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Animation depicts Hanford’s direct-feed waste treatment process
The Department of Energy’s Office of Environmental Management (EM) has released an animated video of the Direct-Feed Low-Activity Waste (DFLAW) Program at the Hanford Site near Richland, Wash. The video shows the integrated procedure for treating Hanford’s radioactive tank waste, a process EM says is a key component of its strategic cleanup vision.
View the animation here.
Nicolas Shugart, Jeffrey King, Jake Jacobson
Nuclear Technology | Volume 204 | Number 2 | November 2018 | Pages 147-161
Technical Paper | dx.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.