Suche nach „[S.] [Gianfelici]“ hat 1 Publikationen gefunden
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    NachhaltigF: Angewandte Naturwissenschaften und WirtschaftsingenieurwesenF: Europan Campus Rottal-Inn


    F. Gabrielli, W. Maschek, Rui Li, C. Matzerath Boccaccini, M. Flad, S. Gianfelici, B. Vezzoni, A. Rineiski

    Probabilistic evaluation of the energetics upper bound during the transition phase of an unprotected loss of flow accident for a sodium cooled fast reactor by using a Phenomenological Relationship Diagram

    Nuclear Engineering and Design, vol. 341, no. 146-154


    DOI: 10.1016/j.nucengdes.2018.11.004

    Abstract anzeigen

    One of the main research goals of the GEN-IV systems is enhancing their safety compared with the former Sodium-Cooled Fast Reactor (SFR) designs. A key issue is the capability of accidents prevention as well as of demonstrating that their consequences do not violate the safety criteria. In order to fulfill such requirements, risk analyses of severe core disruptive accidents are performed. Since the beginning of the SFR development, Hypothetical Core Disruptive Accidents (HCDAs) have played an outstanding role. Numerous safety analyses have been performed for developing and licensing past SFR designs and nowadays a large database of results is available. In particular, a large amount of results of the mechanistic SIMMER-II and SIMMER-III/IV analyses for various core designs and different power classes is available at the Karlsruhe Institute of Technology (KIT). The current paper describes the probabilistic approach based on the Phenomenological Relationship Diagram (PRD), which is used to evaluate the Probability Distribution Function (PDF) of the thermal energy release during the transition phase of an unprotected loss of flow accident scenario for a SFR. The technique allows taking into account the mechanistic nature of the accident scenario. In fact, the available results of the mechanistic analyses of HCDAs in SFRs are used to assess the PDFs of the dominant phenomena affecting the thermal energy release, which are propagated in the PRD by employing a Monte Carlo method.