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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Princeton-led team develops AI for fusion plasma monitoring
A new AI software tool for monitoring and controlling the plasma inside nuclear fuel systems has been developed by an international collaboration of scientists from Princeton University, Princeton Plasma Physics Laboratory (PPPL), Chung-Ang University, Columbia University, and Seoul National University. The software, which the researchers call Diag2Diag, is described in the paper, “Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas,” published in Nature Communications.
Gad Shani
Nuclear Science and Engineering | Volume 65 | Number 1 | January 1978 | Pages 183-187
Technical Note | doi.org/10.13182/NSE78-A27142
Articles are hosted by Taylor and Francis Online.
The hybrid fusion reactor is becoming an interesting and promising model. In the present Note, a method for controlling the breeding-fission ratio is investigated. Since 238U fission occurs mainly with fast neutrons and breeding occurs with intermediate and slow neutrons, an optimal ratio can be obtained by partial slowing down of the original 14.9-MeV neutrons. This is done using iron as the moderator. Uranium samples were irradiated with 14.9-MeV neutrons from a deuterium-tritium reaction with iron layers of various thicknesses between the samples and the neutron source. It was found that with a relatively thin layer of iron (12 cm), any breeding-fission ratio can be obtained within a range of two decades. The breeding rate changes by only 50% when the iron-slab thickness changes from 0 to 12 cm, while the fission rate follows (more or less) the 14-MeV neutron flux and drops by more than two decades. Good agreement was obtained between the measurement and the calculated results.