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Conference Spotlight
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.”
Theodore H. Bauer, Thomas H. Braid, Karl Schleisiek
Nuclear Technology | Volume 99 | Number 3 | September 1992 | Pages 343-350
Technical Paper | Nuclear Fuel Cycle | doi.org/10.13182/NT92-A34718
Articles are hosted by Taylor and Francis Online.
A technique is presented to quantify fuel damage in a liquid-metal reactor through fast-running computer analysis of delayed neutron data, suitable for analysis of both small-scale in-pile experiments and full-scale plants. Validating analyses are described for five in-pile severe accident simulations performed within the Sodium Loop Safety Facility and Mol-7C test programs. Comparison is made of measured and calculated amounts of fuel damage.