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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.”
Jeffery D. Densmore, Edward W. Larsen
Nuclear Science and Engineering | Volume 146 | Number 2 | February 2004 | Pages 121-140
Technical Paper | doi.org/10.13182/NSE04-A2398
Articles are hosted by Taylor and Francis Online.
A new variational variance reduction (VVR) technique is developed for improving the efficiency of Monte Carlo multigroup nuclear reactor eigenvalue and eigenfunction calculations. The VVR method employs a variational functional, which requires detailed estimates of both the forward and adjoint fluxes. The direct functional, employed in standard Monte Carlo calculations, requires only limited information concerning the forward flux. The variational functional requires global information about the forward and adjoint fluxes and hence is more expensive to evaluate but is more accurate than the direct functional. In calculations, this increased accuracy outweighs the extra expense, resulting in a more efficient Monte Carlo simulation. In our work, we evaluate the variational functional using Monte Carlo-calculated forward flux estimates and deterministically calculated adjoint flux estimates. Also, we represent the adjoint flux as a low-order polynomial in space and angle, which is accurate for diffusive systems. (In such systems, which are common in reactor analysis problems, the angular flux is locally nearly linear in space and angle.) Using this adjoint representation, we develop specific VVR methods for eigenvalue problems, in which an estimate of the eigenvalue k in a criticality calculation is desired, and eigenfunction problems, in which an estimate of a detector response due to a fission neutron source during a criticality calculation is desired. The resulting VVR method is very efficient for the problems of interest. With a set of example problems, we demonstrate the increased efficiency of the VVR method over standard Monte Carlo.