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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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.”
Masatoshi Nakagawa
Nuclear Technology | Volume 102 | Number 1 | April 1993 | Pages 81-89
Technical Paper | Mixed-Oxide Fuel / Fission Reactor | doi.org/10.13182/NT93-A34804
Articles are hosted by Taylor and Francis Online.
Validation of the ÉTOILE code through a comparison with experimental bundle/duct interaction (BDI) data is discussed. ÉTOILE is a newly developed three-dimensional finite element program that uses a new analytical method to predict distortions and mechanical behavior in wire-wrapped-type fuel-pin bundles during irradiation in liquid-metal fast breeder reactor cores. Comparisons between the ÉTOILE solutions and the experimental data for bundle stiffnesses and minimum pin-to-pin and pin-to-duct clearances under bundle compression suggest that BDI performance can be predicted reasonably well with a suitable choice of friction coefficient and initial spiral wire displacement. Application of the code in the analysis of the mechanical behavior of soft bundles with distributed wireless pins is also presented to demonstrate the effectiveness of this design in reducing the interaction forces between a fuel-pin bundle and a duct wall under bundle compression. Agreement with the experimental data is fairly good for the reduction in bundle stiffness when the configuration is changed from the normal bundle to the soft bundle.