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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.
Ivan Gajev, Tomasz Kozlowski, Yunlin Xu, Thomas Downar
Nuclear Technology | Volume 180 | Number 3 | December 2012 | Pages 383-398
Technical Paper | Special Issue on the Initial Release of MCNP6 / Fission Reactors | doi.org/10.13182/NT12-A15351
Articles are hosted by Taylor and Francis Online.
Unstable behavior of boiling water reactors (BWRs) is known to occur during operation at certain power and flow conditions. This paper reports on an uncertainty study of the impact of various parameters on the prediction of the stability of the BWR within the framework of the Organisation for Economic Co-operation and Development Ringhals Unit 1 (Ringhals-1) Stability Benchmark. The time domain code TRACE/PARCS was used in the analysis. The paper is divided into two parts: a sensitivity study on numerical parameters (nodalization, time step, etc.) and an uncertainty analysis of the stability event. The sensitivity study was based on a space-time converged solution, and the most important neutronic and thermal-hydraulic parameters were identified for parameterization. The uncertainty calculation was then performed using the well-established propagation of input errors methodology. Finally, the Spearman Rank method was used to identify the most influential parameters affecting the stability of Ringhals-1.