This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

Accident tolerant fuels (ATFs) are being tested by different nuclear vendors and research organizations, and their introduction into the U.S light water reactor fleet is planned for the second half of the 2020s. Under the framework of the U.S. Department of Energy Light Water Reactor Sustainability (LWRS) Program, as part of the LWRS Risk-Informed Systems Analysis Pathway, research is being conducted at the Idaho National Laboratory (INL) to develop tools and methods that can help the industry to quantify the benefits from adopting ATF technology. In this paper we describe the developed risk-informed methodology including the safety analysis code improvements, and we present some results for selected accident scenarios. The developed methodology combines the INL state-of-the-art deterministic Best Estimate code RELAP5-3D and the probabilistic risk analysis tools RAVEN and SAPHIRE. The analyses are performed on a three-loop pressurized water reactor, simulating station blackout and large-break loss-of-coolant accidents and considering near-term ATFs or iron-chromium-aluminum and chromium-coated clads. Finally, we show how, applying our methodology, the new core damage frequency (CDF) can be assessed. The results indicate that the main benefit in introducing near-term ATFs is a significant reduction in hydrogen production during accident conditions. No significant CDF reduction was found.

This report documents the quantitative results of the common-cause failure (CCF) data collection effort (which included data through 2020) and summarizes the results of the parameter estimation quantification process performed on CCF data in the U.S. Nuclear Regulatory Commission (NRC) CCF database. This is the 2020 update to NUREG/CR-5497, updating data and parameter estimations for CCFs. This release, CCF Parameter Estimation 2020, reflects the CCF data contained within the CCF database, https://rads.inl.gov/Pages/CCF.aspx, by executing (in August 2021) the CCF query rules in the folder SPAR Rules 2020. The data covers the period from 1/1/2006 to 12/31/2020, the most recent 15-year period in which data are available. The use of the most recent rolling 15-year data in parameter estimation differs from previous updates, in which 1/1/1997 was used as the starting date (e.g., 1/1/1997 to 12/31/2015 for the 2015 update, 1/1/1997 to 12/31/2012 for the 2012 update). The new date range (i.e., the most recent 15-year period), was selected for this CCF update so as to be consistent with the date range chosen for the component reliability parameter estimation, and with the effort to include sufficient data for analysis while simultaneously reflecting the most recent industry performance. These results are appropriatemore » for use in probabilistic risk assessment (PRA) studies, including the Standardized Plant Analysis Risk (SPAR) models of commercial nuclear power plants (NPPs) in the U.S. This update may be referred as: U.S. Nuclear Regulatory Commission, "CCF Parameter Estimations, 2020 Update," https://nrcoe.inl.gov/publicdocs/CCF/ccfparamest2020.pdf, November 2021. « less

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

This report documents the activities performed during the FY2018 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of Accident Tolerant Fuel (ATF), optimal use of Diverse and Flexible Coping Strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. There are two main focus areas in FY2018 for the ERP R&D efforts. One is to evaluate the risk impact brought by the ATF designs and FLEX inmore » the selected accident scenarios. The other is to investigate various approaches to accomplish the ERP research objective, i.e., use RISA methods and toolkit to enhance existing reactors safety features and reduce plant operating costs. « less

This report, along with report INL/EXT-19-53556, documents the activities performed by Idaho National Laboratory (INL) during the fiscal year (FY) 2019 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. This report includes additional accident scenarios for risk-informed ATF analysis, and examines the risk impacts of FLEX and passive cooling system on nuclear power plants (NPPs) from additional perspectives. The same analysis process, risk analysis approaches, and analysis tools as in FY 2018 were used for near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the small break loss-of-coolant accident (SBLOCA) scenarios, two types of general transient scenarios (locked rotor and turbine trip), and main steam line break (MSLB) scenarios. Benchmark calculations for ATF analysis using RELAP5-3D and MELCOR are also presented. In addition, based on the generic probabilistic risk assessment (PRA) model, the risk impacts of FLEX and the dynamic natural convection (DNC) system on NPPs are evaluated through a risk-informed decision-making process, i.e., significance determination process (SDP).