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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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Fusion Science and Technology
Latest News
First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
J. M. Lopez, J. Vega, S. Dormido-Canto, A. Murari, J. M. Ramirez, M. Ruiz, G. De Arcas, JET-EFDA Contributors
Fusion Science and Technology | Volume 63 | Number 1 | January 2013 | Pages 26-33
Selected Paper from Seventh Fusion Data Validation Workshop 2012 (Part 3) | doi.org/10.13182/FST12-490
Articles are hosted by Taylor and Francis Online.
Disruptions in tokamak devices are inevitable and can severely damage a tokamak device's wall. For this reason, different protection mechanisms have to be implemented. In the Joint European Torus (JET), these protection systems are structured in different levels. At the lowest level are those systems that are responsible for protecting the machine's integrity, which must be highly reliable. More complex systems are located at higher levels; these higher-level systems have been designed to take action before low-level systems. Since the installation of the new metallic wall in JET, new protection systems have been being developed to improve the overall protection of the device. This work focuses on a software application - a disruption predictor - that detects an incoming disruption. This software application simulates the behavior of a real-time implementation.In recent years, efforts have been devoted to developing and optimizing a reliable system that is capable of predicting disruptions. This has been accomplished by the novel combination of machine-learning techniques based on supervised learning methods. Disruptions must be predicted early enough so that the protection systems can mitigate the effects of disruptions. This paper summarizes the software development of the JET disruption predictor. This software simulates the real-time data acquisition and data processing. It has been an essential software tool to both optimize the disruption prediction model and implement a simulator of the real-time predictor.