PSAM 16 - Session Th05 Overview

PSAM 16 Conference Session Th05 Overview

Session Chair: Michelle (Shelby) Bensi (mbensi@umd.edu)

Paper 1 SV101

Lead Author: Lana Lawrence Co-author(s): Todd Anselmi, Todd.Anselmi@inl.gov Diego Mandelli, Diego.Mandelli@inl.gov Curtis Smith, Curtis.Smith@inl.gov

Guidance for Risk-Informed Reliability and Integrity Management Program Development
Every nuclear power plant in the U.S. and around the world is obligated to maintain high levels of safety with measures that ensure plant reliability and integrity. These programs have become increasingly risk-informed in recent years. New reactor designs are very focused on risk-informed approaches to support all stages of development—from initial design and licensing to plant operation and retirement. The License Modernization Project (LMP) initiative by the U.S. Nuclear Regulatory Commission (NRC) is just one example of a risk-informed approach being encouraged for implementation. The LMP initiative resulted in issuance of Regulatory Guide (RG) 1.233, "Guidance for a Technology-Inclusive, Risk-Informed, and Performance-Based Methodology to Inform the Licensing Basis and Content of Applications for Licenses, Certifications, and Approvals for Non-Light Water Reactors." RG 1.233 endorses Nuclear Energy Institute (NEI) 18-04, Revision 1, “Risk-Informed Performance-Based Guidance for Non-Light Water Reactor Licensing Basis Development,” as one acceptable method for non-LWR designers to use for selection of licensing-basis events (LBEs); classification and special treatments of structures, systems, and components (SSCs); and assessment of defense in depth (DID), activities that are fundamental to the safe design of non-LWRs. In August 2020, the NRC communicated to the American Society of Mechanical Engineers (ASME) that it has initiated efforts to review and endorse the 2019 Edition of ASME Boiler & Pressure Vessel Code (BPVC) Section XI, Division 2 (hereafter referred to as Division 2) for application to non-light-water reactors (LWRs). Draft Regulatory Guide DG-1383 was issued for public comments in September 2021 with full issuance expected in 2022. This endorsement adds urgency for developers of new reactor designs to understand how Division 2 is to be implemented. Regulatory Guide DG-1383 “describes an approach that is acceptable to the staff of the NRC for the development and implementation of a preservice (PSI) and inservice (ISI) program for non-light water reactors.” Division 2 also provides the requirements for the creation of the Reliability and Integrity Management (RIM) program for any type of non-LWR nuclear power plant. The RIM program can be beneficial to the industry by reducing implementation costs and providing consistency in implementation for users. However, because Division 2 complies with ISI requirements through application of processes that are common to current LWR designs, there is limited experience to draw from and limited guidance on meeting the requirements for the development of the risk-informed RIM program. Therefore, Idaho National Laboratory’s (INL) Regulatory Development R&D area supporting the Department of Energy’s (DOE) Advanced Reactor Demonstration Program initiated a project to develop guidance based on the pending Division 2 requirements for non-LWR developers through the establishment of the risk-informed RIM program. INL’s project covers a limited scope focused on a few key steps: - Plant, safety systems, and SSC reliability allocations - Identification and evaluation of RIM strategies - Evaluation of uncertainties. The scope was selected based on industry feedback about the development of the RIM program. INL’s project demonstrates the RIM development process using a case study that presents various possibilities and options for meeting RIM program requirements, including considerations of a tradeoff between reliability and economics, and optimization of design options. This paper presents activities, findings, and available outcomes of this project as well as identifies needs for additional research.

Guidance for Risk-Informed Reliability and Integrity Management Program Development

