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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.”
Cody J. Permann, Andrea M. Jokisaari, Michael R. Tonks, Daniel Schwen, Derek R. Gaston, Fande Kong, Robert Hiromoto, Richard C. Martineau
Nuclear Technology | Volume 207 | Number 7 | July 2021 | Pages 885-904
Technical Paper | doi.org/10.1080/00295450.2020.1843893
Articles are hosted by Taylor and Francis Online.
The ability to identify features within finite element simulations and track them over time is necessary for understanding and quantifying complex behaviors as disparate as turbulent vortices in a flow field to microstructure evolution. We extend our previous research on feature identification in parallel unstructured meshes with the novel ability to maintain feature distinctness by dynamically remapping individual features to new simulation variables as the simulation evolves. We utilize this capability to drastically reduce the number of variables required in a simulation while maintaining the same fidelity as simulations without these reductions. We present this novel remapping algorithm and the corresponding implementation within the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. We demonstrate the utility of the method with a novel phase-field model of irradiation-driven grain subdivision in UO2. Grain population statistics are tracked over time, and a dynamically stable population of grains with a reduced size evolves. These results indicate that the small grain sizes observed in high-burnup UO2 can be explained by this mechanism.