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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.”
Taro Ueki, Forrest B. Brown, D. Kent Parsons, Drew E. Kornreich
Nuclear Science and Engineering | Volume 145 | Number 3 | November 2003 | Pages 279-290
Technical Paper | doi.org/10.13182/NSE03-04
Articles are hosted by Taylor and Francis Online.
The cycle-to-cycle correlation (autocorrelation) in Monte Carlo criticality calculations is analyzed concerning the dominance ratio of fission kernels. The mathematical analysis focuses on how the eigenfunctions of a fission kernel decay if operated on by the cycle-to-cycle error propagation operator of the Monte Carlo stationary source distribution. The analytical results obtained can be summarized as follows: When the dominance ratio of a fission kernel is close to unity, autocorrelation of the k-effective tallies is weak and may be negligible, while the autocorrelation of the source distribution is strong and decays slowly. The practical implication is that when one analyzes a critical reactor with a large dominance ratio by Monte Carlo methods, the confidence interval estimation of the fission rate and other quantities at individual locations must account for the strong autocorrelation. Numerical results are presented for sample problems with a dominance ratio of 0.85-0.99, where Shannon and relative entropies are utilized to exclude the influence of initial nonstationarity.