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Safety is central to the design, licensing, operation, and economics of Nuclear Power Plants (NPPs). Consequently, the ability to better characterize and quantify safety margin holds the key to improved decision making about LWR design, operation, and plant life extension. A systematic approach to characterization of safety margins and the subsequent margins management options represents a vital input to the licensee and regulatory analysis and decision making that will be involved. The purpose of the RISMC Pathway R & D is to support plant decisions for risk-informed margins management with the aim to improve economics, reliability, and sustain safety of current NPPs. Goals of the RISMC Pathway are twofold: (1) Develop and demonstrate a risk-assessment method coupled to safety margin quantification that can be used by NPP decision makers as part of their margin recovery strategies. (2) Create an advanced?RISMC toolkit? that enables more accurate representation of NPP safety margin. This report describes the RISMC methodology demonstration where the Advanced Test Reactor (ATR) was used as a test-bed for purposes of determining safety margins. As part of the demonstration, we describe how both the thermal-hydraulics and probabilistic safety calculations are integrated and used to quantify margin management strategies.
Safety is central to the design, licensing, operation, and economics of Nuclear Power Plants (NPPs). As the current Light Water Reactor (LWR) NPPs age beyond 60 years, there are possibilities for increased frequency of Systems, Structures, and Components (SSCs) degradations or failures that initiate safety-significant events, reduce existing accident mitigation capabilities, or create new failure modes. Plant designers commonly "over-design" portions of NPPs and provide robustness in the form of redundant and diverse engineered safety features to ensure that, even in the case of well-beyond design basis scenarios, public health and safety will be protected with a very high degree of assurance. This form of defense-in-depth is a reasoned response to uncertainties and is often referred to generically as "safety margin." Historically, specific safety margin provisions have been formulated, primarily based on "engineering judgment."
This report summarizes the research activity developed during the Fiscal year 2014 within the Risk Informed Safety Margin and Characterization (RISMC) pathway within the Light Water Reactor Sustainability (LWRS) campaign. This research activity is complementary to the one presented in the INL/EXT-??? report which shows advances Probabilistic Risk Assessment Analysis using RAVEN and RELAP-7 in conjunction to novel flooding simulation tools. Here we present several analyses that prove the values of the RISMC approach in order to assess risk associated to nuclear power plants (NPPs). We focus on simulation based PRA which, in contrast to classical PRA, heavily employs system simulator codes. Firstly we compare, these two types of analyses, classical and RISMC, for a Boiling water reactor (BWR) station black out (SBO) initiating event. Secondly we present an extended BWR SBO analysis using RAVEN and RELAP-5 which address the comments and suggestions received about he original analysis presented in INL/EXT-???. This time we focus more on the stochastic analysis such probability of core damage and on the determination of the most risk-relevant factors. We also show some preliminary results regarding the comparison between RELAP5-3D and the new code RELAP-7 for a simplified Pressurized Water Reactors system. Lastly we present some conceptual ideas regarding the possibility to extended the RISMC capabilities from an off-line tool (i.e., as PRA analysis tool) to an online-tool. In this new configuration, RISMC capabilities can be used to assist and inform reactor operator during real accident scenarios.
The Risk-Informed Safety Margin Characterization (RISMC) pathway of the DOE's Light Water Reactor Sustainability (LWRS) program focuses on advancing the state of the art in safety analysis and risk assessment to support decision-making on nuclear power plant operation well beyond the originally designed lifetime of the plants (i.e., beyond 60 years). Among the issues being addressed in RISMC is the significance of SSC aging and how confident we are about our understanding of its impact on the margin between the loads SSCs are expected to see during normal operation and accident conditions, and the SSC capacities (their ability to resist those loads) as the SSCs age. In this paper, a summary is provided of a case study that examines SSC aging from an environmental qualification (EQ) perspective. The case study illustrates how the state of knowledge regarding SSC margin can be characterized given the overall integrated plant design, and was developed to demonstrate a method for deciding on which cables to focus, which cables are not so important from an environmental qualification margin standpoint, and what plant design features or operating characteristics determine the role that environmental qualification plays in establishing a safety case on which decisions regarding margin can be made. The selection of cables for which demonstration of margin with respect to aging and environmental challenges uses a technique known as Prevention Analysis. Prevention Analysis is a Boolean method for optimal selection of SSCs (that is, those combinations of SSCs both necessary and sufficient to meet a predetermined selection criterion) in a manner that allows demonstration that plant-level safety can be demonstrated by the collection of selected SSCs alone. Choosing the set of SSCs that is necessary and sufficient to satisfy the safety objectives, and demonstrating that the safety objectives can be met effectively, determines where resources are best allocated to assure SSC performance margin. The paper describes the resulting component types that were selected by Prevention Analysis and identifies the accident sequence characteristics that cause these component types to be important from an EQ and aging perspective (and, hence, worthwhile evaluating the extent of safety margin). In addition, component types not selected as needing significant margin from an EQ and aging perspective are discussed and an engineering rationale is developed justifying the lack of need to apply resources to demonstrating margin for these component types. This rationale is in terms of design features of the plant and operating characteristics that make these component types less important from an EQ and aging perspective. While the case study focuses on EQ and aging of equipment and cables located inside the containment of this PWR, the prevention analysis method is demonstrated to be an effective technique for identification of minimal collections of components that would be effective in managing safety for a variety of issues associated with aging and long-term operation of the fleet of plants.
