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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.
Pran K. Paul
Nuclear Technology | Volume 205 | Number 6 | June 2019 | Pages 847-866
Technical Paper | doi.org/10.1080/00295450.2018.1533319
Articles are hosted by Taylor and Francis Online.
This paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using the following computer codes: MCNP, Automated Variance Reduction Generator (ADVANTG)/MCNP, Monaco, and Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemishell, cylindrical shell, rectangular plate, cylindrical rod, and cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at 1 mm and 1 m from the package surfaces are calculated for these different source configurations. The MCNP and Monaco cases are run without any biasing options to accelerate the convergence. The Consistent Adjoint Driven Importance Sampling and the Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in the ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using the Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses the Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). The MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at 1 mm and 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.