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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.
C. H. King, M. S. Ouyang, B. S. Pei, Y. W. Wang
Nuclear Technology | Volume 82 | Number 2 | August 1988 | Pages 211-226
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34108
Articles are hosted by Taylor and Francis Online.
A new technique of identifying the flow regimes of air/water two-phase flow in a vertical pipe is proposed. This technique is based on analyzing the statistical characteristics of the static and differential pressure signals by an optimum modeling method. The major concept of the optimum modeling method is to fit the two-phase flow pressure noise by autoregressive moving average (ARMA) models with an optimization technique. The results show that it is possible to identify the flow patterns from a set of “flow regime indices,” such as dynamic signature, order of dominant dynamics mode, and order of ARMA model. A computer code based on these indices has been built on an IBM-PC/XT microcomputer to perform two-phase flow pattern identification. The success probability of this code is ∼85% on the data base collected from our experimental work. The experimental data points are also indicated in a Taitel flow map and excellent matching has been shown, except for some points around the flow regime transition boundaries. These discrepancies are due to the subjective categorization of the flow regimes.
