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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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.

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).

The State-of-the-Art Reactor Consequence Analyses (SOARCA) project for the Peach Bottom Atomic Power Station (the pilot boiling-water reactor) and Surry Power Station (the pilot pressurized-water reactor) represents the most complex deterministic MELCOR analyses performed to date. Uncertainty analyses focusing on input parameter uncertainty are now under way for one scenario at each pilot plant. Analyzing the uncertainty in parameters requires technical justification for the selection of each parameter to include in the analyses and defensible rationale for the associated distributions. This paper describes the methodology employed in the selection of parameters and corresponding distributions for the Surry uncertainty analysis, and insights from applying the methodology to the MELCOR parameters.

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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This paper describes the MELCOR Accident Consequence Code System, Version 2 (MACCS2) dose-truncation sensitivity of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses unmitigated long-term station blackout severe accident scenario at the Peach Bottom Atomic Power Station. Latent-cancer-fatality (LCF) risk results for this sensitivity study are presented for three dose-response models. LCF risks are reported for circular areas ranging from a 10-to a 50-mile radius centered on the plant. For the linear, no-threshold, sensitivity analysis, all regression methods consistently rank the MACCS2 dry deposition velocity and the MELCOR safety relief valve (SRV) stochastic failure probability, respectively, as the most important input parameters. For the alternative dose-truncation models (i.e., USBGR (0.62 rem/yr) and HPS (5 rem/yr with a lifetime limit of 10 rem)) sensitivity analyses, the regression methods consistently rank the MACCS2 inhalation protection factor for normal activity, the MACCS2 lung lifetime risk factor for cancer death, and the MELCOR SRV stochastic failure probability as the most important input variables. The important MELCOR input parameters are relatively independent of the dose-response model used in MACCS2. However, the MACCS2 input variables depend strongly on the dose-response model. The use of either the USBGR or the HPS dose-response model emphasizes MACCS2 input variables associated with doses received in the first year and deemphasizes MACCS2 input parameters associated with long-term phase doses beyond the first year.

This paper describes the MELCOR Accident Consequence Code System, Version 2(MACCS2), parameters and probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses unmitigated long-term station blackout accident scenario at the Peach Bottom Atomic Power Station. Consequence results are presented as conditional risk (i.e., assuming the accident occurs) to individuals of the public as a result of the accident - latent-cancer-fatality (LCF) risk per event or prompt-fatality risk per event. For the mean, individual, LCF risk, all regression methods at each of the circular areas around the plant that are analyzed (10-mile to 50-mile radii are considered) consistently rank the MACCS2 dry deposition velocity, the MELCOR safety relief valve (SRV) stochastic failure probability, and the MACCS2 residual cancer risk factor, respectively, as the most important input parameters. For the mean, individual, prompt-fatality risk (which is zero in over 85% of the Monte Carlo realizations) within circular areas with less than a 2-mile radius, the non-rank regression methods consistently rank the MACCS2 wet deposition parameter, the MELCOR SRV stochastic failure probability, the MELCOR SRV open area fraction, the MACCS2 early health effects threshold for red bone marrow, and the MACCS2 crosswind dispersion coefficient, respectively, as the most important input parameters. For the mean, individual prompt-fatality risk within the circular areas with radii between 2.5-miles and 3.5-miles, the regression methods consistently rank the MACCS2 crosswind dispersion coefficient, the MACCS2 early health effects threshold for red bone marrow, the MELCOR SRV stochastic failure probability, and the MELCOR SRV open area fraction, respectively, as the most important input parameters.

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The radiological transportation risk & consequence program, RADTRAN, has recently added an updated loss of lead shielding (LOS) model to it most recent version, RADTRAN 6.0. The LOS model was used to determine dose estimates to first-responders during a spent nuclear fuel transportation accident. Results varied according to the following: type of accident scenario, percent of lead slump, distance to shipment, and time spent in the area. This document presents a method of creating dose estimates for first-responders using RADTRAN with potential accident scenarios. This may be of particular interest in the event of high speed accidents or fires involving cask punctures.

RADTRAN is an internationally accepted program and code for calculating the risks of transporting radioactive materials. The first versions of the program, RADTRAN I and II, were developed for NUREG-0170 (USNRC, 1977), the first environmental statement on transportation of radioactive materials. RADTRAN and its associated software have undergone a number of improvements and advances consistent with improvements in both available data and computer technology. The version of RADTRAN currently bundled with RadCat is RADTRAN 6.0. This document provides a detailed discussion and a guide for the use of the RadCat 3.0 Graphical User Interface input file generator for the RADTRAN code. RadCat 3.0 integrates the newest analysis capabilities of RADTRAN 6.0 which includes an economic model, updated loss-of-lead shielding model, and unit conversion. As of this writing, the RADTRAN version in use is RADTRAN 6.0.

