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A closer look at the initial NLIC selections—Part 2
In January, the Department of Energy announced its new Nuclear Lifecycle Innovation Campus (NLIC) program, inviting states via a request for information to express their interest in hosting a facility supporting work from the front to the back end of the nuclear fuel cycle.
By April, 26 states had expressed interest in hosting such a facility. At the end of July, the DOE signed memorandums of understanding with five states—Idaho, Louisiana, Oklahoma, Tennessee, and Utah—to more closely explore the possibilities of state-federal partnerships. These MOUs are not firm commitments from either the federal or state governments. Time will tell which—if any—of the five states develop projects through the program. In the meantime, today, we are taking a close look at what Utah, Idaho, Tennessee can offer in terms of a preexisting nuclear sector that could support new fuel cycle developments.
Jae-Woo Ju, Sang-Moon Lee, Kwang-Yong Kim
Nuclear Technology | Volume 181 | Number 2 | February 2013 | Pages 274-281
Technical Paper | Fission Reactors/Thermal Hydraulics | doi.org/10.13182/NT13-A15783
Articles are hosted by Taylor and Francis Online.
The outlet plenum of a pebble bed modular-type gas-cooled nuclear reactor was optimized using three-dimensional Reynolds-averaged Navier-Stokes analysis and optimization techniques. A shear stress transport turbulence model was used as a turbulence closure. Two design variables for the optimization were selected: dimensionless displacement on the horizontal line and the angle of rotation about the center of gravity of the roof support block. The objective function was defined as a pressure drop between the inlet and the outlet of the outlet plenum. Latin hypercube sampling was used for selecting experimental design points within the design space. The objective function value was obtained at each design point through numerical analysis. The results show that the optimal design significantly improved the performance of the outlet plenum with respect to pressure drop. Through optimization, the pressure drop decreased by 11.8% compared to the pressure drop under the reference geometry.