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September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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.”
Nathan Siu, George Apostolakis
Nuclear Science and Engineering | Volume 94 | Number 3 | November 1986 | Pages 213-226
Technical Paper | doi.org/10.13182/NSE86-A17264
Articles are hosted by Taylor and Francis Online.
The assessment of the fire risk in nuclear power plants requires the analysis of fire scenarios within specified rooms. A methodology that integrates the fire protection features of a given room into an existing fire risk analysis framework is developed. An important component of this methodology is a model for the time required to detect and suppress a fire in a given room, called the “hazard time.” This model accounts for the reliability of fire detection and suppression equipment, as well as for the characteristic rates of the detection and suppression processes. Because the available evidence for fire detection and suppression in nuclear power plants is sparse and often qualitative, a second component of this methodology is a set of methods needed to employ imprecise information in a statistical analysis. These methods can be applied to a wide variety of problems.