Every nuclear power plant in the U.S. and around the world is obligated to maintain high levels of safety with measures that ensure plant reliability and integrity. These programs have become increasingly risk-informed in recent years. New reactor designs are very focused on risk-informed approaches to support all stages of development—from initial design and licensing to plant operation and retirement. The License Modernization Project (LMP) initiative by the U.S. Nuclear Regulatory Commission (NRC) is just one example of a risk-informed approach being encouraged for implementation. The LMP initiative resulted in issuance of Regulatory Guide (RG) 1.233, "Guidance for a Technology-Inclusive, Risk-Informed, and Performance-Based Methodology to Inform the Licensing Basis and Content of Applications for Licenses, Certifications, and Approvals for Non-Light Water Reactors." RG 1.233 endorses Nuclear Energy Institute (NEI) 18-04, Revision 1, “Risk-Informed Performance-Based Guidance for Non-Light Water Reactor Licensing Basis Development,” as one acceptable method for non-LWR designers to use for selection of licensing-basis events (LBEs); classification and special treatments of structures, systems, and components (SSCs); and assessment of defense in depth (DID), activities that are fundamental to the safe design of non-LWRs. In August 2020, the NRC communicated to the American Society of Mechanical Engineers (ASME) that it has initiated efforts to review and endorse the 2019 Edition of ASME Boiler & Pressure Vessel Code (BPVC) Section XI, Division 2 (hereafter referred to as Division 2) for application to non-light-water reactors (LWRs). Draft Regulatory Guide DG-1383 was issued for public comments in September 2021 with full issuance expected in 2022. This endorsement adds urgency for developers of new reactor designs to understand how Division 2 is to be implemented. Regulatory Guide DG-1383 “describes an approach that is acceptable to the staff of the NRC for the development and implementation of a preservice (PSI) and inservice (ISI) program for non-light water reactors.” Division 2 also provides the requirements for the creation of the Reliability and Integrity Management (RIM) program for any type of non-LWR nuclear power plant. The RIM program can be beneficial to the industry by reducing implementation costs and providing consistency in implementation for users. However, because Division 2 complies with ISI requirements through application of processes that are common to current LWR designs, there is limited experience to draw from and limited guidance on meeting the requirements for the development of the risk-informed RIM program. Therefore, Idaho National Laboratory’s (INL) Regulatory Development R&D area supporting the Department of Energy’s (DOE) Advanced Reactor Demonstration Program initiated a project to develop guidance based on the pending Division 2 requirements for non-LWR developers through the establishment of the risk-informed RIM program. INL’s project covers a limited scope focused on a few key steps: - Plant, safety systems, and SSC reliability allocations - Identification and evaluation of RIM strategies - Evaluation of uncertainties. The scope was selected based on industry feedback about the development of the RIM program. INL’s project demonstrates the RIM development process using a case study that presents various possibilities and options for meeting RIM program requirements, including considerations of a tradeoff between reliability and economics, and optimization of design options. This paper presents activities, findings, and available outcomes of this project as well as identifies needs for additional research.

Paper SV101 | Download the paper file. | Download the presentation PowerPoint file.

Name: Lana Lawrence (svetlana.lawrence@inl.gov)

Bio: Lana Lawrence is the lead of the Risk-Informed Systems Analysis (RISA) pathway. In this role she oversees multiple research activities related to risk-informed approaches with the goal to enhance sustainability of existing NPPs via improved safety margins, gained economic efficiencies, and greater flexibility in operations and management. Ms. Lawrence is a PRA engineer who worked with multiple nuclear power plants on various risk-informed applications. She earned a B.S. in Civil (structural) Engineering from a Ukrainian university and a M.S. in Reliability Engineering from the University of Maryland. She is currently working towards her Ph.D. in Systems Engineering.

Country: USA
Company: Idaho National Laboratory
Job Title: Risk-Informed Systems Analysis Pathway Lead

Paper 2 EC304

Lead Author: Edward Chen Co-author(s): Han Bao han.bao@inl.gov Tate Shorthill tate.shorthill@inl.gov Carl Elks crelks@vcu.edu Nam Dinh ntdinh@ncsu.edu

Application of Orthogonal-Defect Classification for Software Reliability Analysis
Modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate risk methodologies by both the Nuclear Regulatory Commission and industry. This has resulted in hesitation for further modernization projects until a more unified methodology is recognized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) potential failure modes of a DI&C software system. The semantic classification model is used to address the question: how do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: given the connection between latent defects and software failure root causes, how can we quantify the risk (or reliability) of the software? A case study was conducted on a representative software platform (ChibiOS) running a sensor acquisition software developed by Virginia Commonwealth University. The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of existing methods.

