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Division Spotlight
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.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2023)
February 6–9, 2023
Amelia Island, FL|Omni Amelia Island Resort
Standards Program
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
25th anniversary of failure (and a chance at opportunity)
Silver anniversaries are usually a cause for great celebration, but this one is a cause for regret and a renewed plea for action. January 31, 2023, marks the 25th anniversary of the Department of Energy’s failure under law and contract to start the removal of spent nuclear fuel (SNF) from the country’s 74 commercial nuclear power plant sites in 35 states for disposal per the Nuclear Waste Policy Act of 1982. I personally know the moral and legal responsibility associated with this failure, because in 1998, as the then responsible DOE official, I had to personally announce it. But much has changed since then. There are many new avenues to address these past problems like federal, state, and community partnerships that can be beneficial for all, if there is DOE leadership and congressional action for both disposal and storage.
Geert Verdoolaege, Giorgos Karagounis, Andrea Murari, Jesús Vega, Guido Van Oost, JET-EFDA Contributors
Fusion Science and Technology | Volume 62 | Number 2 | October 2012 | Pages 356-365
Selected Paper from the Seventh Fusion Data Validation Workshop 2012 (Part 1) | doi.org/10.13182/FST12-A14627
Articles are hosted by Taylor and Francis Online.
Pattern recognition is becoming an increasingly important tool for making inferences from the massive amounts of data produced in fusion experiments. In this work, we present an integrated framework for (real-time) pattern recognition for fusion data. The main starting point is the inherent probabilistic nature of measurements of plasma quantities. Since pattern recognition is essentially based on geometric concepts such as the notion of distance, this necessitates a geometric formalism for probability distributions. To this end, we apply information geometry for calculating geodesic distances on probabilistic manifolds. This provides a natural and theoretically motivated similarity measure between data points for use in pattern recognition techniques. We apply this formalism to classification for the automated identification of plasma confinement regimes in an international database and the prediction of plasma disruptions at JET. We show the distinct advantage in terms of classification performance that is obtained by considering the measurement uncertainty and its geometry. We hence advocate the essential role played by measurement uncertainty for data interpretation in fusion experiments. Finally, we discuss future applications such as the establishment of scaling laws.