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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.”
Chaung Lin
Nuclear Technology | Volume 92 | Number 1 | October 1990 | Pages 118-126
Technical Paper | Development of Nuclear Gas Cleaning and Filtering Techniques / Radioactive Waste Management | doi.org/10.13182/NT90-A34491
Articles are hosted by Taylor and Francis Online.
A computer program that searches for control rod patterns has been developed. In the algorithm, the problem is decomposed into two levels. In the first level, according to an assumed average axial power distribution, a control rod pattern is determined that satisfies all constraints at each burnup step. In the second level, the conditions are checked at the end of the fuel cycle. If certain conditions are not satisfied, the average axial power distribution or the weighting factors are modified and the first-level search is repeated. The first-level search is formulated as an optimization problem with constraints. The constrained problem is converted to an equivalent unconstrained problem and a method similar to a penalty function method is then applied to obtain the control rod pattern. The program is demonstrated by successfully generating control rod programming for the Chinshan and Kuosheng nuclear power plants in Taiwan.