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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.
E. M. Gelbard, D. C. Wade, R. W. Schaefer, R. E. Phillips
Nuclear Science and Engineering | Volume 64 | Number 2 | October 1977 | Pages 624-637
Technical Paper | doi.org/10.13182/NSE77-A27395
Articles are hosted by Taylor and Francis Online.
In this paper we describe a validation procedure for and results of streaming calculations for the Argonne National Laboratory gas-cooled fast reactor critical assemblies. The calculational approach for evaluating anisotropic diffusion theory methods is discussed in the context of a broader validation effort. A tentative procedure for converting from the three-dimensional physical unit cell to a one-dimensional model and for the generation of Benoist anisotropic diffusion coefficients in this one-dimensional model is described and analyzed. Based on the results, an alternate one-dimensional model and an alternate anistropic diffusion coefficient prescription are developed. After evaluating the alternate procedure, conclusions are drawn from the study.