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Going Nuclear: Notes from the officially unofficial book tour
I work in the analytical labs at one of Europe’s oldest and largest nuclear sites: Sellafield, in northwestern England. I spend my days at the fume hood front, pipette in one hand and radiation probe in the other (and dosimeter pinned to my chest, of course). Outside the lab, I have a second job: I moonlight as a writer and public speaker. My new popular science book—Going Nuclear: How the Atom Will Save the World—came out last summer, and it feels like my life has been running at full power ever since.
Zhiyuan Feng, Jingang Liang, Wenli Guo, Kan Wang
Nuclear Science and Engineering | Volume 200 | Number 1 | March 2026 | Pages S122-S130
Research Article | doi.org/10.1080/00295639.2024.2403896
Articles are hosted by Taylor and Francis Online.
Because of their favorable thermal conductivity and commendable fuel performance, dispersed fuel elements have been widely adopted in research reactors. However, the geometric complexity resulting from the high packing density of dispersed fuel poses challenges to current geometric modeling methods. Various implicit and explicit modeling techniques have been implemented in Monte Carlo codes. Implicit methods struggle to achieve the correct packing fraction and, therefore, lack accuracy. In this paper, we introduce the Optimized Dropping and Rolling and Virtual Surface method for precise and efficient geometric modeling of such structures. Simultaneously, we apply this novel method to the packing process of an annular container. Test results across various packing fraction cases demonstrate that our modified Optimized Dropping and Rolling method significantly enhances packing efficiency, surpassing the Distinct Element Method hundreds of times.