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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.
Toshio Funada, Isao Nihei, Shunichi Yuhara, Takashi Nakasuji
Nuclear Technology | Volume 45 | Number 2 | September 1979 | Pages 158-165
Technical Paper | Material | doi.org/10.13182/NT79-A32306
Articles are hosted by Taylor and Francis Online.
A technique has been developed to measure the hydrogen level in liquid sodium using an inert gas carrier method. Hydrogen was extracted into an inert gas from sodium through a thin nickel membrane in the form of a helically wound tube. The amount of hydrogen in the inert gas was analyzed by gas chromatography. The present method is unique in that it can be used over the wide range of sodium temperatures (150 to 700°C) and has no problems associated with vacuum systems. The partial pressure of hydrogen in sodium was determined as a function of cold-trap tempera-ture (Tc) as log PH2(500°C) (Torr) = 8.796 − 4795/Tc (K) .Sieverts’ constant (Ks) was determined as a function of sodium temperature (T) as log Ks (ppm·Torr−1/2) = 0.171 + 198.1/T (K) .From Sieverts’ constant, the solubility of hydrogen in sodium is calculated as log CH (ppm) = 4.825 − 2398/Tc (K) .It was found that other impurities in sodium, such as (O) and (OH), have little effect on the hydrogen pressure in the sodium loop.
