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Nuclear Energy Conference & Expo (NECX)
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.”
Yung-An Chao
Nuclear Science and Engineering | Volume 72 | Number 1 | October 1979 | Pages 1-8
Technical Paper | doi.org/10.13182/NSE79-A19304
Articles are hosted by Taylor and Francis Online.
The adjustment of group cross sections fitting integral measurements is viewed as a process of estimating theoretical and/or experimental negligence errors to bring statistical consistency to the integral and differential data so that they can be combined to form an enlarged ensemble, based on which an improved estimation of the physical constants can be made. A three-step approach is suggested, and its formalism of general validity is developed. In step one, the data of negligence error are extracted from the given integral and differential data. The method of extraction is based on the concepts of prior probability and information entropy. It automatically leads to vanishing negligence error as the two sets of data are statistically consistent. The second step is to identify the sources of negligence error and adjust the data by an amount compensating for the extracted negligence discrepancy. In the last step, the two data sets, already adjusted to mutual consistency, are combined as a single unified ensemble. Standard methods of statistics can then be applied to reestimate the physical constants.
