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GLE gets incentives, draft EIS
The governments of Kentucky and McCracken County have granted preliminary approval to Global Laser Enrichment for a comprehensive incentive package to support the development of the North Carolina–based company’s planned Paducah Laser Enrichment Facility in the western part of the state. The performance-based incentive package would provide as much as $98.9 million in tax incentives and other economic incentives—provided that GLE reaches the required thresholds in investments and job creation.
In addition, the Nuclear Regulatory Commission, in cooperation with the U.S. Army Corps of Engineers, has completed a draft environmental impact statement (EIS) in response to GLE’s application to construct and operate the PLEF. Members of the public can submit comments on the draft EIS by May 11 for consideration by the NRC.
Tom Burr, Jeremy Conlin, Jianwei Hu, Jack Galloway, Vladimir Henzl, Howard Menlove, Martyn Swinhoe, Stephen Tobin, Holly Trellue, Timothy Ulrich
Nuclear Science and Engineering | Volume 172 | Number 2 | October 2012 | Pages 180-192
Technical Paper | doi.org/10.13182/NSE11-73
Articles are hosted by Taylor and Francis Online.
Estimating plutonium (Pu) mass in spent nuclear fuel assemblies (SFAs) helps inspectors ensure that no Pu is diverted. Therefore, nondestructive assay (NDA) methods are being developed to assay Pu mass in SFAs. Uncertainty quantification is an important task in most assay methods, and particularly for SFA assay. A computer model (MCNPX) is being used to predict isotope masses and the spatial distribution of masses in virtual SFAs for 64 combinations of initial fuel enrichment (IE), fuel utilization [burnup (BU)], and cooling time (CT) values. Additional MCNPX modeling for the same 64 virtual SFAs provided the expected detector responses (DRs) for several NDA techniques such as the passive neutron albedo reactivity method and the 252Cf interrogation with prompt neutrons method.A previous paper describes one uncertainty quantification approach involving Monte Carlo (MC) simulation using individually any of six new NDA options together with IE, BU, and CT. This paper provides an interpretation of the MC approach that is suited for a numerical Bayesian alternative, separately assesses the impact of MCNPX interpolation error, and compares several options to use subsets of IE, BU, CT, and one DR.
