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Conference Spotlight
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.
J. Darvas, U. Hansen, E. Teuchert
Nuclear Technology | Volume 8 | Number 6 | June 1970 | Pages 496-506
Fuel | doi.org/10.13182/NT70-A28649
Articles are hosted by Taylor and Francis Online.
The use of Pu as a makeup fuel in D2O-moderated thorium converters is investigated. The reactor starts with plutonium, the bred 233U is reprocessed and fed back into the system. During reactor life there is a considerable change in fissile composition. The physics calculations follow the reactor through the whole running in period from the first core into a quasi-equilibrium state. For this type of system, the running in period makes an important contribution to the overall merits of the reactor. The physics of the Pu burner is compared in detail to a similar reactor using 235U as makeup fuel. The evaluation of fuel-cycle costs is performed with present worth methods, calculating quasi-equilibrium costs and average fuel-cycle costs for the reactor lifetime, running in period included. Thorium systems, starting and running with plutonium makeup, have to pay rather high penalties for the first refueling periods. The Pu value is estimated to be in the range of $9/g fissile.