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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.”
John R. White, Thomas F. DeLorey
Nuclear Technology | Volume 95 | Number 2 | August 1991 | Pages 129-147
Technical Paper | Fission Reactor | doi.org/10.13182/NT91-A34551
Articles are hosted by Taylor and Francis Online.
A detailed sensitivity and uncertainty analysis is performed for several parameters of interest in the design of the high-conversion reactor (HCR) concept. The main goals of this work are to determine the response standard deviation due to basic nuclear data uncertainties and to incorporate integral experiment information from the PROTEUS facility to reduce the computed uncertainties, where possible. The results for reactivity and five important reaction rate ratios (at the 0% void state) that are part of the measurement program in the PROTEUS phase II experiments are highlighted. In addition, the void coefficient at both low void and high void is studied. The computed correlation coefficients between the PROTEUS and HCR models are uniformly high for all responses. This indicates that a reduction in uncertainty can be achieved within the measurement uncertainty and that the PROTEUS experiments were ideal for the physics characterization of HCR responses.