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Clustering Analysis of Nuclear Proliferation Resistance Measures

Jankovsky, Zachary Kyle
http://rave.ohiolink.edu/etdc/view?acc_num=osu1398354675

Abstract Details

2014, Master of Science, Ohio State University, Nuclear Engineering.
The development of Generation IV nuclear fuel cycles has led to a renewed interest in nuclear proliferation studies for fast-spectrum reactors and recycling systems. One such system, conceptualized specifically for the purpose of proliferation studies, is the Example Sodium-cooled Fast Reactor (ESFR). The ESFR is an actinide burner, capable of using Light Water Reactor (LWR) Spent Fuel (SF) as an input. A reprocessing plant exists on-site, which separates plutonium and uranium from other actinides and fission products, and forms new ESFR fuel assemblies. This production of relatively-pure plutonium presents a proliferation concern. PRCALC was developed at Brookhaven National Laboratory to represent material diversion from an ESFR system as a Markov model, with absorbing states of detection, technical failure, and success from the point of view of the would-be proliferator. Scenarios are created by varying diversion targets, diversion rates, and safeguards conditions on various elements of the fuel cycle. Since there are relatively large uncertainties on the scenario constituents, this thesis focuses on a methodology to create and analyze a large number of PRCALC scenarios which may result from a sensitivity study. These scenarios are clustered using the mean-shift and k-means algorithms, in addition to an adaptive-bandwidth variation of mean-shift. Clustering is performed to allow analysis of important inputs without examining each of potentially thousands of scenarios by hand. A simple case study was performed as an example of how an analyst may use the methodology in a real-world application. A tool is developed and described to mechanize much of the scenario creation, clustering, and analysis processes. This tool is called Ohio State University Proliferation Resistance (OSUPR) and is written in MATLAB as a companion tool to PRCALC. A sample set of scenarios is run from start to finish using OSUPR to show its use to an analyst. Some trends can be seen in the sample set that would be of interest to an analyst.
Richard Denning, Ph.D. (Advisor)
Tunc Aldemir, Ph.D. (Committee Member)
128 p.
Nuclear Engineering
Nuclear Proliferation, Clustering, Mean-Shift, K-means, PRCALC

Recommended Citations

Citations

  • Jankovsky, Z. K. (2014). Clustering Analysis of Nuclear Proliferation Resistance Measures [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398354675

    APA Style (7th edition)

  • Jankovsky, Zachary. Clustering Analysis of Nuclear Proliferation Resistance Measures. 2014. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1398354675.

    MLA Style (8th edition)

  • Jankovsky, Zachary. "Clustering Analysis of Nuclear Proliferation Resistance Measures." Master's thesis, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398354675

    Chicago Manual of Style (17th edition)

osu1398354675
724
© 2014, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.
Release 3.2.12