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Remembering ANS member Gil Brown
Brown
The nuclear community is mourning the loss of Gilbert Brown, who passed away on July 11 at the age of 77 following a battle with cancer.
Brown, an American Nuclear Society Fellow and an ANS member for nearly 50 years, joined the faculty at Lowell Technological Institute—now the University of Massachusetts–Lowell—in 1973 and remained there for the rest of his career. He eventually became director of the UMass Lowell nuclear engineering program. After his retirement, he remained an emeritus professor at the university.
Sukesh Aghara, chair of the Nuclear Engineering Department Heads Organization, noted in an email to NEDHO members and others that “Gil was a relentless advocate for nuclear energy and a deeply respected member of our professional community. He was also a kind and generous friend—and one of the reasons I ended up at UMass Lowell. He served the university with great dedication. . . . Within NEDHO, Gil was a steady presence and served for many years as our treasurer. His contributions to nuclear engineering education and to this community will be dearly missed.”
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.
