PSAM 16 - Session M22 Overview

PSAM 16 Conference Session M22 Overview

Session Chair: Pavel Krcal (pavel.krcal@lr.org)

Paper 1 AN138,

Lead Author:

Paper AN138, | |

A PSAM Profile is not yet available for this author.

Paper 2 DK40

Lead Author: Dusko Kancev Co-author(s): Rainer Hausherr rhausherr@kkg.ch Gerben Dirksen gerben.dirksen@framatome.com

Development of a new plant-specific, full-scope industrial-scale L1/L2 PSA-model with the application of the new RiskSpectrum® Model Builder Tool
In July 2020, the NPP Goesgen-Daeniken AG (KKG) launched a new project (PSASPECTRUM) of refurbishment and restructuring of its plant PSA model in a new software environment and using new software tools. The main purpose of this project is the progression of the current KKG PSA model into the RiskSpectrum® software, including its update in terms of consideration of all the additional plant modifications, model & documentation review, necessary model & documentation corrections, increasing the level of modelling detail as well as improving the level of modelling and documentation consistency. Hence, with the PSASPECTRUM project, one will achieve a consistent and comprehensive PSA model and documentation, compiled within a state-of the-art PSA modelling software environment, allowing to perform the relevant PSA applications and to fulfil the national regulatory requirements more effectively and in a more efficient time manner. The ultimate goal of this project is to produce a full-scope, all POSs (full-power, low power & shutdown), all IEs classes (internal & external), all hazards (internal & external), fully coupled (L1, L1+, L2) plant model. One of the main highlights of the project is the application of the RiskSpectrum® Model Builder (RSMB) tool on the system level PSA modelling. The RSMB is a software tool for building and maintaining risk-, reliability and availability models. Building on the strength of KB3, originally developed and used by EDF for risk analysis across their critical infrastructure, RiskSpectrum Model Builder, accelerates the generation of risk and reliability analysis by automating and standardising the risk modelling process. By using this platform, EDF has experienced productivity gains of 40-80%. As such, the RSMB was commercialized by Lloyd`s Register RiskSpectrum AB in 2019/2020 and rendered compatible with the RiskSpectrum PSA platform as part of the RiskSpectrum suite. The three key features of the RSMB tool are improving the automation, acceleration and the standardisation of the risk and reliability modelling process: • Intuitive drag-and-drop interface to draw systems and subsystems based on the actual P&IDs; • Central knowledge base containing standardised definitions of systems, structures and components (SSCs) as well as their functional properties and constraints; • Automatic generation of fault trees and other risk models for each system design, with automatic export into RiskSpectrum PSA ready for further analysis and/or PSA-modelling further on, on the plant-level. The application of the tool offers higher grade of consistency in the PSA studies, the modelling assumptions are systematic and traceable, a higher grade of homogeneity among the system models is achieved. Also, once the PSA model is built by using the RSMB tool, then a rapid, efficient and systematic model update potential is ensured for the future. This paper presents a summary of the system-level PSA modelling using the RSMB Tool within the framework of the PSASPECTRUM project. A new method for pre-FMEA analysis, based on the PSA-relevant systems` P&IDs, is presented as the first step of the system-level PSA modelling. Each of the relevant systems P&ID is screened for PSA-relevant components, which are in turn then marked in a way that is reflecting their corresponding failure mode relevant for the analysed PSA system function. These pre-formatted P&IDs are then used as the basis for building the corresponding system function availability models with the RSMB tool. In this regards, three different systems are presented within this paper as case studies – the ECCS, the essential CCWS, the auxiliary/start-up FWS, as well as the conventional intercooling circuit system as one of the important support systems. Each of the automatically generated FTs to the corresponding system functions is subsequently discussed. FT`s automatic export into the main environment for the plant-level PSA-modelling, the RiskSpectrum PSA, is then demonstrated and its binding within the corresponding ET discussed. In summary, this study underlines the need and importance of a systematic, homogeneous, traceable and easily validatable approach with a minimal potential for human error for a PSA-modelling in industrial-scale projects.

Development of a new plant-specific, full-scope industrial-scale L1/L2 PSA-model with the application of the new RiskSpectrum® Model Builder Tool

