Publications

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A simplified ESBWR MELCOR model was developed to track the transport of iodine released from damaged reactor fuel in a hypothesized core damage accident. To account for the effects of iodine pool chemistry, radiolysis of air and cable insulation, and surface coatings (i.e., paint) the iodine pool model in MELCOR was activated. Modifications were made to MELCOR to add sodium pentaborate as a buffer in the iodine pool chemistry model. An issue of specific interest was whether iodine vapor removed from the drywell vapor space by the PCCS heat exchangers would be sequestered in water pools or if it would be rereleased as vapor back into the drywell. As iodine vapor is not included in the deposition models for diffusiophoresis or thermophoresis in current version of MELCOR, a parametric study was conducted to evaluate the impact of a range of iodine removal coefficients in the PCCS heat exchangers. The study found that higher removal coefficients resulted in a lower mass of iodine vapor in the drywell vapor space.

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Because of past military operations, lack of upkeep and looting there are now enormous radioactive waste problems in Iraq. These waste problems include destroyed nuclear facilities, uncharacterized radioactive wastes, liquid radioactive waste in underground tanks, wastes related to the production of yellow cake, sealed radioactive sources, activated metals and contaminated metals that must be constantly guarded. Iraq currently lacks the trained personnel, regulatory and physical infrastructure to safely and securely manage these facilities and wastes. In 2005 the International Atomic Energy Agency (IAEA) agreed to organize an international cooperative program to assist Iraq with these issues. Soon after, the Iraq Nuclear Facility Dismantlement and Disposal Program (the NDs Program) was initiated by the U.S. Department of State (DOS) to support the IAEA and assist the Government of Iraq (GOI) in eliminating the threats from poorly controlled radioactive materials. The Iraq NDs Program is providing support for the IAEA plus training, consultation and limited equipment to the GOI. The GOI owns the problems and will be responsible for implementation of the Iraq NDs Program. Sandia National Laboratories (Sandia) is a part of the DOS's team implementing the Iraq NDs Program. This report documents Sandia's support of the Iraq NDs Program, which has developed into three principal work streams: (1) training and technical consultation; (2) introducing Iraqis to modern decommissioning and waste management practices; and (3) supporting the IAEA, as they assist the GOI. Examples of each of these work streams include: (1) presentation of a three-day training workshop on 'Practical Concepts for Safe Disposal of Low-Level Radioactive Waste in Arid Settings;' (2) leading GOI representatives on a tour of two operating low level radioactive waste disposal facilities in the U.S.; and (3) supporting the IAEA's Technical Meeting with the GOI from April 21-25, 2008. As noted in the report, there was significant teaming between the various participants to best help the GOI. On-the-ground progress is the focus of the Iraq NDs Program and much of the work is a transfer of technical and practical skills and knowledge that Sandia uses day-to-day. On-the-ground progress was achieved in July of 2008 when the GOI began the physical cleanup and dismantlement of the Active Metallurgical Testing Laboratory (LAMA) facility at Al Tuwaitha, near Baghdad.

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This is a progress report on polynomial system solving for statistical modeling. This is a progress report on polynomial system solving for statistical modeling. This quarter we have developed our first model of shock response data and an algorithm for identifying the chamber cone containing a polynomial system in n variables with n+k terms within polynomial time - a significant improvement over previous algorithms, all having exponential worst-case complexity. We have implemented and verified the chamber cone algorithm for n+3 and are working to extend the implementation to handle arbitrary k. Later sections of this report explain chamber cones in more detail; the next section provides an overview of the project and how the current progress fits into it.

This report presents progress on identifying and classifying features involving combustion in turbulent flow using principal component analysis (PCA) and k-means clustering using an in situ analysis framework. We describe a process for extracting temporally- and spatially-varying information from the simulation, classifying the information, and then applying the classification algorithm to either other portions of the simulation not used for training the classifier or further simulations. Because the regions classified as being of interest take up a small portion of the overall simulation domain, it will consume fewer resources to perform further analysis or save these regions at a higher fidelity than previously possible. The implementation of this process is partially complete and results obtained from PCA of test data is presented that indicates the process may have merit: the basis vectors that PCA provides are significantly different in regions where combustion is occurring and even when all 21 species of a lifted flame simulation are correlated the computational cost of PCA is minimal. What remains to be determined is whether k-means (or other) clustering techniques will be able to identify combined combustion and flow features with an accuracy that makes further characterization of these regions feasible and meaningful.