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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.”
M. Azam, R. S. Gowda, S. Ganesan
Nuclear Science and Engineering | Volume 152 | Number 3 | March 2006 | Pages 320-324
Technical Paper | doi.org/10.13182/NSE06-A2586
Articles are hosted by Taylor and Francis Online.
The relative differential cross section for testing the validity of the Ramsauer model was previously introduced by Azam and Gowda. This quantity for intermediate energy neutron scattering processes is independent of the details of nuclear interaction and depends only on nuclear radius as a parameter. In this paper we use this quantity to predict the neutron total and differential shape-elastic cross sections. We show that, given the radius parameter, by making a measurement of the differential cross section at one angle, the total shape-elastic cross section (and hence the reaction cross section if the total cross section is known) can be determined to a good degree of accuracy. The forward-angle differential shape-elastic cross section is also well predicted. The method is of very general applicability and will be most useful in those situations where model-based fits to these quantities either do not exist or are unreliable for extrapolation/interpolation.