In July 2020, the NPP Goesgen-Daeniken AG (KKG) launched a new project (PSASPECTRUM) of refurbishment and restructuring of its plant PSA model in a new software environment and using new software tools. The main purpose of this project is the progression of the current KKG PSA model into the RiskSpectrum® software, including its update in terms of consideration of all the additional plant modifications, model & documentation review, necessary model & documentation corrections, increasing the level of modelling detail as well as improving the level of modelling and documentation consistency. Hence, with the PSASPECTRUM project, one will achieve a consistent and comprehensive PSA model and documentation, compiled within a state-of the-art PSA modelling software environment, allowing to perform the relevant PSA applications and to fulfil the national regulatory requirements more effectively and in a more efficient time manner. The ultimate goal of this project is to produce a full-scope, all POSs (full-power, low power & shutdown), all IEs classes (internal & external), all hazards (internal & external), fully coupled (L1, L1+, L2) plant model. One of the main highlights of the project is the application of the RiskSpectrum® Model Builder (RSMB) tool on the system level PSA modelling. The RSMB is a software tool for building and maintaining risk-, reliability and availability models. Building on the strength of KB3, originally developed and used by EDF for risk analysis across their critical infrastructure, RiskSpectrum Model Builder, accelerates the generation of risk and reliability analysis by automating and standardising the risk modelling process. By using this platform, EDF has experienced productivity gains of 40-80%. As such, the RSMB was commercialized by Lloyd`s Register RiskSpectrum AB in 2019/2020 and rendered compatible with the RiskSpectrum PSA platform as part of the RiskSpectrum suite. The three key features of the RSMB tool are improving the automation, acceleration and the standardisation of the risk and reliability modelling process: • Intuitive drag-and-drop interface to draw systems and subsystems based on the actual P&IDs; • Central knowledge base containing standardised definitions of systems, structures and components (SSCs) as well as their functional properties and constraints; • Automatic generation of fault trees and other risk models for each system design, with automatic export into RiskSpectrum PSA ready for further analysis and/or PSA-modelling further on, on the plant-level. The application of the tool offers higher grade of consistency in the PSA studies, the modelling assumptions are systematic and traceable, a higher grade of homogeneity among the system models is achieved. Also, once the PSA model is built by using the RSMB tool, then a rapid, efficient and systematic model update potential is ensured for the future. This paper presents a summary of the system-level PSA modelling using the RSMB Tool within the framework of the PSASPECTRUM project. A new method for pre-FMEA analysis, based on the PSA-relevant systems` P&IDs, is presented as the first step of the system-level PSA modelling. Each of the relevant systems P&ID is screened for PSA-relevant components, which are in turn then marked in a way that is reflecting their corresponding failure mode relevant for the analysed PSA system function. These pre-formatted P&IDs are then used as the basis for building the corresponding system function availability models with the RSMB tool. In this regards, three different systems are presented within this paper as case studies – the ECCS, the essential CCWS, the auxiliary/start-up FWS, as well as the conventional intercooling circuit system as one of the important support systems. Each of the automatically generated FTs to the corresponding system functions is subsequently discussed. FT`s automatic export into the main environment for the plant-level PSA-modelling, the RiskSpectrum PSA, is then demonstrated and its binding within the corresponding ET discussed. In summary, this study underlines the need and importance of a systematic, homogeneous, traceable and easily validatable approach with a minimal potential for human error for a PSA-modelling in industrial-scale projects.

Paper DK40 | Download the paper file. | Download the presentation PowerPoint file.

Name: Dusko Kancev (dkancev@kkg.ch)

Bio: I am a PSA specialist, since 2014 employed at the NPP Goesgen – Daeniken, where I work mainly on development, upgrade, update of our PSA model. I hold a PhD (2012) in Nuclear Engineering from the University of Ljubljana, Slovenia and B.Sc. (2007) in Electrical Engineering from the University Ss. Cyril and Methodius, Skopje, Macedonia. Simultaneously with my PhD studies, I was working as a research assistant at the Reactor Engineering Division, Jozef Stefan Institute in Ljubljana. There I worked on development of time-dependent unavailability models in the nuclear industry; incorporation of ageing in PSA calculations; power systems reliability analysis. After the PhD, I did my postdoc research at the Joint Research Centre of the European Commission in Petten, NL. There I worked in the team of the Centralised EU Nuclear Safety Clearinghouse for Operational Experience Feedback, fostering the collection of operating experience from European nuclear regulators and operators.

Country: CHE
Company: NPP Goesgen - Daeniken
Job Title: PSA Specialist

Paper 3 JA278

Lead Author: James Knudsen Co-author(s): Curtis L. Smith (Curtis.Smith@inl.gov) Michael Calley (Michael.Calley@inl.gov)

Issues and Approaches Regarding Success Terms for Probabilistic Risk Assessment Models
Solving event tree accident sequences in probabilistic risk assessments (PRAs) involves assumptions about the success of systems (i.e., event tree top events). The primary assumption is that failure of the system is a rare event (i.e., a low probability of failure); therefore, the success probability is very close to 1.0. Under most conditions, this assumption is valid. However, such is not always the case. When event tree top events have higher failure probabilities—and thus success probabilities that are not close to 1.0—this assumption causes the sequences with success branches to be incorrect. To address this issue, it is necessary to properly account for the success probability of event tree top events in order to better quantify each sequence of the event tree. The current state of practice allows for some success event tree top events to be included in the accident sequence cut sets (i.e., only single basic events representing the success term and its value). In addition, sequence cut sets are typically quantified using the minimal cut set upper bound approximation versus the exact solution. Combining success terms in the sequence cut sets with the minimal cut set upper bound approximation tends to make the sequence’s quantification results appear close to the exact results. This paper presents two approaches to better quantify event tree sequences featuring cut sets that include success terms with low values (i.e., the respective failure value is higher). One approach quantifies each sequence, taking into account the success term at its low value by using the minimal cut set upper bound approximation. The second approach is similar, except that the success term is quantified via a binary decision diagram (BDD) approach, and the result is them multiplied back into each sequence cut set. These two approaches will be evaluated using a complex PRA model for two standard event trees. The evaluation will involve a loss of offsite power event and a seismic external event. Both of these event trees contain complex systems that can carry a high probability of failure The pros and cons of these approaches will be discussed along with the overall conclusions.

