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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.
L. W. Weston, J. H. Todd
Nuclear Science and Engineering | Volume 63 | Number 2 | June 1977 | Pages 143-148
Technical Paper | doi.org/10.13182/NSE77-A27017
Articles are hosted by Taylor and Francis Online.
The average 240Pu capture cross section was measured from 200 eV to 350 keV. The cross section was normalized at thermal-neutron energies (0.02 to 0.03 eV), and this normalization was confirmed at the 1.06-eV resonance by the black resonance technique. The source of pulsed neutrons was the Oak Ridge Electron Linear Accelerator. The capture gamma-ray detector used was the “total energy detector,” which is a modification of the Moxon-Rae detector. The shape of the neutron flux was measured relative to the 10B(n, α) cross section up to 2 keV and the 6Li(n, α) cross section at higher neutron energies. The results of the measurement define the average capture cross section of 240Pu over a wide neutron energy range to an accuracy of ∼8%, which is significantly better than previously known. The results indicate that the ENDF/B-IV evaluation is ∼25% low above 30-keV neutron energy. The cross section is important in fast plutonium-fueled reactors.