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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.
Nuclear Technology | Volume 7 | Number 2 | August 1969 | Pages 170-178
Accelerators | doi.org/10.13182/NT69-A28361
Articles are hosted by Taylor and Francis Online.
Formation of fission-fragment etch pits in glass was investigated with emphasis on the application of the method to the measurement of uranium distributions in solids and low-flux neutron dosimetry. The application of the method to the determination of uranium distributions, in both small and large specimens, was illustrated with specimens ∼450 µ m in diameter and with large, uranium-doped cesium iodide crystals. Upper and lower detection limits for uranium and neutron fluence were established for the glass slides employed. The purpose of the research was to illustrate the applicability of etch-pit techniques to a range of problems in nuclear technology.
