Publications

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Efforts are being pursued to develop and qualify a system-level model of a reactor core isolation (RCIC) steam-turbine-driven pump. The model is being developed with the intent of employing it to inform the design of experimental configurations for full-scale RCIC testing. The model is expected to be especially valuable in sizing equipment needed in the testing. An additional intent is to use the model in understanding more fully how RCIC apparently managed to operate far removed from its design envelope in the Fukushima Daiichi Unit 2 accident. RCIC modeling is proceeding along two avenues that are expected to complement each other well. The first avenue is the continued development of the system-level RCIC model that will serve in simulating a full reactor system or full experimental configuration of which a RCIC system is part. The model reasonably represents a RCIC system today, especially given design operating conditions, but lacks specifics that are likely important in representing the off-design conditions a RCIC system might experience in an emergency situation such as a loss of all electrical power. A known specific lacking in the system model, for example, is the efficiency at which a flashing slug of water (as opposed to a concentrated jet of steam) could propel the rotating drive wheel of a RCIC turbine. To address this specific, the second avenue is being pursued wherein computational fluid dynamics (CFD) analyses of such a jet are being carried out. The results of the CFD analyses will thus complement and inform the system modeling. The system modeling will, in turn, complement the CFD analysis by providing the system information needed to impose appropriate boundary conditions on the CFD simulations. The system model will be used to inform the selection of configurations and equipment best suitable of supporting planned RCIC experimental testing. Preliminary investigations with the RCIC model indicate that liquid water ingestion by the turbine decreases the developed turbine torque; the RCIC speed then slows, and thus the pump flow rate to the RPV decreases. Subsequently, RPV water level decreases due to continued boiling and the liquid fraction flowing to the RCIC decreases, thereby accelerating the RCIC and refilling the RPV. The feedback cycle then repeats itself and/or reaches a quasi-steady equilibrium condition. In other words, the water carry-over is limited by cyclic RCIC performance degradation, and hence the system becomes self-regulating. The indications achieved to date with the system model are more qualitative than quantitative. The avenues being pursued to increase the fidelity of the model are expected to add quantitative realism. The end product will be generic in the sense that the RCIC model will be incorporable within the larger reactor coolant system model of any nuclear power plant or experimental configuration.

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This is to serve as verification that the Center 6200 experimental pieces supplied to the Technology Training and Demonstration Area within the Center of Global Security and Cooperation are indeed unclassified unlimited released for viewing.

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This document provides Sandia National Laboratories’ meeting notes and presentations at the Society for Modeling and Simulation Power Plant Simulator conference in Jacksonville, FL. The conference was held January 26-28, 2015, and SNL was invited by the U.S. nuclear industry to present Fukushima modeling insights and lessons learned.

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This paper describes the knowledge advancements from the uncertainty analysis for the State-of- the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout accident scenario at the Peach Bottom Atomic Power Station. This work assessed key MELCOR and MELCOR Accident Consequence Code System, Version 2 (MACCS2) modeling uncertainties in an integrated fashion to quantify the relative importance of each uncertain input on potential accident progression, radiological releases, and off-site consequences. This quantitative uncertainty analysis provides measures of the effects on consequences, of each of the selected uncertain parameters both individually and in interaction with other parameters. The results measure the model response (e.g., variance in the output) to uncertainty in the selected input. Investigation into the important uncertain parameters in turn yields insights into important phenomena for accident progression and off-site consequences. This uncertainty analysis confirmed the known importance of some parameters, such as failure rate of the Safety Relief Valve in accident progression modeling and the dry deposition velocity in off-site consequence modeling. The analysis also revealed some new insights, such as dependent effect of cesium chemical form for different accident progressions. (auth)

This paper describes the convergence of MELCOR Accident Consequence Code System, Version 2 (MACCS2) probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout scenario at the Peach Bottom Atomic Power Station. The consequence metrics evaluated are individual latent-cancer fatality (LCF) risk and individual early fatality risk. Consequence results are presented as conditional risk (i.e., assuming the accident occurs, risk per event) to individuals of the public as a result of the accident. In order to verify convergence for this uncertainty analysis, as recommended by the Nuclear Regulatory Commission’s Advisory Committee on Reactor Safeguards, a ‘high’ source term from the original population of Monte Carlo runs has been selected to be used for: (1) a study of the distribution of consequence results stemming solely from epistemic uncertainty in the MACCS2 parameters (i.e., separating the effect from the source term uncertainty), and (2) a comparison between Simple Random Sampling (SRS) and Latin Hypercube Sampling (LHS) in order to validate the original results obtained with LHS. Three replicates (each using a different random seed) of size 1,000 each using LHS and another set of three replicates of size 1,000 using SRS are analyzed. The results show that the LCF risk results are well converged with either LHS or SRS sampling. The early fatality risk results are less well converged at radial distances beyond 2 miles, and this is expected due to the sparse data (predominance of “zero” results).

A proposed method is considered to classify the regions in the close neighborhood of selected measurements according to the ratio of two radionuclides measured from either a radioactive plume or a deposited radionuclide mixture. The subsequent associated locations are then considered in the area of interest with a representative ratio class. This method allows for a more comprehensive and meaningful understanding of the data sampled following a radiological incident.

Data, a brief description of key boundary conditions, and results of Sandia National Laboratories’ ongoing MELCOR analysis of the Fukushima Unit 2 accident are given for the reactor core isolation cooling (RCIC) system. Important assumptions and related boundary conditions in the current analysis additional to or different than what was assumed/imposed in the work of SAND2012-6173 are identified. This work is for the U.S. Department of Energy’s Nuclear Energy University Programs fiscal year 2014 Reactor Safety Technologies Research and Development Program RC-7: RCIC Performance under Severe Accident Conditions.

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