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Centrus, X-energy sign enrichment contract as TRISO-X expands TX-1 campus
Centrus Energy Corp. will be providing X-energy with enrichment services for low-enriched uranium and high-assay, low-enriched uranium to support X-energy’s planned deployments of Xe-100 small modular reactors and TRISO-X fuel, according to the terms of a new contract signed by the companies. The fuel will be produced at Centrus’s American Centrifuge Plant in Piketon, Ohio. In turn, X-energy will provide Centrus with prepayments to help support expanding the capacity of Centrus’s domestic commercial enrichment program.
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.