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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.”
Balazs Molnar, Gabor Tolnai, David Legrady
Nuclear Science and Engineering | Volume 190 | Number 1 | April 2018 | Pages 56-72
Technical Paper | doi.org/10.1080/00295639.2017.1413876
Articles are hosted by Taylor and Francis Online.
A novel particle tracking framework is introduced in this paper that utilizes null-collisions to sample distance to collision in Monte Carlo particle transport problems. The sampling process is described in the most general form as it covers all of the main developments concerning the Woodcock method (delta tracking). We show that none of the previously suggested modifications are optimal in terms of either variance or efficiency. Variance analysis is provided for a general transport problem along with the estimation of computational cost. Simplified models with analytic solutions are further investigated and propositions for optimal settings are discussed based on the derived equations. A well-known variance reduction technique, exponential transform, is found to be a limiting case of the biased Woodcock tracking method and comparison shows the proposed framework may outperform the exponential transform in real-case scenarios.