Developing a big picture understanding of a severe accident is extremely challenging. Operating crews and emergency response teams are faced with rapidly evolving circumstances, uncertain information, distributed expertise, and a large number of conflicting goals and priorities. Severe accident management guidance (SAMGs) provides support for collecting information and assessing the state of a nuclear power plant during severe accidents. However, SAMGs developers cannot anticipate every possible accident scenario. Advanced Probabilistic Risk Assessment (PRA) methods can be used to explore an extensive space of possible accident sequences and consequences. Using this advanced PRA to develop a decision support system can provide expanded support for diagnosis and response. In this paper, we present an approach that uses dynamic PRA to develop risk-informed "Smart SAMGs". Bayesian Networks form the basis of the faster-than-real-time decision support system. The approach leverages best-available information from plant physics simulation codes (e.g., MELCOR). Discrete Dynamic Event Trees (DDETs) are used to provide comprehensive coverage of the potential accident scenario space. This paper presents a methodology to develop Smart procedures and provides an example model created for diagnosing the status of the ECCS valves in a generic iPWR design.
The current wave of small modular reactor (SMR) designs all have the goal of reducing the cost of management and operations. By optimizing the system, the goal is to make these power plants safer, cheaper to operate and maintain, and more secure. In particular, the reduction in plant staffing can result in significant cost savings. The introduction of advanced reactor designs and increased use of advanced automation technologies in existing nuclear power plants will likely change the roles, responsibilities, composition, and size of the crews required to control plant operations. Similarly, certain security staffing requirements for traditional operational nuclear power plants may not be appropriate or necessary for SMRs due to the simpler, safer and more automated design characteristics of SMRs. As a first step in a process to identify where regulatory requirements may be met with reduced staffing and therefore lower cost, this report identifies the regulatory requirements and associated guidance utilized in the licensing of existing reactors. The potential applicability of these regulations to advanced SMR designs is identified taking into account the unique features of these types of reactors.
Uncertainty distributions for specific parameters of the Cassini General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS-RTG) Final Safety Analysis Report consequence risk analysis were revised and updated. The revisions and updates were done for all consequence parameters for which relevant information exists from the joint project on Probabilistic Accident Consequence Uncertainty Analysis by the United States Nuclear Regulatory Commission and the Commission of European Communities.
A multi-attribute utility analysis is applied to a decision process to select a treatment method for the management of aluminum-based spent nuclear fuel (Al-SNF) owned by the US Department of Energy (DOE). DOE will receive, treat, and temporarily store Al-SNF, most of which is composed of highly enriched uranium, at its Savannah River Site in South Carolina. DOE intends ultimately to send the treated Al-SNF to a geologic repository for permanent disposal. DOE initially considered ten treatment alternatives for the management of Al-SNF, and has narrowed the choice to two of these: the direct disposal and melt and dilute alternatives. The decision analysis presented in this document focuses on a formal decision process used to evaluate these two remaining alternatives.
A multi-attribute utility analysis is applied to the decision to select a treatment method for the management of aluminum-based spent nuclear i%el (A1-SNF) owned by the United States Department of Energy (DOE). DOE will receive, treat, and temporarily store Al- SNF, most of which is composed of highly enriched uranium, at its Savannah River Site in South Carolina. DOE intends ultimately to send the treated Al-SNJ? to a geologic repository for permanent disposal. DOE initially considered ten treatment alternatives for the management of A1-SNF, and has narrowed the choice to two of these the direct disposal and melt and dilute alternatives. The decision analysis presented in this document focuses on a decision between these two remaining alternatives.
The Department of Energy (DOE) proposes to construct and operate the National Ignition Facility (NIF) in support of the Stockpile Stewardship and Management (SSM) Programmatic Environmental impact Statement (PEIS). The National Environmental Policy Act requires the DOE to look at alternative sites for the NIF. The SSM PEIS will evaluate four alternative locations for the NIF. This study documents the process and results of a site selection study for a preferred site for the NIF at SNL/NM. The NIF research objectives are to provide the world`s most powerful laser systems to be used in ignition of fusion fuel and energy gain to perform high energy density and radiation effects experiments in support of the DOE`s national security, energy, and basic science research mission. The most immediate application of the NIF will be to provide nuclear-weapon-related physics data, since many phenomena occurring on the laboratory scale are similar to those that occur in weapons. The NIF may also provide an important capability for weapons effects simulation. The NIF is designed to achieve propagating fusion bum and modest energy gain for development as a source of civilian energy.
The potential radiological and nonradiological risks associated with specific radioactive waste shipping campaigns at the Hanford Site are estimated. The shipping campaigns analyzed are associated with the transportation of wastes from the N-Reactor site at the 200-W Area, both within the Hanford Reservation, for disposal. The analysis is based on waste that would be generated from the N-Reactor stabilization program.
The objective of this review is to evaluate the South Texas Project (STP) Probabilistic Safety Analysis (PSA) for the USNRC. The PSA was reviewed for thoroughness of analysis, accuracy in plant modeling, legitimacy of assumptions, and overall quality of the work. The review is limited to the internal event analysis and the fire sequence analysis. This review is not a quantitative evaluation of the adequacy of the PSA. The adequacy of the PSA depends on the intended uses and must be addressed on a case-by-case basis by the licensee and the NRC. This review identifies strengths, weakness, and areas where additional clarification would assist the NRC in evaluating the PSA for specific regulatory purposes. The licensee, Houston Lighting and Power (HL P), reviewed a draft version of this report prior to its final release to the USNRC. The responses provided by HL P are provided in detail in appendices to this report, and they are summarized in the main body of the report. All issues raised during the review were adequately addressed by HL P in the responses. 27 refs., 4 tabs.