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Conference Spotlight
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.
F. B. Cheung, L. Baker, Jr.
Nuclear Science and Engineering | Volume 60 | Number 1 | May 1976 | Pages 1-9
Technical Paper | doi.org/10.13182/NSE76-A26851
Articles are hosted by Taylor and Francis Online.
Transient flow and freezing of molten core debris in coolant channels of the subassemblies of a liquid-metal fast breeder reactor has been an important consideration in postaccident heat removal. As a first step to study this phenomenon, transient freezing of a number of simulant materials in tube flow was investigated experimentally. Controlling parameters of the transient freezing process were determined from theoretical consideration. A parametric study of the effects of the controlling parameters on freezing was carried out, and an empirical correlation based on experimental measurements was obtained that is applicable over a wide range of Prandtl numbers. Results of the present study were compared to the existing analytical models.