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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.
S. K. Bhattacharyya, R. B. Pond
Nuclear Science and Engineering | Volume 65 | Number 3 | March 1978 | Pages 548-553
Technical Note | doi.org/10.13182/NSE78-A27186
Articles are hosted by Taylor and Francis Online.
The Doppler effect of a small UO2 sample was determined for the temperature range from 300 to 1100 K at the core center of the Argonne National Laboratory gas-cooled fast reactor (GCFR) critical assembly. The measurement provided the first data on the important 238U Doppler effect in GCFR systems. The normalized value of the GCFR 238U Doppler effect was found to be 54% smaller than the corresponding value in an equivalent liquid-metal fast breeder reactor (LMFBR) assembly. Calculations with ENDF/B-IV data yielded a calculated/experimental (C/E) ratio of 0.83, which is considerably lower than that in LMFBR assemblies. The reason for this misprediction appears to be an underprediction of the low-energy flux, a feature that seems to be general to hard spectrum assemblies. The 238U Doppler effect was also determined in a “steam-flooded” GCFR assembly. The Doppler effect for the temperature range from 300 to 1100 K increased by 93% relative to the “dry” reference value because of spectral softening. The same calculational methods using ENDF/B-IV data resulted in the much better C/E value of 1.00.