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November 9–12, 2025
Washington, DC|Washington Hilton
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NRC’s hybrid AI workshop coming up
The Nuclear Regulatory Commission will host a hybrid public workshop on September 24 from 9 a.m.-5 p.m. Eastern time to discuss its activities for the safe and secure use of artificial intelligence in NRC-regulated activities.
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.