Publications

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Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

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. NASA has prepared an Environmental Impact Statement (EIS) in accordance with the National Environmental Policy Act. The EIS includes information on the risks of mission accidents to the general public and on-site workers at the launch complex. The Nuclear Risk Assessment (NRA) addresses the responses of the MMRTG option 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 the MMRTG option for the EIS. This paper provides a summary of the methods and results used in the NRA.

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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 ± 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).

Spent nuclear fuel reprocessing may involve some hazardous liquids that may explode under accident conditions. Explosive accidents may result in energetic dispersion of the liquid. The atomized liquid represents a major hazard of this class of event. The magnitude of the aerosol source term is difficult to predict, and historically has been estimated from correlations based on marginally relevant data. A technique employing a coupled finite element structural dynamics and control volume computational fluid dynamics has been demonstrated previously for a similar class of problems. The technique was subsequently evaluated for detonation events. Key to the calculations is the use of a Taylor Analogy Break-up (TAB) based model for predicting the aerodynamic break-up of the liquid drops in the air environment, and a dimensionless parameter for defining the chronology of the mass and momentum coupling. This paper presents results of liquid aerosolization from an explosive event.

Spent nuclear fuel reprocessing may involve some hazardous liquids that may explode under accident conditions. Explosive accidents may result in energetic dispersion of the liquid. The atomized liquid represents a major hazard of this class of event. The magnitude of the aerosol source term is difficult to predict, and historically has been estimated from correlations based on marginally relevant data. A technique employing a coupled finite element structural dynamics and control volume computational fluid dynamics has been demonstrated previously for a similar class of problems. The technique was subsequently evaluated for detonation events. Key to the calculations is the use of a Taylor Analogy Break-up (TAB) based model for predicting the aerodynamic break-up of the liquid drops in the air environment, and a dimensionless parameter for defining the chronology of the mass and momentum coupling. This paper presents results of liquid aerosolization from an explosive event.

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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Nuclear thermal rockets (NTR) have the potential to greatly enhance payloads from low earth orbit to Mars, the Moon, or other deep space destinations. NTR tests at the Nevada Test Site in the 1960s produced some release of radioactive fission products in the rocket exhaust. This release came from some degradation of the surface coating on the reactor fuel and coolant channels during the high-temperature operation. This paper estimates the potential doses and health effects to populations on Earth should comparable releases occur during NTR thrusting in low earth orbit during a mission to Mars or other destinations. A multi-compartment atmospheric model is developed to track the time needed for exhaust components to reach the surface of the earth. Isotopic decay is included in this model. Because most fission products have a short half-life and the time for aerosols to reach the earth's surface is many years, very little radioactive material reaches the earth's surface. The average dose per person from a typical NTR thrusting operation in low earth orbit (using the NTR designs of the 1960s) is calculated to be about 1E-08 of the dose received from natural background radiation.

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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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