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The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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ANS Student Conference 2025
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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.”
C. van der Hoeven, E. Schneider, L. Leal
Nuclear Science and Engineering | Volume 179 | Number 1 | January 2015 | Pages 1-21
Technical Paper | doi.org/10.13182/NSE13-78
Articles are hosted by Taylor and Francis Online.
There is a need for improved molybdenum isotope covariance data for use in modeling a new uranium-molybdenum fuel form to be produced at the Y-12 National Security Complex (Y-12). Covariance data correlate the uncertainty in an isotopic cross section at a particular energy to uncertainties at other energies. While high-fidelity covariance data exist for key isotopes, the low-fidelity covariance data available for most isotopes, including the natural molybdenum isotopes considered in this work, are derived from integral measurements without meaningful correlation between energy regions. This paper provides a framework for using the Bayesian R-matrix code SAMMY to derive improved isotopic resonance region covariance data from elemental experimental cross-section data. These resonance-wise covariance data were combined with integral uncertainty data from the Atlas of Neutron Resonances, uncertainty data generated via a dispersion method, and high-energy uncertainty data previously generated with the Empire-KALMAN code to produce an improved set of covariance data for the natural molybdenum isotopes. The improved covariance data sets, along with the associated resonance parameters, were inserted into JENDL4.0 data files for the molybdenum isotopes for use in data processing and modeling codes. Additionally, a series of critical experiments featuring the new U(19.5%)-10Mo fuel form produced at Y-12 was designed. Along with existing molybdenum sensitive critical experiments, these were used to compare the performance of the new molybdenum covariance data against the existing low-fidelity evaluation. The new covariance data were found to result in reduced overall bias, reduced bias due to the molybdenum isotopes, and improved goodness of fit of computational to experimental results.