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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.”
Ho Jin Park, Hyung Jin Shim, Han Gyu Joo, Chang Hyo Kim
Nuclear Science and Engineering | Volume 175 | Number 1 | September 2013 | Pages 28-43
Technical Paper | doi.org/10.13182/NSE12-25
Articles are hosted by Taylor and Francis Online.
The B1 theory-augmented Monte Carlo (MC) method has been recently presented as a new MC method to generate homogenized few-group diffusion theory constants (FGCs) of nuclear systems such as a fuel pin cell or a fuel assembly (FA). It is demonstrated that it can produce FGCs that are well qualified for highly accurate two-step core neutronics analyses. However, it is unavoidable for FGCs from it to carry uncertainties that are ascribed to statistical uncertainties, as well as nuclear cross-section and nuclide number density input data uncertainties, of MC calculations pivotal in the new MC method. In order to evaluate the impact of these uncertainties of FGCs on the core neutronics design applications, therefore, it becomes essential to present their uncertainties quantitatively in addition to FGCs themselves. The purpose of this paper is to develop a mathematical formulation for separately quantifying contributions of statistical and input data uncertainties to uncertainties of FGCs from the new MC method and to illustrate its applications for computing uncertainties of the burnup-dependent FGCs. To do so, the basic mathematical equations linking input uncertainties to output uncertainties are established in terms of an arbitrary single-step computational problem that requires either a MC or a deterministic method calculation. It is shown that repeated applications of the basic equations stepwise from steps 1 through 5 of the new MC method at the very beginning of the preset burnup intervals lead to a desired formulation that can not only quantify uncertainties of the burnup-dependent FGCs but also separately identify individual contributions of uncertain sources to them. The formulation is incorporated into the Seoul National University MC code McCARD. It is then used to compute the uncertainties of the burnup-dependent homogenized two-group constants of a low-enriched UO2 fuel pin cell and a pressurized water reactor FA on the assumption that nuclear cross-section input data of 235U and 238U have uncertainties as reflected in covariance files of the JENDL 3.3 library. The effects of the cross-section input data uncertainties of the two U isotopes on the uncertainties of two-group constants and on those of neutron multiplication factors of the UO2 pin cell and the FA are quantified. The utilities of uncertainty quantifications are then discussed from the standpoint of evaluation of feasibility of nuclear design results of new reactor systems and improvement of the nuclear data including covariance files of the evaluated nuclear data libraries.