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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.”
Edgar A. Rhodes, Theodore H. Bauer, George S. Stanford, James P. Regis, Charles E. Dickerman
Nuclear Technology | Volume 98 | Number 1 | April 1992 | Pages 91-99
Technical Paper | Fast Reactor Safety / Nuclear Reactor Safety | doi.org/10.13182/NT92-A34653
Articles are hosted by Taylor and Francis Online.
Results from hodoscope data analyses are presented for transient overpower (TOP) tests M5, M6, and M7 at the Transient Reactor Test Facility, with emphasis on transient feedback mechanisms, including prefailure expansion at the tops of the fuel pins, subsequent dispersive axial fuel motion, and losses in relative worth of the fuel pins during the tests. Tests M5 and M6 were the first TOP tests of margin to cladding breach and prefailure elongation of D9-clad ternary (U-Pu-Zr) integral fast reactor-type fuel. Test M7 extended these results to high-burnup fuel and also initiated transient testing of HT-9-clad binary (U-Zr) Fast Flux Test Facility driver fuel. Results show significant prefailure negative reactivity feedback and strongly negative feedback from fuel driven to failure.