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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.”
Aaron M. Krueger (Texas A&M), Vincent A. Mousseau (SNL), Yassin A. Hassan (Texas A&M)
Proceedings | Advances in Thermal Hydraulics 2018 | Orlando, FL, November 11-15, 2018 | Pages 1003-1014
Applying solution verification methods to computational fluid dynamic (CFD) simulations has substantially increased within the past three decades, especially with the introduction of the grid convergence index (GCI) metric. Since then, numerical and meshing schemes and the governing equations have increased in complexity, which makes understanding the discretization error for a simulation even more complex. Greater understanding of how discretization error develops from local truncation error (LTE) within a simulation can provide additional evidence to determine the adequacy of the error model used in current solution verification methods. It also provides meshing strategies to improve the adequacy of the error model. When the error model is determined to be adequate, additional confidence is added to the solution verification studies. One way of understanding how discretization error develops from LTE is to quantify the LTE and track how it propagates through time and space using the partial differential equation. Propagating LTE through time and space was completed using two methods: difference of difference quotients (DDQ) method and method of manufactured solutions-informed modified equation analysis (MMS-informed MEA) method. These methods justify the adequacy of the error model implemented in most Richardson extrapolation (RE) methods for the implemented numerical and meshing scheme. In addition, an example problem is provided that showed the implementation of both discretization error estimation methods using a first-order method and a uniform, structured mesh. The discretization error estimation results were then compared to the exact discretization error.