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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.
Patrick J. Roache
Nuclear Science and Engineering | Volume 64 | Number 1 | September 1977 | Pages 219-221
Technical Paper | doi.org/10.13182/NSE77-A27092
Articles are hosted by Taylor and Francis Online.
The title problem is considered from the viewpoint of one involved in aerodynamics problems, rather than reactor modeling. The status of opinion is briefly reviewed on two sources of error: errors due to discretization, especially in regard to “high cell Reynolds number” difficulties, and errors in the continuum equations, especially in regard to turbulence modeling. It is concluded that significant improvement is to be expected over the lumped-parameter codes, but that even the forthcoming codes based on simulation of the partial differential equations are expected to be limited to a rather crude level of accuracy.