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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.
M. L. Williams, W. W. Engle, Jr.
Nuclear Science and Engineering | Volume 62 | Number 1 | January 1977 | Pages 92-104
Technical Paper | doi.org/10.13182/NSE77-A26941
Articles are hosted by Taylor and Francis Online.
The concept of channel theory is used to locate spatial regions that are important in contributing to a shielding response. The method is analogous to the channel-theory method developed for ascertaining important energy channels in cross-section analysis. The mathematical basis for the theory is shown to be the generalized reciprocity relation, and sample problems are given to exhibit and verify the properties predicted by the mathematical equations. Finally, a practical example is cited from the shielding analysis of the Fast Flux Test Facility performed at Oak Ridge National Laboratory, in which a perspective plot of channel-theory results was found useful in locating streaming paths around the reactor cavity shield.
