Publications

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Robust and reliable quantitative proliferation assessment tools have the potential to contribute significantly to a strengthened nonproliferation regime and to the future deployment of nuclear fuel cycle technologies. Efforts to quantify proliferation resistance have thus far met with limited success due to the inherent subjectivity of the problem and interdependencies between attributes that lead to proliferation resistance. We suggest that these limitations flow substantially from weaknesses in the foundations of existing methodologies--the initial data inputs. In most existing methodologies, little consideration has been given to the utilization of varying types of inputs--particularly the mixing of subjective and objective data--or to identifying, understanding, and untangling relationships and dependencies between inputs. To address these concerns, a model set of inputs is suggested that could potentially be employed in multiple approaches. We present an input classification scheme and the initial results of testing for relationships between these inputs. We will discuss how classifying and testing the relationship between these inputs can help strengthen tools to assess the proliferation risk of nuclear fuel cycle processes, systems, and facilities.

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Proliferation resistance features that reduce the likelihood of diversion of nuclear materials from the civilian nuclear power fuel cycle are critical for a global nuclear future. A framework that monitors process information continuously can demonstrate the ability to resist proliferation by measuring and reducing diversion risk, thus ensuring the legitimate use of the nuclear fuel cycle. The automation of new nuclear facilities requiring minimal manual operation makes this possible by generating instantaneous system state data that can be used to track and measure the status of the process and material at any given time. Sandia National Laboratories (SNL) and the Japan Atomic Energy Agency (JAEA) are working in cooperation to develop an advanced transparency framework capable of assessing diversion risk in support of overall plant transparency. The ''diversion risk'' quantifies the probability and consequence of a host nation diverting nuclear materials from a civilian fuel cycle facility. This document introduces the details of the diversion risk quantification approach to be demonstrated in the fuel handling training model of the MONJU Fast Reactor.

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Due to increasing concerns over the buildup of long-lived transuranic isotopes in spent nuclear fuel waste, attention has been given in recent years to technologies that can burn up these species. The separation and transmutation of transuranics is part of a solution to decreasing the volume and heat load of nuclear waste significantly to increase the repository capacity. A fusion neutron source can be used for transmutation as an alternative to fast reactor systems. Sandia National Laboratories is investigating the use of a Z-Pinch fusion driver for this application. This report summarizes the initial design and engineering issues of this ''In-Zinerator'' concept. Relatively modest fusion requirements on the order of 20 MW can be used to drive a sub-critical, actinide-bearing, fluid blanket. The fluid fuel eliminates the need for expensive fuel fabrication and allows for continuous refueling and removal of fission products. This reactor has the capability of burning up 1,280 kg of actinides per year while at the same time producing 3,000 MWth. The report discusses the baseline design, engineering issues, modeling results, safety issues, and fuel cycle impact.

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