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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.
A. Tsechanski, G. Shani
Nuclear Science and Engineering | Volume 87 | Number 2 | June 1984 | Pages 189-194
Technical Note | doi.org/10.13182/NSE84-A17711
Articles are hosted by Taylor and Francis Online.
A simple method for the measurement of the loss of deuteron energy in a solid Ti-T target of a neutron generator is described. The method is based on a comparison of the results of measurements of the full-width at half-maximum of the peak in the spectrum of a collimated T(d,n)4He neutron beam directed at nominal angles of O and 95 deg to the neutron generator axis. The average deuteron energy loss in the solid Ti-T target is estimated to be (58.5 ± 4.0) keV at 150-kV nominal accelerating voltage of the neutron generator. The neutron spectrum measurements were carried out by a 2- × 2-in. NE-213 liquid scintillator. The proton recoil spectra created in the liquid scintillator were unfolded into the neutron energy spectra with the FORIST unfolding code.