Publications

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A methodology for using the MELCOR code with the Latin Hypercube Sampling method was developed to estimate uncertainty in various predicted quantities such as hydrogen generation or release of fission products under severe accident conditions. In this case, the emphasis was on estimating the range of hydrogen sources in station blackout conditions in the Sequoyah Ice Condenser plant, taking into account uncertainties in the modeled physics known to affect hydrogen generation. The method uses user-specified likelihood distributions for uncertain model parameters, which may include uncertainties of a stochastic nature, to produce a collection of code calculations, or realizations, characterizing the range of possible outcomes. Forty MELCOR code realizations of Sequoyah were conducted that included 10 uncertain parameters, producing a range of in-vessel hydrogen quantities. The range of total hydrogen produced was approximately 583kg <U+F0B1> 131kg. Sensitivity analyses revealed expected trends with respected to the parameters of greatest importance, however, considerable scatter in results when plotted against any of the uncertain parameters was observed, with no parameter manifesting dominant effects on hydrogen generation. It is concluded that, with respect to the physics parameters investigated, in order to further reduce predicted hydrogen uncertainty, it would be necessary to reduce all physics parameter uncertainties similarly, bearing in mind that some parameters are inherently uncertain within a range. It is suspected that some residual uncertainty associated with modeling complex, coupled and synergistic phenomena, is an inherent aspect of complex systems and cannot be reduced to point value estimates. The probabilistic analyses such as the one demonstrated in this work are important to properly characterize response of complex systems such as severe accident progression in nuclear power plants.

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).

In the summer of 2020, the National Aeronautics and Space Administration (NASA) plans to launch a spacecraft as part of the Mars 2020 mission. One option for the rover on the proposed spacecraft uses a Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) to provide continuous electrical and thermal power for the mission. An alternative option being considered is a set of solar panels for electrical power with up to 80 Light-Weight Radioisotope Heater Units (LWRHUs) for local component heating. Both the MMRTG and the LWRHUs use radioactive plutonium dioxide. NASA is preparing an Environmental Impact Statement (EIS) in accordance with the National Environmental Policy Act. The EIS will include information on the risks of mission accidents to the general public and on-site workers at the launch complex. This Nuclear Risk Assessment (NRA) addresses the responses of the MMRTG or LWRHU options to potential accident and abort conditions during the launch opportunity for the Mars 2020 mission and the associated consequences. This information provides the technical basis for the radiological risks of both options for the EIS.

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The dose limits for emissions from the nuclear fuel cycle were established by the Environmental Protection Agency in 40 CFR Part 190 in 1977. These limits were based on assumptions regarding the growth of nuclear power and the technical capabilities of decontamination systems as well as the then-current knowledge of atmospheric dispersion and the biological effects of ionizing radiation. In the more than thirty years since the adoption of the limits, much has changed with respect to the scale of nuclear energy deployment in the United States and the scientific knowledge associated with modeling health effects from radioactivity release. Sandia National Laboratories conducted a study to examine and understand the methodologies and technical bases of 40 CFR 190 and also to determine if the conclusions of the earlier work would be different today given the current projected growth of nuclear power and the advances in scientific understanding. This report documents the results of that work.

The PUFF code was originally written and designed to calculate the rise of a large detonation or deflagration non-continuous plume (puff) in the atmosphere. It is based on a buoyant spherical control volume approximation. The theory for the model is updated and presented. The model has been observed to result in what are believed to be unrealistic plume elevation oscillations as the plume approaches the terminal elevation. Recognizing a similarity between the equations for a classical damped spring oscillator and the present model, the plume rise model can be analyzed by evaluating equivalent spring constants and damping functions. Such an analysis suggests a buoyant plume in the atmosphere is significantly under-damped, explaining the occurrence of the oscillations in the model. Based on lessons learned from the analogy evaluations and guided by comparisons with early plume rise data, a set of assumptions is proposed to address the excessive oscillations found in the predicted plume near the terminal elevation, and to improve the robustness of the predictions. This is done while retaining the basic context of the present model formulation. The propriety of the present formulation is evaluated. The revised model fits the vast majority of the existing data to +/- 25%, which is considered reasonable given the present model form. Further validation efforts would be advisable, but are impeded by a lack of quality existing datasets. Copyright © 2008 by ASME.