Integrated deterministic and probabilistic safety assessment of a superconducting magnet cryogenic cooling circuit for nuclear fusion applications

R. Bellaera, R. Bonifetto, F. Di Maio, N. Pedroni, L. Savoldi, R. Zanino and E. Zio

Reliability Engineering and System Safety, 2020, vol. 201, issue C

Abstract: The most promising configuration of a nuclear energy fusion system is the tokamak, the largest of which, called ITER, is under construction in Cadarache, France, which uses a complex system of superconducting magnets to generate a field of several tesla (T), aimed at confining the plasma in the toroidal chamber where nuclear fusion reactions occur. For industrial development, the safety of nuclear fusion systems has to be proved and verified by a systematic analysis of operational transients and accidental conditions. Although the final aim of fusion reactors is to reach steady state operation, present-day tokamaks present complex dynamic features, as their operation is based on the transformer principle with a subset of the superconducting magnets operating in a pulsed mode, to inductively generate plasma currents of the order of several MA. We adopt the framework of Integrated Deterministic and Probabilistic Safety Assessment (IDPSA), for identifying the component failures that may cause a Loss-Of-Flow-Accident (LOFA) in the cooling circuit of a superconducting magnet for fusion applications. Post-processing of the simulated scenarios for the identification of the abnormal transients is performed in an unsupervised manner resorting to a spectral clustering approach embedding a Fuzzy-C Means (FCM) that is compared with an Extended Symbolic Aggregate approximation (ESAX) from the literature that also resorts to the FCM for the classification.

Keywords: Nuclear fusion; Superconducting magnets; Cryogenic cooling circuit; IDPSA; Spectral clustering; Extended symbolic aggregate approximation (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:201:y:2020:i:c:s0951832019301425

DOI: 10.1016/j.ress.2020.106945

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