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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.
Hesham R. Nasif, Fukuzo Masuda, Hidetsugu Morota, Hitomasa Iida, Satoshi Sato, Chikara Konno
Nuclear Technology | Volume 180 | Number 1 | October 2012 | Pages 89-102
Technical Paper | Radiation Protection | doi.org/10.13182/NT12-A14521
Articles are hosted by Taylor and Francis Online.
GEOMIT is a computer-aided design (CAD)/MCNP conversion interface code. It was developed to automatically generate Monte Carlo geometrical data from CAD data due to the difference in the representation scheme. GEOMIT is capable of importing as well as exporting different CAD formats. GEOMIT has the capability to produce solid cells as well as void cells without using the complement operator. While loading the CAD shapes (solids), each shape is assigned a material number and density according to its color on the original CAD data. A shape fixing process has been applied to cure the errors in the CAD data. Vertex location correctness is evaluated first, and then a removal of free edges and removal of small faces processes. A binary space portioning tree technique is used to automatically split complicated solids into simpler cells to avoid excessively complicated cells to allow MCNP to run faster. MCNP surfaces are subjected to an automatic reduction before creating the model. CAD data of the ITER benchmark model have been converted successfully to MCNP geometrical input. MCNP input model validations have been carried out by checking lost particles and comparing volumes calculated by MCNP to those of the original CAD data. Different test cases have been evaluated for ITER, including blanket first wall heat loading calculations, surface fluxes, and volume fluxes at different divertor regions as well as toroidal field coil heating.