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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.
Valeria Raffuzzi, Rufus Neame, Paul Cosgrove
Nuclear Science and Engineering | Volume 200 | Number 1 | March 2026 | Pages S485-S502
Research Article | doi.org/10.1080/00295639.2025.2458958
Articles are hosted by Taylor and Francis Online.
Deep penetration radiation shielding problems often use Monte Carlo (MC) augmented with weight windows (WWs) to obtain sufficiently low variances in acceptable run times. In this paper, the random ray (RR) method is proposed as an approach to generating WWs. Compared to deterministic alternatives, it allows for straightforward spatial discretization and continuously samples angular phase space. The methods implemented were tested on two shielding problems, examining global variance reduction (GVR) and source-detector variance reduction. In both cases, the figure of merit of the RR-based methods is at least 50 times higher than analog MC, and in the GVR model, it is comparable to that of MAGIC, a popular fully MC approach to WW generation. The methods implemented are also robust to modeling choices like the source of multigroup cross sections (NJOY or MC), scattering anisotropy, and the order of the RR spatial source representation.