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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Fusion Science and Technology
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.
R. Herzing, L. Kuypers, P. Cloth, D. Filges, R. Hecker, N. Kirch
Nuclear Science and Engineering | Volume 60 | Number 2 | June 1976 | Pages 169-175
Technical Paper | doi.org/10.13182/NSE76-A26872
Articles are hosted by Taylor and Francis Online.
Measurements of the most important parameter of the blanket of a thermonuclear reactor—tritium production—are necessary for testing present nuclear data and analytical methods. A cylindrical model containing lithium metal was designed and constructed. The tritium production was measured by three methods: (a) tritium determination by a liquid scintillation method, (b) internal gas counting of the tritium β-activity, and (c) recording of the α-particles associated with the tritium producing reactions by solid-state track detectors. The space-dependent tritium production rates were calculated using discrete ordinates and Monte Carlo methods. The agreement between liquid scintillation and Monte Carlo results is as good as can be expected taking into account the uncertainty of the nuclear data used for the calculations.