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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.
S. Lapaire, T. Bonaccorsi, J-M. Palau
Nuclear Science and Engineering | Volume 200 | Number 1 | March 2026 | Pages S322-S331
Research Article | doi.org/10.1080/00295639.2025.2453787
Articles are hosted by Taylor and Francis Online.
Scientific computing tools, particularly neutronic codes, are employed in the study of nuclear reactor cores. Codes are confronted to the experiments to characterize the deviation (C-E) between the code (C) and the experiment (E). Typically, for power factors, the fission rate recorded in in-core instrumentation is compared to the fission rate simulated by the code. Observed deviations are influenced by uncertainties in both simulation and experimentation. To enhance the interpretation of these deviations, it is essential to thoroughly characterize the sources of uncertainty. Observations and assumptions suggest that a significant share of uncertainty may originate from technological parameters. A prior study conducted at CEA introduced a methodology for calibrating technological parameters through Bayesian inference. While successfully demonstrating the feasibility of such calibration, the methodology revealed limitations in calculation time and number of parameters that could be studied. To overcome these constraints, we propose the development of a deterministic calculation scheme. This paper introduces the lattice part of this scheme, developed with APOLLO3® and validated with TRIPOLI-4®. Additionally, the geometry developed with ALAMOS for perturbing the geometrical parameters is presented, along with the results obtained for the perturbation of the in-core instrumentation’s position. Finally, we demonstrate that simple linear regressions can be used to describe the response of the instrumentation to a perturbation to its position.