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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Senate EPW Committee to hold Nieh nomination hearing
Nieh
The Senate Environment and Public Works Committee will hold a nomination hearing Wednesday for Ho Nieh, President Donald Trump’s nominee to serve as commission at the Nuclear Regulatory Commission.
Trump nominated Nieh on July 30 to serve as NRC commissioner the remainder of a term that will expire June 30, 2029, as Nuclear NewsWire previously reported.
Nieh has been vice president of regulatory affairs at Southern Nuclear since 2021, though since June 2024 he has been at the Institute of Nuclear Power Operations as a loaned executive.
A return to the NRC: If confirmed by the Senate, Nieh would be returning to the NRC after three previous stints totaling nearly 20 years.
Gwendolyn J. Chee, Roberto E. Fairhurst Agosta, Jin Whan Bae, Robert R. Flanagan, Anthony M. Scopatz, Kathryn D. Huff
Nuclear Technology | Volume 207 | Number 2 | February 2021 | Pages 182-203
Technical Paper | doi.org/10.1080/00295450.2020.1753444
Articles are hosted by Taylor and Francis Online.
The present U.S. nuclear fuel cycle faces challenges that hinder the expansion of nuclear energy technology. The U.S. Department of Energy identified four nuclear fuel cycle options that make nuclear energy technology more desirable. Successfully analyzing the transitions from the current fuel cycle to these promising fuel cycles requires a nuclear fuel cycle simulator that can predictively and automatically deploy fuel cycle facilities to meet user-defined power demand. This work introduces and demonstrates the demand-driven deployment capabilities in Cyclus, an open-source nuclear fuel cycle simulator framework. User-controlled capabilities such as time-series forecasting algorithms, supply buffers, and facility preferences were introduced to give users tools to minimize power undersupply in a transition scenario simulation. The demand-driven deployment capabilities are referred to as d3ploy. We demonstrate the capability of d3ploy to predict future commodities’ supply and demand, and automatically deploy fuel cycle facilities to meet the predicted demand in four transition scenarios. Using d3ploy to set up transition scenarios saves the user simulation setup time compared to previous efforts that required a user to manually calculate and use trial and error to set up the deployment scheme for the supporting fuel cycle facilities.