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Nuclear is ready now
Michael Goff
I don’t think we’ve ever had a busier year in the Office of Nuclear Energy, and it’s probably been decades since we’ve had this much momentum within the overall U.S. nuclear industry.
President Trump and Energy Secretary Wright have made very clear the important role that nuclear must play in meeting our energy needs, and that’s well demonstrated by the four executive orders that the president signed [more than] 375 days ago. In nuclear, we’re now talking about days, not years.
Those EOs set a goal for the United States to quadruple the amount of nuclear that we have. We need to go from the 94 reactors that we have operating right now, which generate roughly 100 gigawatts of electricity, to 400 gigawatts by 2050.
Nicolas Shugart, Jeffrey King, Jake Jacobson
Nuclear Technology | Volume 204 | Number 2 | November 2018 | Pages 147-161
Technical Paper | doi.org/10.1080/00295450.2018.1469350
Articles are hosted by Taylor and Francis Online.
SafeGuards Analysis (SGA) is a toolbox developed to allow engineers and scientists to create detailed simulations of safeguards material control and accountability simulations. SGA accepts material flow data from an external material flow model and can be used with any existing fuel cycle or material control code. This paper examines some new developments to the SGA code that allow the code to consider material losses over long time frames. The first scenario described in this paper examined an enrichment facility consisting of two material balance areas (MBAs). Cumulative sum and basic control chart tests were evaluated for a case involving a loss of material from both MBAs simultaneously and a case in which material is removed from the facility over a timescale of double the one that the tests were calibrated to detect. A second scenario represents an entire fuel cycle consisting of four MBAs and two materials of interest (low-enriched uranium and plutonium). This scenario evaluated the calibrated safeguards system with three blind unidentified stream cases, with the goal of determining the calibrated system’s ability to detect where the material loss occurred in each case. SGA was able to produce the expected results for all of the examples examined in this paper, demonstrating that modules produced using the toolbox are capable of examining larger systems in realistic multi-MBA scenarios.