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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.”
Paul A. Smith
Nuclear Technology | Volume 92 | Number 3 | December 1990 | Pages 363-373
Technical Paper | Radioactive Waste Management | doi.org/10.13182/NT90-A16237
Articles are hosted by Taylor and Francis Online.
The results of a diffusion-sorption experiment, using simulated groundwater spiked with a mixture of I25I, 85Sr, and 137Cs, are modeled by a one-dimensional porous-medium approach in which sorption is described by Freundlich isotherms. The governing equations are solved analytically for the special case of a linear isotherm and numerically using the RANCH-DIFF computer code for nonlinear isotherms. A set of time-dependent ordinary differential equations is obtained using the Lagrange interpolation technique and is integrated by Gear’s variable-order predictor-corrector method. The analysis allows the diffusion coefficients and parameters of the Freundlich isotherms to be extracted from the experimental data. It is shown that the sorption behavior of 85Sr can be modeled successfully by a linear isotherm, using a sorption parameter consistent with batch-sorption tests. The behavior of 137Cs may be modeled by a nonlinear isotherm, but the amount of 137Cs sorbed is less than that anticipated from batch-sorption tests. Iodine-125 is assumed to be nonsorbing and is used to determine the porosity of the rock.
