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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.
Weston M. Stacey, Jr., Mohamed A. Abdou
Nuclear Technology | Volume 37 | Number 1 | January 1978 | Pages 29-39
Technical Paper | Reactor | doi.org/10.13182/NT78-A32088
Articles are hosted by Taylor and Francis Online.
Received May 12, 1977 Accepted for Publication September 7, 1977 The major parameters and corresponding economic characteristics of a representative class of commercial tokamak fusion power reactors are examined as a function of four major design parameters: plasma βt, toroidal magnetic field strength, first-wall lifetime, and power output. It is shown that for βt ≥ 0.06, the minimum cost of energy is obtained for toroidal field strengths of ∼8 to 9 T. Tokamak power plants exhibit an economy of scaling with a lower cost of energy for larger power reactors. Representative design parameters, costs, schedule, and technology advances are presented for a sequence of three reactors that could lead to the demonstration of commercial feasibility of this class of tokamak fusion power reactors near the turn of the century.