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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. J. Mueller, J. K. Vaurio
Nuclear Science and Engineering | Volume 69 | Number 2 | February 1979 | Pages 264-278
Technical Paper | doi.org/10.13182/NSE79-A20616
Articles are hosted by Taylor and Francis Online.
This paper describes the basic equations and solution techniques of a collection of heat transfer and coolant voiding dynamics models that have been developed and successfully applied to simulate hypothetical accidents in liquid-metal-cooled fast breeder reactors (LMFBRs) to the point of permanent subcriticality or to the initiation of a prompt-critical excursion. These models emphasize analytic and integral solution techniques to minimize computational time and have been programmed into the SACO fast-running accident analysis computer code. The comparisons of SACO results to analogous SAS3D results used to qualify these models are illustrated and discussed. The fast-running nature of these models makes them an ideal sensitivity analysis tool for use in probabilistic evaluations of LMFBR accidents. Their use in this application is illustrated.