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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.
Hiromichi Fumoto, Shigekazu Sato, Wataru Ito, Takaaki Tamura, Nobuya Yoshiki, Yasutoshi Kobayashi
Nuclear Technology | Volume 75 | Number 1 | October 1986 | Pages 96-108
Technical Paper | Radioactive Waste Management | doi.org/10.13182/NT86-A15980
Articles are hosted by Taylor and Francis Online.
In the nuclear fuel reprocessing plant, dissolver off-gas (DOG) is supposed to include nitrogen oxides (NOX) during the operation. An adsorption process by mineral zeolite has been studied for DOG treatment that follows a dehydration and iodine removal process. According to the results, the characteristics of the mineral zeolite hydrogenated by 1 N HCl are very favorable for this purpose. As for the actual operation, a small fraction of iodine is supposed to penetrate the I2 removal process to the NOX adsorption process. No degradation has been observed for the NOX adsorption of mineral zeolite by the presence of I2.