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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Latest News
Atomic Canyon partners with INL on AI benchmarks
As interest and investment grows around AI applications in nuclear power plants, there remains a gap in standardized benchmarks that can quantitatively compare and measure the quality and reliability of new products.
Nuclear-tailored AI developer Atomic Canyon is moving to fill that gap by entering into a new strategic partnership with Idaho National Laboratory to develop and release the “first comprehensive benchmark suite for evaluating retrieval-augmented generation (RAG) and large language models (LLMs) in nuclear applications.”
Brent J. Lewis, Fernando C. Iglesias, C. E. Laurence Hunt, David S. Cox
Nuclear Technology | Volume 99 | Number 3 | September 1992 | Pages 330-342
Technical Paper | Nuclear Reactor Safety | doi.org/10.13182/NT92-A34717
Articles are hosted by Taylor and Francis Online.
An analytical model has been developed to describe the kinetic release behavior of the volatile fission product species (e.g., cesium) from uranium dioxide fuel. This treatment is based on the analysis of a series of out-of-pile annealing tests with bare fuel specimens, at temperatures of 1200 to 1800°C, performed under a wide range of atmospheric conditions that are characteristic of a severe reactor accident. The physically based model accounts for the changing fuel stoichiometry. A more general framework is therefore provided to detail the release kinetics in reducing and oxidizing environments. Solid-state diffusion in the fuel matrix is shown to be the rate-controlling mechanism of release in atmospheres of either hydrogen or argon. On the other hand, in addition to the slower diffusion component, it is demonstrated that a “burst-release” process also occurs in a steam environment, in accordance with first-order rate theory, where fission products are rapidly released at small values of the stoichiometry deviation.