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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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PR: American Nuclear Society welcomes Senate confirmation of Ted Garrish as the DOE’s nuclear energy secretary
Washington, D.C. — The American Nuclear Society (ANS) applauds the U.S. Senate's confirmation of Theodore “Ted” Garrish as Assistant Secretary for Nuclear Energy at the U.S. Department of Energy (DOE).
“On behalf of over 11,000 professionals in the fields of nuclear science and technology, the American Nuclear Society congratulates Mr. Garrish on being confirmed by the Senate to once again lead the DOE Office of Nuclear Energy,” said ANS President H.M. "Hash" Hashemian.
Joshua Hodson, Robert Spall, Barton Smith
Nuclear Technology | Volume 161 | Number 3 | March 2008 | Pages 268-276
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT08-A3925
Articles are hosted by Taylor and Francis Online.
The effectiveness of five different turbulence models is assessed for the flow across a row of confined cylinders at a pitch-to-diameter ratio of 1.7 and at Reynolds numbers ranging from 2621 to 55 920. Models examined include the one-equation Spalart-Almaras model; two-equation realizable k - [curly epsilon], k - , and shear stress transport models; and a four-equation v2 - f model. Quantities compared against published experimental data include minor loss coefficients, separation angles about cylinders, wake lengths behind cylinders, and streamwise velocity profiles at the periodic inlet/outlet boundaries. Results indicate that each of the models did a reasonable job in predicting the minor loss coefficient as a function of Reynolds number. With the exception of the k - [curly epsilon] model, each was also able to predict the experimentally observed trend of decreasing wake and separation lengths with increasing Reynolds number. In addition, all models also predicted a local minimum in the separation angle about the inner cylinder as a function of Reynolds number, which has also been observed experimentally. Our conclusion is that the v2 - f model performed slightly better at predicting the experimental data than any of the other models examined, although at the computational expense of solving two additional equations.