A disruption predictor based on fuzzy logic applied to JET data

Disruptions remain a serious issue for International Thermonuclear Experimental Reactor (ITER) and the commercial reactor. In the past years, significant efforts have been devoted to the development of reliable disruption predictors. In this paper, the potential of fuzzy logic in this field is explored. A new disruption predictor for Joint European Torus (JET), which is based on fuzzy logic, was tested off-line using data collected during several JET campaigns, covering a very wide range of scenarios and plasma parameters. In the standard configuration, it was able to predict 92% of disruptions with about 18% of false alarms (FAs). The flexibility of the approach, which is to provide a different tradeoff between missed and FAs, depending on the desired results in terms of safety, is demonstrated. The potential of the technique to help quantifying the risks that are associated with the operation outside the already explored parameter space is also discussed.