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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.
Keiichiro Tsuchihashi, Yorio Gotoh
Nuclear Science and Engineering | Volume 58 | Number 2 | October 1975 | Pages 213-225
Technical Paper | doi.org/10.13182/NSE75-A28224
Articles are hosted by Taylor and Francis Online.
The effective resonance absorption of coated particles, which are embedded in a graphite matrix, is studied. The effect of a random arrangement of particles on the resonance integral is examined using the radial distribution function derived from the Percus-Yevick equation. A differential equation is proposed to obtain the neutron-beam current from a source particle in a medium in which the distribution function of coated particles is specified. By the use of the neutron beam current and the distribution function as the weight, the fuel-to-fuel collision probability is defined. This collision probability is applied to a RICM-type resonance integral code. The depression of the resonance integral of 238U due to grain structure amounts 5% in a design study of the multi-purpose high-temperature gas-cooled reactor (HTGCR) at the Japan Atomic Energy Research Institute. The applicabilities of the spherical cell model and of the collision probability in the high-dilution approximation of Lane et al. are tested. These simple procedures give satisfactory results for the treatment of microscopic heterogeneity in the range of the HTGCR design.