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Pupek C.,ERIN Engineering and Research
International Topical Meeting on Probabilistic Safety Assessment and Analysis 2013, PSA 2013 | Year: 2013

Now, in the third decade of Probabilistic Risk Assessment (PRA) usage in the industry, senior leaders and regulators are challenging the PRA community to drive an understanding of the insights and methodology that will allow further enhancement to plant safety. This next step is to develop an understanding of key characteristics unique to PRA techniques that can aid communication of insights throughout the organization. Such focused communication can help drive more thoughtful consideration of issues affecting decision-making on a variety of plant issues, from financial management to maintenance tool selection. To accomplish this lofty goal, a new paradigm in PRA education is required. In this new model, education starts with the results and creates an understanding of their derivation, which facilitates insights. This process is best served with the multi-discipline interaction required for successful PRA application and plant performance improvement. This paper discusses several risk-informed applications as tools for PRA socialization and education. It identifies the various disciplines involved with the applications and what they bring to the process with the goal of elaborating on how these experiences provide an opportunity to create understanding of PRA capability and insight that nuclear power plant personnel of all levels can relate to without turning into a training course on PRA techniques. Examples are discussed on how these processes create a reinforcing feedback loop that improves overall plant safety and key indicators. The importance of communications skills and tactics is also discussed. Source


Addis H.,ERIN Engineering and Research
International Topical Meeting on Probabilistic Safety Assessment and Analysis 2013, PSA 2013 | Year: 2013

Recent industry events have shown that a periodic PRA model update can cause a plant to cross the Mitigating System Performance Index (MSPI) green to white performance indicator threshold resulting in significant additional resources to both investigate the change in the indicator and support an additional NRC inspection. MSPI is an application that requires the PRA modeler to explicitly consider the model results prior to approval to ensure that MSPI fulfills the intended function as an ROP indicator. If a plant has low MSPI margin, the PRA modeler must use extreme caution to ensure the assumptions and modeling are as exact as necessary to preserve MSPI margin, not cause a MSPI color change and comply with all requirements of NEI 99-02. This must be done with integrity and precision to ensure that the indicator is not biased by the plant's desire to stay within the MSPI green threshold. The unique PRA modeling considerations, in light of MSPI insights and lessons learned, are explored including evaluating the impact of the PRA model changes on MSPI, timing of PRA model issuance, and MSPI-specific model reviews. The final insight is that the PRA Modeler should fully understand the impact of model changes on the MSPI value as exceeding the exact value of 1E-06 can result in a white performance indicator. Source


Baranowsky P.W.,ERIN Engineering and Research
International Topical Meeting on Probabilistic Safety Assessment and Analysis 2013, PSA 2013 | Year: 2013

The generic fire ignition frequencies used in fire PRAs were originally developed and provided in NUREG/CR-6850 [1]. An interim revision of those fire frequencies to emphasize the more recent but still 10 year old data was developed by the Electric Power Research Institute (EPRI) [2] and incorporated in a supplement to NUREG/CR-6850 [3]. This paper describes the initial analysis of new fire event data to estimate updated fire ignition frequencies as a potential improvement for fire PRA applications. The new fire event data extends the EPRI fire events database an additional 10 years, through 2009. That data along with the existing historical data has been analyzed for consistency and applicability for estimating updated fire ignition frequencies. The fire event data were collected, coded and classified over time using somewhat different data sources with varying information quality and completeness. Therefore, data quality and quantitative factors have also been assessed to ensure proper use of data. In particular it was noted that the fire event data exhibits a discontinuity in the occurrence rate for the period around 1990-1999. Therefore, the methodology for estimating the updated fire ignition frequencies for fire PRAs that was previously developed was adjusted to account for the data anomalies. Then the fire event data was applied to assess fire ignition frequencies using the revised methods. The updated frequencies have been compared with fire frequencies currently being used in fire PRAs with initial insights as to differences indicated. Source


Sloane B.,ERIN Engineering and Research
International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015 | Year: 2015

The ASME/ANS Joint Committee on Nuclear Risk Management (JCNRM) is responsible for development and maintenance of standards and related guidance on nuclear facility probabilistic risk assessment (PRA) and risk management. The JCNRM Subcommittee on Standards Development (SC-SD) has responsibility of developing new PRA standards in accordance with JCNRM-adopted guidelines, and there are currently five new PRA standards in development and in various stages of the consensus ballot process. The JCNRM has recently implemented a process whereby a new standard that has been approved by technical committee consensus ballot and received administrative approval from both the ASME and ANS standards boards may be initially issued for a designated trial use period. The purpose of the trial use period, during which the standard, although approved within the ASME and ANS process, is not an ANSI (American National Standards Institute) standard, is to: (a) allow standard users and other stakeholders the opportunity to "test out" the standard and provide feedback to the SC-SD and writing groups regarding technical dfJIculties, application dfJIculties, editorial issues, and so forth, and (b) obtain feedback from stakeholders on selected technical issues that have been identfled by the standards writers as possibly involving limitations related to state of technology, lack of consensus, and so forth hut were deemed not so monumental as to preclude issuance of the standard. As of this submittal, one trial use standard has been issued (Non-Light Water Reactor PRA Standard) andfour others are planned to be issued for trial use within 18-24 months. This paper summarizes the current status of trial use standards and issues the SC-SD is evaluating regarding implementation of the trial use process, and provides initial feedback on how the process has been working to date. © 2015 by the American Nuclear Society. Source


Baranowsky P.W.,ERIN Engineering and Research
International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015 | Year: 2015

This paper presents a probabilistic concept for treating early phase fire growth from fire ignition to detection, suppression, and resultant fire severity in a PRA framework that estimates the likelihood of damaging fires in a manner more consistent with the operating experience fire data. The concept and data analysis were developed for fires in electrical cabinets. The data shows that the current approach used in fire PRAs does not realistically represent the early stage fire growth in timing, magnitude and damage likelihood. An event tree approach has been adopted using insights from the data for electrical cabinet fires from EPRI's Fire Events Data Base to estimate the likelihood that early stage fires (pre T- squared fire growth) will develop into more risk significant fires. The conceptual approach comports well with the operating experience data by design, showing a substantial reduction in the likelihood of early stage electrical cabinet fires progressing to more risk significant conditions. © 2015 by the American Nuclear Society. Source

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