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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.”
Joon On Yang, Soon Heung Chang
Nuclear Technology | Volume 95 | Number 3 | September 1991 | Pages 266-271
Technical Paper | Fission Reactor | doi.org/10.13182/NT91-A34576
Articles are hosted by Taylor and Francis Online.
An alarm processing system (APS) has been developed that uses artificial intelligence techniques to help operators to make decisions. Alarms in nuclear power plants are classified into generalized and special alarms. Generalized alarms are further classified into global and local alarms. For each type of alarm, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The processing for the generalized alarms is based on “model-based reasoning.” The special alarms are processed by the cause-consequence check rules. The priorities of alarms are determined according to both the plant state and the consistencies among the alarms. This APS is built on a workstation using the Prolog language.