Application of Orthogonal-Defect Classification for Software Reliability Analysis

Modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate risk methodologies by both the Nuclear Regulatory Commission and industry. This has resulted in hesitation for further modernization projects until a more unified methodology is recognized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) potential failure modes of a DI&C software system. The semantic classification model is used to address the question: how do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: given the connection between latent defects and software failure root causes, how can we quantify the risk (or reliability) of the software? A case study was conducted on a representative software platform (ChibiOS) running a sensor acquisition software developed by Virginia Commonwealth University. The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of existing methods.

Paper EC304 | Download the paper file. | Download the presentation PowerPoint file.

Name: Edward Chen (echen2@ncsu.edu)

Bio: Edward is a 4th year Ph.D. candidate researching risk and reliability in digital instrumentation and control systems at North Carolina State University under the direction of Dr. Nam Dinh. His primary areas of focus include risk quantification and model development in conventional PLC based as well as data-driven ML control and information systems. He has worked with multiple groups including Kairos power as a simulation developer for transient cases as well as a contractor for Idaho National Laboratories under the Light Water Sustainability Project. He has also worked on ARPA-e projects such as the Near Autonomous Management and Control system and has developed multiple data-driven autonomous safety systems.

Country: USA
Company: North Carolina State University
Job Title: Research Assistant

Paper 3 MA29

Lead Author: Matthew Humberstone Co-author(s): Keith Compton, Keith.Compton@nrc.gov Trey Hathaway, Alred.Hathaway@nrc.gov Kurt Vedros, Kurt.Vedros@inl.gov

The Impact of External Hazards and FLEX Credit in the Application of LMP for Operating Reactors
As part of the Nuclear Regulatory Commission’s (NRC’s) effort to provide resources to longer-term, forward looking research projects with potential regulatory benefits, a future focused research (FFR) project was established to study the implementation of the Licensing Modernization Project (LMP) methodology for the operating reactors. This research effort used the LMP methodology and applied the NRC’s Level 3 probabilistic risk assessment (PRA) model results to gain feasibility insights. The initial phase of this effort used results from a limited scope of the NRC’s level 3 PRA model to explore key risk-insights of the licensing basis for reactors licensed under Title 10 of the Code of Federal Regulations (10 CFR) Part 50. The next phase of this effort addressed in this paper uses the expanded results from the NRC’s level 3 PRA model that includes model enhancements. This paper compares the results derived from the level 1, level 2, and level 3 PRA models for internal events and internal floods with the results that include external events. Moreover, the paper uses this comparison to gain insights on the impact of modeling external hazards, identify implementation challenges, and explore the feasibility of using results that consider the impact of external hazards in the LMP framework. These PRA results are used in the context of the frequency consequence (F-C) curve to both gain experience with the overall LMP methodology’s risk-informed performance-based guidance and to identify key risk-insights on operating reactor technology. Furthermore, these insights provide an example of a “safety case” for operating plants which include discussions on the risk-important plant events, potential risk ranking of SSCs, and a risk-informed defense-in-depth evaluation of the plant. Insights may also support future studies to highlight portions of Part 50 that are the best candidates for further risk-informed considerations.

The Impact of External Hazards and FLEX Credit in the Application of LMP for Operating Reactors

As part of the Nuclear Regulatory Commission’s (NRC’s) effort to provide resources to longer-term, forward looking research projects with potential regulatory benefits, a future focused research (FFR) project was established to study the implementation of the Licensing Modernization Project (LMP) methodology for the operating reactors. This research effort used the LMP methodology and applied the NRC’s Level 3 probabilistic risk assessment (PRA) model results to gain feasibility insights. The initial phase of this effort used results from a limited scope of the NRC’s level 3 PRA model to explore key risk-insights of the licensing basis for reactors licensed under Title 10 of the Code of Federal Regulations (10 CFR) Part 50. The next phase of this effort addressed in this paper uses the expanded results from the NRC’s level 3 PRA model that includes model enhancements. This paper compares the results derived from the level 1, level 2, and level 3 PRA models for internal events and internal floods with the results that include external events. Moreover, the paper uses this comparison to gain insights on the impact of modeling external hazards, identify implementation challenges, and explore the feasibility of using results that consider the impact of external hazards in the LMP framework. These PRA results are used in the context of the frequency consequence (F-C) curve to both gain experience with the overall LMP methodology’s risk-informed performance-based guidance and to identify key risk-insights on operating reactor technology. Furthermore, these insights provide an example of a “safety case” for operating plants which include discussions on the risk-important plant events, potential risk ranking of SSCs, and a risk-informed defense-in-depth evaluation of the plant. Insights may also support future studies to highlight portions of Part 50 that are the best candidates for further risk-informed considerations.

