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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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.
Victor C. Leite, Elia Merzari, Roberto Ponciroli, Lander Ibarra
Nuclear Technology | Volume 209 | Number 5 | May 2023 | Pages 645-666
Technical Paper | doi.org/10.1080/00295450.2022.2151822
Articles are hosted by Taylor and Francis Online.
In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. To demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.