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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Ho Nieh nominated to the NRC
Nieh
President Trump recently nominated Ho Nieh for the role of commissioner in the Nuclear Regulatory Commission through the remainder of a term that will expire June 30, 2029.
Nieh has been the vice president of regulatory affairs at Southern Nuclear since 2021, though he is currently working as a loaned executive at the Institute of Nuclear Power Operations, where he has been for more than a year.
Nieh’s experience: Nieh started his career at the Knolls Atomic Power Laboratory, where he worked primarily as a nuclear plant engineer and contributed as a civilian instructor in the U.S. Navy’s Nuclear Power Program.
From there, he joined the NRC in 1997 as a project engineer. In more than 19 years of service at the organization, he served in a variety of key leadership roles, including division director of Reactor Projects, division director of Inspection and Regional Support, and director of the Office of Nuclear Reactor Regulation.
Mohammed Boufenar, Djemai Merrouche
Nuclear Science and Engineering | Volume 199 | Number 7 | July 2025 | Pages 1181-1200
Research Article | doi.org/10.1080/00295639.2024.2434389
Articles are hosted by Taylor and Francis Online.
In most cases of probabilistic safety assessment model quantification, the minimal cut set (MCS) generation technique is effective and fully sufficient. But as the number of high probability events increases, e.g. due to seismic risk assessments, more accurate methods may be necessary to compensate for the overestimation of the core damage frequency resulting from using MCS methods. Furthermore, in some applications, a relevant numerical treatment of dependencies and success in sequence analysis in noncoherent fault trees may also be required to avoid overly conservative results.
To mitigate these issues, this work introduces the binary decision diagram (BDD) method for calculating the exact top event probability. BDD efficiently captures and processes complex Boolean relationships within a fault tree, allowing for more accurate system reliability evaluations. The BDD method is highlighted for its ability to handle dependencies and success branches more accurately than the MCS approach.
This study demonstrates the feasibility and effectiveness of using BDD within the seismic probabilistic safety assessment of a nuclear research reactor. The results suggest that the utilization of this method provides reasonable assurance, allowing for robust decision making regarding real-time risk status with confidence.