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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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North American construction is back—smaller and faster—at OPG’s Darlington
“The nuclear renaissance is real here,” said Ontario Power Generation’s Subo Sinnathamby on May 8, one year to the day after OPG secured a final investment decision to build the first of four planned BWRX-300 reactors at its Darlington nuclear power plant, and shortly after the new reactor’s foundation was lifted into place. “We got our license to construct in April and our [final investment decision] in May, and we’ve been off to the races since.”
ames L. Macdonald, Billy V. Koen
Nuclear Science and Engineering | Volume | Number | Pages 142-151
Technical Paper | doi.org/10.13182/NSE75-A26636
Articles are hosted by Taylor and Francis Online.
This paper investigates the application of two artificial intelligence techniques, heuristic programming and learning theory, to the problem of digital computer control of nuclear reactors. The purpose of using an artificial intelligence approach is to alleviate the requirement for a detailed mathematical model of the nuclear reactor system. A control system is developed ivhich demonstrates the primary features of such an approach. Results are shown for several reactor and control problem variations using a computer simulated reactor.