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Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Fusion Science and Technology
Latest News
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
R. Moreno, J. Vega, S. Dormido-Canto, A. Pereira, A. Murari, JET Contributors
Fusion Science and Technology | Volume 69 | Number 2 | April 2016 | Pages 485-494
Technical Paper | doi.org/10.13182/FST15-167
Articles are hosted by Taylor and Francis Online.
The Advanced Predictor of Disruptions (APODIS) has been working in the JET real-time network since the beginning of the ITER-like wall (ILW) campaigns. APODIS is a data-driven system based on a multilayer structure of Support Vector Machines (SVM) classifiers. APODIS was trained with JET data corresponding to carbon wall discharges between April 2006 and October 2009, without any retraining in spite of its use with metallic wall discharges. This paper has two main parts. First, APODIS disruption prediction capabilities are evaluated during the ILW run period from July 2013 to October 2014. The results obtained from these experimental campaigns (more than 1059 nondisruptive discharges and 390 nonintentional disruptions) showed 2.46% false alarms and 85.38% success rate. Taking into account that ITER (International Thermonuclear Experimental Reactor) will work with a similar wall to the current ILW at JET, the purpose of the second part of this study is to compare predictors trained with data from JET ILW campaigns. The high computational cost that APODIS training requires and the great performance of SVM have motivated the development of a one-layer SVM predictor. Therefore, an APODIS version and a simpler one-layer predictor have been compared. They have been trained with data between September 2011 and July 2012 (1036 nondisruptive discharges and 201 nonintentional disruptions) and tested with experimental data in the period July 2013 to October 2014 (1051 nondisruptive discharges and 390 nonintentional disruptions). The one-layer predictor shows slightly better results than the APODIS structure.
