Publications

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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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For the U.S. Nuclear Regulatory Commission (NRC) Extremely Low Probability of Rupture (xLPR) pilot study, Sandia National Laboratories (SNL) was tasked to develop and evaluate a probabilistic framework using a commercial software package for Version 1.0 of the xLPR Code. Version 1.0 of the xLPR code is focused assessing the probability of rupture due to primary water stress corrosion cracking in dissimilar metal welds in pressurizer surge nozzles. Future versions of this framework will expand the capabilities to other cracking mechanisms, and other piping systems for both pressurized water reactors and boiling water reactors. The goal of the pilot study project is to plan the xLPR framework transition from Version 1.0 to Version 2.0; hence the initial Version 1.0 framework and code development will be used to define the requirements for Version 2.0. The software documented in this report has been developed and tested solely for this purpose. This framework and demonstration problem will be used to evaluate the commercial software's capabilities and applicability for use in creating the final version of the xLPR framework. This report details the design, system requirements, and the steps necessary to use the commercial-code based xLPR framework developed by SNL.

Sandia National Laboratories (SNL) participated in a Pilot Study to examine the process and requirements to create a software system to assess the extremely low probability of pipe rupture (xLPR) in nuclear power plants. This project was tasked to develop a prototype xLPR model leveraging existing fracture mechanics models and codes coupled with a commercial software framework to determine the framework, model, and architecture requirements appropriate for building a modular-based code. The xLPR pilot study was conducted to demonstrate the feasibility of the proposed developmental process and framework for a probabilistic code to address degradation mechanisms in piping system safety assessments. The pilot study includes a demonstration problem to assess the probability of rupture of DM pressurizer surge nozzle welds degraded by primary water stress-corrosion cracking (PWSCC). The pilot study was designed to define and develop the framework and model; then construct a prototype software system based on the proposed model. The second phase of the project will be a longer term program and code development effort focusing on the generic, primary piping integrity issues (xLPR code). The results and recommendations presented in this report will be used to help the U.S. Nuclear Regulatory Commission (NRC) define the requirements for the longer term program.

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A total system performance assessment (TSPA) model has been developed to analyze the ability of the natural and engineered barriers of the Yucca Mountain repository to isolate nuclear waste over the period following repository closure. The principal features of the engineered barrier system are emplacement tunnels (or "drifts") containing a two-layer waste package (WP) for waste containment and a titanium drip shield to protect the WP from seeping water and falling rock. The 25-mm-thick outer shell of the WP is composed of Alloy 22, a highly corrosion-resistant nickel-based alloy. There are five nominal degradation modes of the Alloy 22: general corrosion, microbially influenced corrosion, stress corrosion cracking, early failure due to manufacturing defects, and localized corrosion (LC). This paper specifically examines the incorporation of the Alloy 22 LC model into the Yucca Mountain TSPA model, particularly the abstraction and modeling methodology, as well as issues dealing with scaling, spatial variability, uncertainty, and coupling to other submodels that are part of the total system model, such as the submodel for seepage water chemistry.

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Sandia National Laboratories (Sandia), a U.S. Department of Energy National Laboratory, has over 30 years experience in the assessment of radioactive waste disposal, and at the time of this publication is providing assistance internationally in a number of areas relevant to the safety assessment of radioactive waste disposal systems. In cooperation with the Republic of Taiwan’s Institute of Nuclear Engineering and Research (INER), Sandia National Laboratories (SNL) has developed software that provides an interface between a deterministic mass transport code and GoldSim™ (a commercial software used to conduct Monte Carlo analyses). The SNL-developed software enables INER to perform probabilistic simulations for safety analysis and performance assessment of geologic disposal of commercial spent nuclear fuel. This report details the software design, the steps necessary to use the software, and presents an example application of the paradigm of coupling deterministic codes to a contemporary probabilistic software application.