Paper MA29 | Download the paper file. | Download the presentation PowerPoint file.

Name: Matthew Humberstone (Matthew.Humberstone@nrc.gov)

Bio: Dr. Matthew Humberstone is a Senior Reliability and Risk Analyst in the Division of Risk Analysis at the United States Nuclear Regulatory Commission (USNRC). Dr. Humberstone works in the Performance and Reliability Branch in the Office of Nuclear Regulatory Research (RES) which uses risk assessments and insights to support a broad range of regulatory applications. Dr. Humberstone joined the US NRC’s Nuclear Safety Professional Development program in 2010 and has held several different positions supporting several high-priority projects while at the NRC. Dr. Humberstone received his bachelor’s degree in engineering physics from New Mexico State University, a master's degree in statistics from the University of Tennessee, and a master’s degree and Ph.D. in nuclear engineering from the University of Tennessee.

Country: USA
Company: US NRC
Job Title: Senior Reliability and Risk Analyst

Paper 4 ST181

Lead Author: Stanislav Hustak

PSA Applications for Dukovany NPP
Reliability and Risk Department in UJV Rez, a. s., the Czech Republic, has developed and currently maintains Living PSA project for Dukovany NPP, a four-unit nuclear power plant in the Czech Republic. RiskSpectrum® PSA software has been used for development and quantification of the Living PSA model. It is an integrated model which comprises all initiating events, including internal and external hazards, for all plant operational modes in the same project. The PSA model is continuously updated and used extensively for various PSA applications at Dukovany NPP, such as risk monitoring, evaluation of Technical Specifications, event analysis, analysis of plant modifications etc. The use of the selected PSA applications to support Dukovany NPP risk management is required by the Czech regulatory Decree and supported by the Czech regulatory guidelines. The paper describes the selected PSA applications at Dukovany NPP that have been performed recently, namely evaluation of Technical Specifications and requirements for availability of diverse and mobile (DAM) equipment. This evaluation follows the respective Czech regulatory guideline. Several changes have been subsequently done in the plant Technical Specifications based on this evaluation. The paper also discusses the other recently performed PSA applications at Dukovany NPP as well as their outputs.

PSA Applications for Dukovany NPP

Reliability and Risk Department in UJV Rez, a. s., the Czech Republic, has developed and currently maintains Living PSA project for Dukovany NPP, a four-unit nuclear power plant in the Czech Republic. RiskSpectrum® PSA software has been used for development and quantification of the Living PSA model. It is an integrated model which comprises all initiating events, including internal and external hazards, for all plant operational modes in the same project. The PSA model is continuously updated and used extensively for various PSA applications at Dukovany NPP, such as risk monitoring, evaluation of Technical Specifications, event analysis, analysis of plant modifications etc. The use of the selected PSA applications to support Dukovany NPP risk management is required by the Czech regulatory Decree and supported by the Czech regulatory guidelines. The paper describes the selected PSA applications at Dukovany NPP that have been performed recently, namely evaluation of Technical Specifications and requirements for availability of diverse and mobile (DAM) equipment. This evaluation follows the respective Czech regulatory guideline. Several changes have been subsequently done in the plant Technical Specifications based on this evaluation. The paper also discusses the other recently performed PSA applications at Dukovany NPP as well as their outputs.

Paper ST181 | Download the paper file. | Download the presentation pdf file. Download the presentation PowerPoint file.

Name: Stanislav Hustak (stanislav.hustak@ujv.cz)

Bio: Mr. Stanislav Hustak works for Reliability and Risk Department in UJV Rez in the Czech Republic. He has more than 30 years’ experience in the area of PSA. Mr. Hustak is responsible for Living PSA project for Dukovany NPP in the Czech Republic. He is actively involving in many areas of PSA modelling and in integration of PSA model as well as in elaboration of PSA applications for Dukovany NPP. Mr. Hustak holds a Master of Science degree in nuclear engineering.

Country: CZE
Company: UJV Rez, a. s.
Job Title: Senior PSA Expert