Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 209, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2020.107426
Keywords
Nuclear fusion; ITER; Superconducting magnets; Cryogenic cooling circuit; Loss-of-flow accident (LOFA); Precursors; Spectral clustering; Fuzzy C-means
Ask authors/readers for more resources
This work presents an approach to identify LOFA precursors (component failures leading to a loss of flow accidents) using a Spectral Clustering method based on the Fuzzy C-Means algorithm, applied to the Superconducting Magnet Cryogenic Cooling Circuit of a single module of ITER's Central Solenoid.
In the International Thermonuclear Experimental Reactor, plasma is magnetically confined with Superconductive Magnets (SMs) that must be maintained at cryogenic temperature by a Superconducting Magnet Cryogenic Cooling Circuit (SMCCC). To guarantee cooling, Loss-Of-Flow Accidents (LOFAs) in the SMCCC are to be avoided. In this work, an approach to identify LOFA precursors (i.e., those component failures leading to a LOFA) is presented. The approach is based on a Spectral Clustering (SC) method using the Fuzzy C-Means (FCM) algorithm and is applied to the SMCCC of a single module of the ITER Central Solenoid (CS).
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available