The concept of "margin" has a long history in nuclear licensing and in the codification of good engineering practices. However, some traditional applications of "margin" have been carried out for surrogate scenarios (such as design basis scenarios), without regard to the actual frequencies of those scenarios, and have been carried out with in a systematically conservative fashion. This means that the effectiveness of the application of the margin concept is determined in part by the original choice of surrogates, and is limited in any case by the degree of conservatism imposed on the evaluation. In the RISMC project, which is part of the Department of Energy's "Light Water Reactor Sustainability Program" (LWRSP), we are developing a risk-informed characterization of safety margin. Beginning with the traditional discussion of "margin" in terms of a "load" (a physical challenge to system or component function) and a "capacity" (the capability of that system or component to accommodate the challenge), we are developing the capability to characterize probabilistic load and capacity spectra, reflecting both aleatory and epistemic uncertainty in system response. For example, the probabilistic load spectrum will reflect the frequency of challenges of a particular severity. Such a characterization is required if decision-making is to be informed optimally. However, in order to enable the quantification of probabilistic load spectra, existing analysis capability needs to be extended. Accordingly, the INL is working on a next-generation safety analysis capability whose design will allow for much more efficient parameter uncertainty analysis, and will enable a much better integration of reliability-related and phenomenology-related aspects of margin.
The INL has carried out a demonstration of the RISMC approach for the purpose of configuration risk management. We have shown how improved accuracy and realism can be achieved by simulating changes in risk - as a function of different configurations - in order to determine safety margins as the plant is modified. We described the various technical issues that play a role in these configuration-based calculations with the intent that future applications can take advantage of the analysis benefits while avoiding some of the technical pitfalls that are found for these types of calculations. Specific recommendations have been provided on a variety of topics aimed at improving the safety margin analysis and strengthening the technical basis behind the analysis process.
The purpose of the Risk Informed Safety Margin Characterization (RISMC) Pathway research and development (R & D) is to support plant decisions for risk-informed margins management with the aim to improve economics, reliability, and sustain safety of current NPPs. Goals of the RISMC Pathway are twofold: (1) Develop and demonstrate a risk-assessment method coupled to safety margin quantification that can be used by NPP decision makers as part of their margin recovery strategies. (2) Create an advanced "RISMC toolkit" that enables more accurate representation of NPP safety margin. In order to carry out the R & D needed for the Pathway, the Idaho National Laboratory (INL) is collaborating with the Electric Power Research Institute (EPRI) in order to focus on applications of interest to the U.S. nuclear power industry. This report documents the collaboration activities performed between INL and EPRI during FY2013.
This report describes the development plan for a new multi-partner External Hazards Experimental Group (EHEG) coordinated by Idaho National Laboratory (INL) within the Risk-Informed Safety Margin Characterization (RISMC) technical pathway of the Light Water Reactor Sustainability Program. Currently, there is limited data available for development and validation of the tools and methods being developed in the RISMC Toolkit. The EHEG is being developed to obtain high-quality, small- and large-scale experimental data validation of RISMC tools and methods in a timely and cost-effective way. The group of universities and national laboratories that will eventually form the EHEG (which is ultimately expected to include both the initial participants and other universities and national laboratories that have been identified) have the expertise and experimental capabilities needed to both obtain and compile existing data archives and perform additional seismic and flooding experiments. The data developed by EHEG will be stored in databases for use within RISMC. These databases will be used to validate the advanced external hazard tools and methods.
The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated. In order to evaluate the impact of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the impact of power uprate on the safety of a boiled water reactor system. The case study considered is a loss of off-site power followed by the loss of diesel generators, i.e., a station black out (SBO) event. Analysis is performed by using a thermo-hydraulic code, i.e. RELAP-5, and a stochastic analysis tool currently under development at INL, i.e. RAVEN. Starting from the event tree models contained in SAPHIRE, we built the input file for RELAP-5 that models in great detail system dynamics under SBO conditions. We also interfaced RAVEN with RELAP-5 so that it would be possible to run multiple RELAP-5 simulation runs by changing specific keywords of the input file. We both employed classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. We also employed advanced data analysis and visualization tools that helped us to correlate simulation outcome such as maximum core temperature with a set of input uncertain parameters. Results obtained gave a detailed overview of the issues associated to power uprate for a SBO accident scenario. We were able to quantify how timing of safety related events were impacted by a higher reactor core power. Such insights can provide useful material to the decision makers to perform risk-infomed safety margins management.