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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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General Kenneth Nichols and the Manhattan Project
Nichols
The Oak Ridger has published the latest in a series of articles about General Kenneth D. Nichols, the Manhattan Project, and the 1954 Atomic Energy Act. The series has been produced by Nichols’ grandniece Barbara Rogers Scollin and Oak Ridge (Tenn.) city historian David Ray Smith. Gen. Nichols (1907–2000) was the district engineer for the Manhattan Engineer District during the Manhattan Project.
As Smith and Scollin explain, Nichols “had supervision of the research and development connected with, and the design, construction, and operation of, all plants required to produce plutonium-239 and uranium-235, including the construction of the towns of Oak Ridge, Tennessee, and Richland, Washington. The responsibility of his position was massive as he oversaw a workforce of both military and civilian personnel of approximately 125,000; his Oak Ridge office became the center of the wartime atomic energy’s activities.”
Faouzi Hakimi, Claude Brayer, Amandine Marrel, Fabrice Gamboa, Benoît Habert
Nuclear Science and Engineering | Volume 198 | Number 3 | March 2024 | Pages 578-591
Research Article | doi.org/10.1080/00295639.2023.2197838
Articles are hosted by Taylor and Francis Online.
In the framework of risk assessment in nuclear accidents, simulation tools are widely used to understand and model physical phenomena. These simulation tools take into account a large number of uncertain input parameters. We often use Monte Carlo–type methods to explore their range of variation: The input space is randomly sampled, and a code run is performed on each sampled point. However, some of these code runs may fail to converge. Analyzing these code failures to understand which of the inputs have the most influence on them leads to a better understanding of how the code works. It also intends to improve the robustness of the simulation software and code computations. For this purpose, we propose two complementary approaches performing a statistical analysis of the code failures. The first approach is based on goodness-of-fit tests and compares conditional probability distributions according to code failures to a reference one. A second approach, based on a dependence measure named the Hilbert-Schmidt Independence Criterion, provides another way to measure the global dependence between the inputs and the code failures. The development of this methodology is carried out in the context of severe nuclear accidents. More especially, the presented methods are applied for the study of the simulation code MC3D, which simulates the fuel-coolant interaction in a severe nuclear accident context.