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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.
Vijay K. Dhir, Kin Wong, W. E. Kastenberg
Nuclear Science and Engineering | Volume 63 | Number 3 | July 1977 | Pages 350-356
Technical Note | doi.org/10.13182/NSE77-A27049
Articles are hosted by Taylor and Francis Online.
One-dimensional, nonhomogeneous transient conduction equations in both liquid and solid regions of a volumetrically heated sphere subjected to arbitrary time-independent convective cooling condition at the surface are numerically integrated. The results of numerical integration show that, depending on the relative magnitudes of the volumetric heat generation rate and the surface heat removal rate, the initially molten particle may completely solidify, temporarily solidify and then completely remelt, or have a solid outer crust with an inner molten core. The times needed to attain these quasi-stable states and the solidification and remelting rates prior to attaining these physical states are also computed.