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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.
Brijesh Vyas, Carl J. Czajkowski, John R. Weeks
Nuclear Technology | Volume 55 | Number 2 | November 1981 | Pages 525-537
Technical Paper | Materials | doi.org/10.13182/NT55-525
Articles are hosted by Taylor and Francis Online.
A metallurgical failure analysis was performed on feedwater nozzle cracks from the steam generators of pressurized water reactors. The types of cracking observed have been categorized into three general classifications. The failures are considered to be caused by low cycle, stress-induced fatigue, probably enhanced by the corrosion process. Prior machine marks appeared to form initiation sites for cracks, while metallurgical structure had no apparent effect on crack location or propagation.