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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.
Kuan-Chywan Tu, Chien-Hsiung Lee, Shih-Jen Wang, Bau-Shei Pei
Nuclear Technology | Volume 124 | Number 3 | December 1998 | Pages 243-254
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT98-A2923
Articles are hosted by Taylor and Francis Online.
A new mechanistic critical heat flux (CHF) model has been developed for flow boiling CHF data of low-pressure (i.e., 0.2 to 4.0 MPa), low-mass-flux (i.e., 189 to 789 kg/m2s), and high-quality conditions. In general, CHF at these conditions associates with the flow regime of annular flow. This model assumes that the Helmholtz instability at the liquid-vapor interface of annular flow triggers the onset of CHF. CHF is the energy required to dryout the liquid film isolated by flow instability. With five empirical constants to properly correlate the liquid-vapor configurations of annular flow in the steam-water systems, the model successfully achieves a mean deviation error of 10.2% over a CHF data set consisting of 733 CHF data. The prediction of this model is more accurate than those of Biasi and Bowring correlations at the aforementioned low-pressure and low-mass-flux conditions.