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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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U.S. nuclear supply chain: Ready for liftoff
Craig Piercycpiercy@ans.org
This month, September 8–11, the American Nuclear Society is teaming up with the Nuclear Energy Institute to host our first-ever Nuclear Energy Conference and Expo—NECX for short—in Atlanta. This new meeting combines ANS’s Utility Working Conference and NEI’s Nuclear Energy Assembly to form what NEI CEO Maria Korsnick and I hope will be the premier nuclear industry gathering in America.
We did this because after more than four decades of relative stagnation, the U.S. nuclear supply chain is finally entering a new era of dynamic growth. This resurgence is being driven by several powerful and increasingly durable forces: the explosive demand for electricity from artificial intelligence and data centers, an unprecedented wave of public and private acceptance of—and investment in—advanced nuclear technologies, and a strong market signal for reliable, on-demand power. Add the recent Trump administration executive orders on nuclear into the mix, and you have all the makings of an accelerant-rich business environment primed for rapid expansion.
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.