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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.”
Martin G. Plys
Nuclear Technology | Volume 101 | Number 3 | March 1993 | Pages 400-410
Technical Paper | Severe Accident Technology / Nuclear Reactor Safety | doi.org/10.13182/NT93-A34796
Articles are hosted by Taylor and Francis Online.
Hydrogen production and combustion during hypothetical severe nuclear reactor accidents are discussed from the perspective of integral predictive assessment of such accidents. Unmitigated hydrogen production after prolonged core dryout has the adverse impacts of accelerating the degradation of core geometry, reducing heat transfer area, and impeding the in-vessel recovery of an accident. Unmitigated hydrogen combustion can, in certain circumstances, lead to containment failure, or it could damage equipment and thereby impede recovery. The phenomena of in-vessel hydrogen generation and combustion are summarized, including recent experiments, and selected models for integral predictive assessment of these phenomena are described. Adequacies and shortcomings of models and the experimental data base are identified, and the effects of mitigation are discussed.