistic what-if scenarios. The dissertation also addresses two classical objections to probabilistic approaches. First, the difficulty of obtaining information about the scenario probabilities is tackled by generating data through computer simulations and expert judgments. The quality of these data inputs is characterized by accommodating ranges of probability values, which makes it possible to produce risk estimates even in the presence of scarce information. Moreover, the quantification of uncertainties concerning the residual risk level helps assess the comprehensiveness of the analysis, which, as a goal, cannot be readily attained by non-probabilitstic approaches. Second, the dissertation proposes risk importance measures for identifying which scenarios involve greater risks than others. Thus, these probabilistic methods provide support for structured risk management decisions instead of merely lumping all the data inputs into a single risk estimate.
The methodologies are illustrated with case studies on nuclear waste management by examining the spent-fuel storage plant in Saluggia (Italy) and the near-surface repository of Dessel (Belgium). Still, the methodological results are generic as they can be extended to many other application areas, such as finance, in which systemic dependencies must be accounted for. The dissertation has been carried out mainly in the framework of the Finnish research programs KYT 2018 and KYT 2022 on nuclear waste management.
Opponent is Professor doctor Man-Sung Yim, Korea Advanced Institute of Science and Technology, South Korea
Custos is Professor Ahti Salo, Aalto University School of Science, Department of Mathematics and Systems Analysis
The public defence will be organised via Zoom and on campus. Link to the event
The doctoral thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.