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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.
David B. Reister
Nuclear Science and Engineering | Volume 51 | Number 3 | July 1973 | Pages 316-323
Technical Paper | doi.org/10.13182/NSE73-A26608
Articles are hosted by Taylor and Francis Online.
A method for determining narrow upper and lower bounds for the fundamental eigenvalue of a nuclear reactor in either multigroup diffusion theory or transport theory has been developed. This method is based on the Barta-Polya theorem. The Barta-Polya theorem has been extended to yield bounds for multigroup diffusion theory eigenvalue problems. The trial function is a linear sum of known modes and unknown amplitude parameters. Determination of the optimum values of the parameters is a max-min problem of the type that occurs in optimum control and economics. To facilitate numerical computation, a coarse mesh is introduced. A computational method has been developed which quickly yields narrow eigenvalue bounds. Classical methods cannot determine optimum bounds since the function which is to be optimized is not differentiable at the max-min point. The bounds are determined using an iterative method. On each iteration the function is linearized about the mesh points, and linear programming is used to find the optimum solution to the approximate problem. Bounds have been found for a two-region, one-group diffusion theory problem and for a one-group transport theory problem. The bounds are superior to previous results and approach the exact solution as the number of terms in the trial function increases.