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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.
Hsiao-Kang Wang, Lawrence Ruby
Nuclear Science and Engineering | Volume 57 | Number 1 | May 1975 | Pages 86-90
Technical Note | doi.org/10.13182/NSE75-A40348
Articles are hosted by Taylor and Francis Online.
The general theory of reactor noise in the time domain for a zero-power reactor is formulated by using an equation for the probability generating function (pgf). With suitable manipulations of the pgf, several previously known theoretical results from noise analysis in the time domain can be deduced from this general theory. Although the detection process is not treated generally, a new result is the explicit determination of the pgf for the case where delayed neutrons are considered.