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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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NERS publishes report on machine learning and microreactors
The University of Michigan’s Department of Nuclear Engineering and Radiological Sciences (NERS) has published a summary of a study on nuclear microreactors and machine learning (ML) that was conducted by researchers from NERS and Idaho National Laboratory. The full paper, “Nuclear Microreactor Transient and Load-Following Control with Deep Reinforcement Learning,” was featured in the July issue of Energy Conversion and Management: X.
H. Deuber, J. G. Wilhelm
Nuclear Technology | Volume 46 | Number 3 | December 1979 | Pages 399-403
Technical Paper | Nuclear Power Reactor Safety / Reactor | doi.org/10.13182/NT79-A32345
Articles are hosted by Taylor and Francis Online.
In a 1300-MW(electric) pressurized water reactor power plant, the sources of the airborne 131I species were determined over a period of five months. During power operation, the main source of the radio-logically decisive elemental 131I was the exhaust from the hoods in which samples from the primary coolant are taken and processed. During refueling outage, elemental 131I was mainly contributed by the containment purge air. By efficient filtration of these exhausts, a reduction of the ingestion dose, caused by the total 131I stack release, by a factor of nearly 4 during power operation and of possibly 10 during refueling outage can be accomplished.
