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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.”
Enrique Castillo, Cristina Solares, Patricia Gómez
Nuclear Science and Engineering | Volume 126 | Number 2 | June 1997 | Pages 158-167
Technical Paper | doi.org/10.13182/NSE97-A24469
Articles are hosted by Taylor and Francis Online.
A new method is presented for propagating uncertainties in complex nuclear power plant safety system fault tree models. The method is especially useful for estimating extreme percentiles and high-probability one-sided confidence intervals of the system unavailability. Likelihood weighing simulation methods, which assign a score to each sample point (x1,... ,xn) to compensate for the differences between the sample and the parent distributions, are used to directly simulate the adequate tail distribution of the probability of the fault tree top event. The polynomial structure of the probability of the top event is exploited to sequentially find upper and lower bounds to simulate each of the basic variables, without the need to invert the polynomial expression. The performance of the proposed method is spectacular when compared with the standard Monte Carlo simulation for tails. Finally, one example of application to a real case is used to illustrate the whole simulation process.