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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.”
Andrej Prosek, Borut Mavko
Nuclear Technology | Volume 126 | Number 2 | May 1999 | Pages 186-195
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT99-A2966
Articles are hosted by Taylor and Francis Online.
When best-estimate calculations are performed, uncertainty needs to be quantified. An optimal statistical estimator (OSE) algorithm is adapted, extended, and used for response surface generation to demonstrate the algorithm's applicability to evaluating uncertainties in single-value or time-dependent parameters. A small-break loss-of-coolant accident with the break in the cold leg of a two-loop pressurized water reactor is selected for analysis. The code scaling, applicability, and uncertainty (CSAU) method was used for uncertainty quantification. The uncertainty was quantified for the RELAP5/MOD3.2 thermal-hydraulic computer code.The study shows that an OSE can be efficiently used instead of regression analysis for response surface generation. With the OSE, optimal information obtained from the code calculation is used for response surface generation. This finding indicates that by increasing the number of code calculations, one increases the confidence level of the uncertainty bounds. Increasing the number of calculations also results in convergence of the peak cladding temperature. As uncertainty can be evaluated for time-dependent parameters, the OSE tool makes the CSAU method universal for evaluating uncertainties of transients other than those of a loss-of-coolant accident.