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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.”
Andrei V. Gribok, Ibrahim K. Attieh, J. Wesley Hines, Robert E. Uhrig
Nuclear Technology | Volume 134 | Number 1 | April 2001 | Pages 3-14
Technical Paper | NURETH-9 | doi.org/10.13182/NT01-A3181
Articles are hosted by Taylor and Francis Online.
Inferential sensing is a method that can be used to evaluate parameters of a physical system based on a set of measurements related to these parameters. The most common method of inferential sensing uses mathematical models to infer a parameter value from correlated sensor values. However, since inferential sensing is an inverse problem, it can produce inconsistent results due to minor perturbations in the data. This research shows that regularization can be used in inferential sensing to produce consistent results. Data from Florida Power Corporation's Crystal River nuclear power plant (NPP) are used to give an important example of monitoring NPP feedwater flow rate.