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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Fusion Science and Technology
Latest News
High temperature fission chambers engineered for AMR/SMR safety and performance
As the global energy landscape shifts towards safer, smaller, and more flexible nuclear power, Small Modular Reactors (SMRs) and Gen. IV* technologies are at the forefront of innovation. These advanced designs pose new challenges in size, efficiency, and operating environment that traditional instrumentation and control solutions aren’t always designed to handle.
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.