Issues and Approaches Regarding Success Terms for Probabilistic Risk Assessment Models

Solving event tree accident sequences in probabilistic risk assessments (PRAs) involves assumptions about the success of systems (i.e., event tree top events). The primary assumption is that failure of the system is a rare event (i.e., a low probability of failure); therefore, the success probability is very close to 1.0. Under most conditions, this assumption is valid. However, such is not always the case. When event tree top events have higher failure probabilities—and thus success probabilities that are not close to 1.0—this assumption causes the sequences with success branches to be incorrect. To address this issue, it is necessary to properly account for the success probability of event tree top events in order to better quantify each sequence of the event tree. The current state of practice allows for some success event tree top events to be included in the accident sequence cut sets (i.e., only single basic events representing the success term and its value). In addition, sequence cut sets are typically quantified using the minimal cut set upper bound approximation versus the exact solution. Combining success terms in the sequence cut sets with the minimal cut set upper bound approximation tends to make the sequence’s quantification results appear close to the exact results. This paper presents two approaches to better quantify event tree sequences featuring cut sets that include success terms with low values (i.e., the respective failure value is higher). One approach quantifies each sequence, taking into account the success term at its low value by using the minimal cut set upper bound approximation. The second approach is similar, except that the success term is quantified via a binary decision diagram (BDD) approach, and the result is them multiplied back into each sequence cut set. These two approaches will be evaluated using a complex PRA model for two standard event trees. The evaluation will involve a loss of offsite power event and a seismic external event. Both of these event trees contain complex systems that can carry a high probability of failure The pros and cons of these approaches will be discussed along with the overall conclusions.

Paper JA278 | Download the paper file. | Download the presentation PowerPoint file.

Name: James Knudsen (james.knudsen@inl.gov)

Bio: Mr. Knudsen is Risk Analysis Engineer with over twenty years of probabilistic risk assessment (PRA) experience including all aspects of model development. He is the project lead for the different Standardized Plant Analysis Risk (SPAR) model development and enhancement projects and also the project lead for the Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) software program developed for the NRC. He provides instruction and technical support to NRC and NASA staff on the use of the risk models. He also provides technical training in PRA concepts and PRA modeling along with the use of the SAPHIRE PRA code.

Country: USA
Company: Idaho National Laboratory
Job Title: Engineer

Paper 4 JS149

Lead Author: Joy Shen Co-author(s): Michelle T Bensi: mbensi@umd.edu Mohammad Modarres: modarres@umd.edu

Synthesis of Questionnaire Insights Regarding Current PRA and Additional Tools
This paper presents and analyzes the responses to a questionnaire on the nuclear industry's insights on current probabilistic risk assessment (PRA) tools. Many PRA tools traditionally use event tree and fault tree analysis. While these tools are well-established and developed, they are not without limitations. Additionally, the PRA scope is evolving to include other areas of interest, such as external hazard PRAs, human reliability assessments, or dynamic PRAs. A questionnaire was created to engage PRA practitioners and gather insights about the community's views on the advantages/limitations of PRA tools and trending needs. The questionnaire requested anonymous feedback and insights on applying legacy, conventional, and other PRA tools. Additionally, a review/survey was performed of existing resources to supplement the questionnaire and develop a comprehensive analysis. The questionnaire and survey reveal that the needs of the PRA community are evolving, as are the tools they use to accomplish this change. The high-level needs of the PRA community include dynamic PRAs, external hazard analyses, and collaboration.

Synthesis of Questionnaire Insights Regarding Current PRA and Additional Tools

This paper presents and analyzes the responses to a questionnaire on the nuclear industry's insights on current probabilistic risk assessment (PRA) tools. Many PRA tools traditionally use event tree and fault tree analysis. While these tools are well-established and developed, they are not without limitations. Additionally, the PRA scope is evolving to include other areas of interest, such as external hazard PRAs, human reliability assessments, or dynamic PRAs. A questionnaire was created to engage PRA practitioners and gather insights about the community's views on the advantages/limitations of PRA tools and trending needs. The questionnaire requested anonymous feedback and insights on applying legacy, conventional, and other PRA tools. Additionally, a review/survey was performed of existing resources to supplement the questionnaire and develop a comprehensive analysis. The questionnaire and survey reveal that the needs of the PRA community are evolving, as are the tools they use to accomplish this change. The high-level needs of the PRA community include dynamic PRAs, external hazard analyses, and collaboration.

Paper JS149 | Download the paper file. | Download the presentation PowerPoint file.

Name: Joy Shen (jshen132@umd.edu)

Bio:

Country: ---
Company:
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