Publications

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The Department of Energy has assigned to Sandia National Laboratories the responsibility of producing a Safety Analysis Report (SAR) for the plutonium-dioxide fueled Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) proposed to be used in the Mars Science Laboratory (MSL) mission. The National Aeronautic and Space Administration (NASA) is anticipating a launch in fall of 2009, and the SAR will play a critical role in the launch approval process. As in past safety evaluations of MMRTG missions, a wide range of potential accident conditions differing widely in probability and seventy must be considered, and the resulting risk to the public will be presented in the form of probability distribution functions of health effects in terms of latent cancer fatalities. The basic descriptions of accident cases will be provided by NASA in the MSL SAR Databook for the mission, and on the basis of these descriptions, Sandia will apply a variety of sophisticated computational simulation tools to evaluate the potential release of plutonium dioxide, its transport to human populations, and the consequent health effects. The first step in carrying out this project is to evaluate the existing computational analysis tools (computer codes) for suitability to the analysis and, when appropriate, to identify areas where modifications or improvements are warranted. The overall calculation of health risks can be divided into three levels of analysis. Level A involves detailed simulations of the interactions of the MMRTG or its components with the broad range of insults (e.g., shrapnel, blast waves, fires) posed by the various accident environments. There are a number of candidate codes for this level; they are typically high resolution computational simulation tools that capture details of each type of interaction and that can predict damage and plutonium dioxide release for a range of choices of controlling parameters. Level B utilizes these detailed results to study many thousands of possible event sequences and to build up a statistical representation of the releases for each accident case. A code to carry out this process will have to be developed or adapted from previous MMRTG missions. Finally, Level C translates the release (or ''source term'') information from Level B into public risk by applying models for atmospheric transport and the health consequences of exposure to the released plutonium dioxide. A number of candidate codes for this level of analysis are available. This report surveys the range of available codes and tools for each of these levels and makes recommendations for which choices are best for the MSL mission. It also identities areas where improvements to the codes are needed. In some cases a second tier of codes may be identified to provide supporting or clarifying insight about particular issues. The main focus of the methodology assessment is to identify a suite of computational tools that can produce a high quality SAR that can be successfully reviewed by external bodies (such as the Interagency Nuclear Safety Review Panel) on the schedule established by NASA and DOE.

This report documents a probabilistic risk assessment of an existing power supply system at a large telecommunications office. The focus is on characterizing the increase in the reliability of power supply through the use of two alternative power configurations. Telecommunications has been identified by the Department of Homeland Security as a critical infrastructure to the United States. Failures in the power systems supporting major telecommunications service nodes are a main contributor to major telecommunications outages. A logical approach to improve the robustness of telecommunication facilities would be to increase the depth and breadth of technologies available to restore power in the face of power outages. Distributed energy resources such as fuel cells and gas turbines could provide one more onsite electric power source to provide backup power, if batteries and diesel generators fail. The analysis is based on a hierarchical Bayesian approach and focuses on the failure probability associated with each of three possible facility configurations, along with assessment of the uncertainty or confidence level in the probability of failure. A risk-based characterization of final best configuration is presented.