Publications

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Nuclear fuel reprocessing plants contain a wealth of plant monitoring data including material measurements, process monitoring, administrative procedures, and physical protection elements. Future facilities are moving in the direction of highly-integrated plant monitoring systems that make efficient use of the plant data to improve monitoring and reduce costs. The Separations and Safeguards Performance Model (SSPM) is an analysis tool that is used for modeling advanced monitoring systems and to determine system response under diversion scenarios. This report both describes the architecture for such a future monitoring system and present results under various diversion scenarios. Improvements made in the past year include the development of statistical tests for detecting material loss, the integration of material balance alarms to improve physical protection, and the integration of administrative procedures. The SSPM has been used to demonstrate how advanced instrumentation (as developed in the Material Protection, Accounting, and Control Technologies campaign) can benefit the overall safeguards system as well as how all instrumentation is tied into the physical protection system. This concept has the potential to greatly improve the probability of detection for both abrupt and protracted diversion of nuclear material.

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The future of reprocessing in the United States is strongly driven by plant economics. With increasing safeguards, security, and safety requirements, future plant monitoring systems must be able to demonstrate more efficient operations while improving the current state of the art. The goal of this work was to design and examine the incorporation of advanced plant monitoring technologies into safeguards systems with attention to the burden on the operator. The technologies examined include micro-fluidic sampling for more rapid analytical measurements and spectroscopy-based techniques for on-line process monitoring. The Separations and Safeguards Performance Model was used to design the layout and test the effect of adding these technologies to reprocessing. The results here show that both technologies fill key gaps in existing materials accountability that provide detection of diversion events that may not be detected in a timely manner in existing plants. The plant architecture and results under diversion scenarios are described. As a tangent to this work, both the AMUSE and SEPHIS solvent extraction codes were examined for integration in the model to improve the reality of diversion scenarios. The AMUSE integration was found to be the most successful and provided useful results. The SEPHIS integration is still a work in progress and may provide an alternative option.

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Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.

Imported oil exacerabates our trade deficit and funds anti-American regimes. Nuclear Energy (NE) is a demonstrated technology with high efficiency. NE's two biggest political detriments are possible accidents and nuclear waste disposal. For NE policy, proliferation is the biggest obstacle. Nuclear waste can be reduced through reprocessing, where fuel rods are separated into various streams, some of which can be reused in reactors. Current process developed in the 1950s is dirty and expensive, U/Pu separation is the most critical. Fuel rods are sheared and dissolved in acid to extract fissile material in a centrifugal contactor. Plants have many contacts in series with other separations. We have taken a science and simulation-based approach to develop a modern reprocessing plant. Models of reprocessing plants are needed to support nuclear materials accountancy, nonproliferation, plant design, and plant scale-up.

The Separations and Safeguards Performance Model is a reprocessing plant model that has been developed for safeguards analyses of future plant designs. The model has been modified to integrate bulk process monitoring data with traditional plutonium inventory balances to evaluate potential advanced safeguards systems. Taking advantage of the wealth of operator data such as flow rates and mass balances of bulk material, the timeliness of detection of material loss was shown to improve considerably. Four diversion cases were tested including both abrupt and protracted diversions at early and late times in the run. The first three cases indicated alarms before half of a significant quantity of material was removed. The buildup of error over time prevented detection in the case of a protracted diversion late in the run. Some issues related to the alarm conditions and bias correction will need to be addressed in future work. This work both demonstrates the use of the model for performing diversion scenario analyses and for testing advanced safeguards system designs.

Near Real Time Accountability (NRTA) of actinides at high precision in reprocessing plants has been a long sought-after goal in the safeguards community. Achieving this goal is hampered by the difficulty of making precision measurements in the reprocessing environment, equipment cost, and impact to plant operations. Thus the design of future reprocessing plants requires an optimization of different approaches. The Separations and Safeguards Performance Model, developed at Sandia National Laboratories, was used to evaluate a number of NRTA strategies in a UREX+ reprocessing plant. Strategies examined include the incorporation of additional actinide measurements of internal plant vessels, more use of process monitoring data, and the option of periodic draining of inventory to key tanks. Preliminary results show that the addition of measurement technologies can increase the overall measurement uncertainty due to additional error propagation, so care must be taken when designing an advanced system. Initial results also show that relying on a combination of different NRTA techniques will likely be the best option. The model provides a platform for integrating all the data. The modeling results for the different NRTA options under various material loss conditions will be presented.

Traditional safeguards and security design for fuel cycle facilities is done separately and after the facility design is near completion. This can result in higher costs due to retrofits and redundant use of data. Future facilities will incorporate safeguards and security early in the design process and integrate the systems to make better use of plant data and strengthen both systems. The purpose of this project was to evaluate the integration of materials control and accounting (MC&A) measurements with physical security design for a nuclear reprocessing plant. Locations throughout the plant where data overlap occurs or where MC&A data could be a benefit were identified. This mapping is presented along with the methodology for including the additional data in existing probabilistic assessments to evaluate safeguards and security systems designs.

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