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The RADTRAN Loss of Shielding (LOS) Model was benchmarked using MicroShield 6.20®. This analysis considers an intact spent fuel truck cask as well as a set of damaged truck casks. Ratios of dose rates are calculated for casks with a loss of lead shielding to those of intact casks, and are then compared to ratios generated by the LOS model. LOS Model results were considered verified if two main constraints were satisfied. First, the dose rate profiles for both the LOS and MicroShield 6.20® calculations must have the same general shape and behavior. Additionally, the largest factor difference between any two points of the dose rate profiles may not exceed an order of magnitude. Reasonable agreement is shown for large-fraction LOS scenarios; however the differences in results are not satisfactory for cases with small fractions of slump.

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This document describes the specimen and transportation containers currently available for use with hazardous and infectious materials. A detailed comparison of advantages, disadvantages, and costs of the different technologies is included. Short- and long-term recommendations are also provided.3 DraftDraftDraftExecutive SummaryThe Federal Bureau of Investigation's Hazardous Materials Response Unit currently has hazardous material transport containers for shipping 1-quart paint cans and small amounts of contaminated forensic evidence, but the containers may not be able to maintain their integrity under accident conditions or for some types of hazardous materials. This report provides guidance and recommendations on the availability of packages for the safe and secure transport of evidence consisting of or contaminated with hazardous chemicals or infectious materials. Only non-bulk containers were considered because these are appropriate for transport on small aircraft. This report will addresses packaging and transportation concerns for Hazardous Classes 3, 4, 5, 6, 8, and 9 materials. If the evidence is known or suspected of belonging to one of these Hazardous Classes, it must be packaged in accordance with the provisions of 49 CFR Part 173. The anthrax scare of several years ago, and less well publicized incidents involving unknown and uncharacterized substances, has required that suspicious substances be sent to appropriate analytical laboratories for analysis and characterization. Transportation of potentially hazardous or infectious material to an appropriate analytical laboratory requires transport containers that maintain both the biological and chemical integrity of the substance in question. As a rule, only relatively small quantities will be available for analysis. Appropriate transportation packaging is needed that will maintain the integrity of the substance, will not allow biological alteration, will not react chemically with the substance being shipped, and will otherwise maintain it as nearly as possible in its original condition.The recommendations provided are short-term solutions to the problems of shipping evidence, and have considered only currently commercially available containers. These containers may not be appropriate for all cases. Design, testing, and certification of new transportation containers would be necessary to provide a container appropriate for all cases.Table 1 provides a summary of the recommendations for each class of hazardous material.Table 1: Summary of RecommendationsContainerCost1-quart paint can with ArmlockTM seal ringLabelMaster(r)%242.90 eachHazard Class 3, 4, 5, 8, or 9 Small ContainersTC Hazardous Material Transport ContainerCurrently in Use4 DraftDraftDraftTable 1: Summary of Recommendations (continued)ContainerCost55-gallon open or closed-head steel drumsAll-Pak, Inc.%2458.28 - %2473.62 eachHazard Class 3, 4, 5, 8, or 9 Large Containers95-gallon poly overpack LabelMaster(r)%24194.50 each1-liter glass container with plastic coatingLabelMaster(r)%243.35 - %243.70 eachHazard Class 6 Division 6.1 Poisonous by Inhalation (PIH) Small ContainersTC Hazardous Material Transport ContainerCurrently in Use20 to 55-gallon PIH overpacksLabelMaster(r)%24142.50 - %24170.50 eachHazard Class 6 Division 6.1 Poisonous by Inhalation (PIH) Large Containers65 to 95-gallon poly overpacksLabelMaster(r)%24163.30 - %24194.50 each1-liter transparent containerCurrently in UseHazard Class 6 Division 6.2 Infectious Material Small ContainersInfectious Substance ShipperSource Packaging of NE, Inc.%24336.00 eachNone Commercially AvailableN/AHazard Class 6 Division 6.2 Infectious Material Large ContainersNone Commercially Available N/A5

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This document provides a detailed discussion and a guide for the use of the RadCat 2.0 Graphical User Interface input file generator for the RADTRAN 5.5 code. The differences between RadCat 2.0 and RadCat 1.0 can be attributed to the differences between RADTRAN 5 and RADTRAN 5.5 as well as clarification for some of the input parameters. 3