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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.”
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Turbulent mixing of different temperature fluids in T-junction geometries is a technically critical issue for the safe operation of power plants. Due to the strong flow deformation, the scale separation assumption is not respected locally, limiting the applicability of classic unsteady Reynolds-averaged Navier-Stokes (URANS) models, which are unable to deliver the required accuracy in the prediction of temperature fluctuations. On the contrary, eddy resolving methods, and in particular large eddy simulation (LES), can provide reliable results at a computational cost that is still impracticable for the industry.

A robust second-generation URANS (2G-URANS) model was recently proposed at MIT, which aims at locally resolving complex flow structures. In the present paper, the performance of the structure-based (STRUCT) model is assessed specifically against low Reynolds number (??????=4,485) DNS data on a T-junction case. Velocity and temperature distributions in the mixing region are compared between URANS, STRUCT and LES solutions and the reference DNS data. The STRUCT model demonstrates significant advancement in the ability to model the thermal striping phenomena. Its application produces accurate predictions of the flow behavior on coarse URANS computational grids, with a large cost saving in comparison to LES.