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Conference Spotlight
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.”
Conor O’Carroll, Klaus Lassmann
Nuclear Technology | Volume 99 | Number 2 | August 1992 | Pages 268-273
Technical Note | Nuclear Fuel Cycle | doi.org/10.13182/NT92-A34697
Articles are hosted by Taylor and Francis Online.
To describe the transport of volatile fission products along grain boundaries in nuclear fuels, a nonlinear diffusion equation must be used. Analytic solutions exist for the steady-state case, but the equation seems to be intractable when time dependence is included. A simple implicit numerical method has been developed that can guarantee a convergent stable solution when there is a central void. If there is no void, the method always yields a solution. There is perfect agreement between the analytic and numerical solutions for the steady state, and the method developed here offers significant advantages over other methods of solution. This basic model can be used in nuclear fuel performance studies.