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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures

This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models

In a standard Bayesian approach to the alpha-factor model for common-cause failure, a precise Dirichlet prior distribution models epistemic uncertainty in the alpha-factors. This Dirichlet prior is then updated with observed data to obtain a posterior distribution, which forms the basis for further inferences. In this paper, we adapt the imprecise Dirichlet model of Walley to represent epistemic uncertainty in the alpha-factors. In this approach, epistemic uncertainty is expressed more cautiously via lower and upper expectations for each alpha-factor, along with a learning parameter which determines how quickly the model learns from observed data. For this application, we focus on elicitation of the learning parameter, and find that values in the range of 1 to 10 seem reasonable. The approach is compared with Kelly and Atwood's minimally informative Dirichlet prior for the alpha-factor model, which incorporated precise mean values for the alpha-factors, but which was otherwise quite diffuse. Next, we explore the use of a set of Gamma priors to model epistemic uncertainty in the marginal failure rate, expressed via a lower and upper expectation for this rate, again along with a learning parameter. As zero counts are generally less of an issue here, we find that the choice of this learning parameter is less crucial. Finally, we demonstrate how both epistemic uncertainty models can be combined to arrive at lower and upper expectations for all common-cause failure rates. Thereby, we effectively provide a full sensitivity analysis of common-cause failure rates, properly reflecting epistemic uncertainty of the analyst on all levels of the common-cause failure model.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Common Cause Failure Analysis for Nuclear Power Plant Instrumentation and Control Systems

This presentation is prepared for the IAEA Virtual Consultancy Meeting on Preparation of a Coordinated Research Project on Common Cause Failures in Nuclear Power Plant Instrumentation and Control Systems from February 5 ? 8, 2024. It provides an overview of the INL activities on the common cause failure analysis for instrumentation and control system in nuclear power plants.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Developing Component-Specific Prior Distributions for Common Cause Failure Alpha Factors

This report presents the development of component-specific common cause failure (CCF) prior distributions for five component categories: pump, valve, strainer, generator, and other. For ease in comparing these component-specific CCF priors with the 2015 generic CCF priors, the same method used to develop the 2015 generic CCF priors was also employed in this report, along with the same set of failure data (1997–2015) featured in INL/EXT-21-43723. For selected CCF templates, this report also evaluates the effects of applying component-specific priors to CCF parameters.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

PV Inverter Failures Cause AC Breaker Damage - Power Quality

This poster discusses how PV inverter failures cause AC breaker damage and is intended to help system owners identify power quality issues and origins, help inverter and/or circuit breaker manufacturers develop safer failure modes, and develop addendums to standards for failure testing of breakers and inverters.

arc↗
DOE OSTI2017

NRC technical basis for evaluation of its position on protection against common cause failure in digital systems used in nuclear power plants - 378

Digital technology has advantages over analog systems, including automated monitoring and alerts for standby safety functions, and predictive algorithms to maintain critical safety systems. Additionally, digital technology generally has higher reliability and can be designed to reduce single point vulnerabilities. For these reasons many nuclear plants have applied digital technology to safety and non-safety related applications, including reactor protection system, feedwater and turbine controls, etc. with a corresponding significant improvement in trip reduction. Nonetheless, digital instrumentation and control (I and C) systems also present potential new vulnerabilities that need to be assessed, including potential failures due to increased complexity of digital systems, the introduction of unique failure modes due to software (including software common cause failure (CCF)), and limited operating history of digital systems in nuclear safety related applications compared to analog systems. The fact that software is intangible means that common methods, such as analysis or testing, used for detecting CCF may not be effective when applied to software. Consequently, digital technology is perceived to pose a potential risk from the introduction of undetected systematic faults that could result in CCF. Despite the I and C system upgrades and modifications performed to date, the U.S. Nuclear Regulatory Commission (NRC) and industry stakeholders have identified the need to modernize the regulatory infrastructure to efficiently address risks associated with the use of digital technology for nuclear safety applications and address regulatory uncertainties. The NRC's current position on CCF is guided by the staff requirements memorandum (SRM) on SECY 93-087. The SRM provides specific acceptance criteria for the evaluation of CCF, which the staff implemented in the Branch Technical Position (BTP) 7-19. However, industry stakeholders have proposed using methods to characterize the likelihood of software CCF and eliminate it from further consideration in a defense-in-depth and diversity analysis. The NRC's current position does not consider these alternatives, and thus corresponding acceptance criteria is not currently available. The work discussed in this paper assesses the underlying technical basis associated with CCF, provides technical support for updating the NRC position and considers proposed methods for addressing potential CCF in digital systems while enhancing efficiency, clarity, and confidence. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Taxonomy for Common-Cause Failure Vulnerability and Mitigation

Applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The potential for CCF vulnerability inhibits I&C modernization, thereby challenging the long-term sustainability of existing plants. For new plants and advanced reactor concepts, concern about CCF vulnerability in highly integrated digital I&C systems imposes a design burden that results in higher costs and increased complexity. The regulatory uncertainty in determining which mitigation strategies will be acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. To address the conditions that constrain the transition to digital I&C technology by the US nuclear industry, crosscutting research is needed to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for nuclear power plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is investigating mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive basis to qualify digital technology for nuclear power applications. This report documents the development of a CCF taxonomy. The basis for the CCF taxonomy was generated by determining consistent terminology and establishing a classification approach. The terminology is based on definitions from standards, guides, and relevant nuclear power industry technical reports. The classification approach is derived from identified classification schemes focused on I&C systems and key characteristics, including failure modes. The CCF taxonomy provides the basis for a systematic organization of key systems aspects relevant to analyzing the potential for CCF vulnerability and the suitability of mitigation techniques. Development of an effective CCF taxonomy will help to provide a framework for establishing the objective analysis and assessment capabilities desired to facilitate rigorous identification of fault types and triggers that are the fundamental elements of CCF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Identification of Modeling Approaches To Support Common-Cause Failure Analysis

Experience with applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The impact of CCF vulnerability is to inhibit I&C modernization and, thereby, challenge the long-term sustainability of existing plants. For new plants and advanced reactor concepts, the issue of CCF vulnerability for highly integrated digital I&C systems imposes a design burden resulting in higher costs and increased complexity. The regulatory uncertainty regarding which mitigation strategies are acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. The conditions that constrain the transition to digital I&C technology by the U.S. nuclear industry require crosscutting research to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for usage in Nuclear Power Plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is conducting an investigation into mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive technical basis for establishing the qualification of digital technology for nuclear power applications. This report documents the investigation of modeling approaches for representing failure of I&C systems. Failure models are used when there is a need to analyze how the probability of success (or failure) of a system depends on the success (or failure) of individual elements. If these failure models are extensible to represent CCF, then they can be employed to support analysis of CCF vulnerabilities and mitigation strategies. Specifically, the research findings documented in this report identify modeling approaches that can be adapted to contribute to the basis for developing systematic methods, quantifiable measures, and objective criteria for evaluating CCF vulnerabilities and mitigation strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Common Cause Failure Evaluation of High Safety-significant Safety-related Digital Instrumentation and Control Systems

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes a Platform for Risk Assessment of DI&C (PRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of PRADIC on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In PRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that PRADIC can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Impacts of common cause failure regulatory requirements on protection system architectures - 304

Regulatory-based design considerations for potential common cause failures (CCF) in digital instrumentation and control (I and C) systems have evolved over time and have impacted the development of protection system I and C architectures. The single failure criterion used to be the main design driver for a protection system I and C architecture and resulted in the familiar four-fold and three-fold system architectures. The single failure criterion has now been replaced by the conservative assumptions associated with digital CCF concerns (i.e., assumed digital CCF coincident with an anticipated operational transient or postulated accident) which are classified as 'beyond design basis events' by regulatory authorities. It is unusual for a beyond design basis event to be the controlling factor for a safety system design but that is now the reality for I and C system designers. The preferred regulatory solution is to introduce diversity into I and C system designs to guard against the general concern of digital CCF. However, the lack of clear criteria on how to define sufficient diversity (i.e., how much, what kind, and whether it is linked to identified digital CCF vulnerabilities) had led to more complex I and C architectures. The trend has been towards lengthy and more difficult reviews for the treatment of digital CCF vulnerabilities and I and C system architectures because of the subjective definition of digital CCF vulnerabilities and the lack of clear acceptance criteria for diversity strategy. Improvement in the treatment of digital CCF is needed to reverse the trend of increased I and C system architecture complexity and longer regulatory reviews. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Common Cause Failure Evaluation of High Safety Significant Safety-related Digital Instrumentation and Control Systems using IRADIC Technology

Digital instrumentation and control (DI&C) systems in nuclear power plants (NPPs) have many advantages over analog systems but also pose different engineering and technical challenges, such as potential threats due to common cause failures (CCFs). This paper proposes an integrated risk assessment technology for DI&C systems (IRADIC) developed by Idaho National Laboratory for dealing with potential software CCFs in DI&C systems of NPPs. The methodology development of the IRADIC technology on the quantitative evaluation of software CCFs in high safety-significant safety-related DI&C systems in NPPs is illustrated in this paper. In IRADIC, qualitative hazard analysis and quantitative reliability and consequence analysis are successively implemented to obtain quantitative risk information, compare with respective risk evaluation acceptance criteria, and provide suggestions for risk reduction and design optimization. A comprehensive case study was also performed and documented in this paper. Results show that the IRADIC technology can effectively identify potential digital-based CCFs, estimate their failure probabilities, and evaluate their impacts to system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Feasibility Study of Developing Alternative Common-Cause Failure Model for Event Assessment

This report is a revision of the original report, INL/LTD-14-33376. The original report, which was a limited distribution to the Nuclear Regulatory Commission (NRC) only and not available to the public, was revised as this report for public distribution. The report presents the feasibility study of alternative common-cause failure (CCF) models that could be used for event assessment in the Standardized Plant Analysis Risk (SPAR) models. The current CCF model used by the SPAR models is the alpha factor model. The proposed alternative CCF models are the partial alpha factor model and general dependency model. These alternative CCF models are reviewed and compared to the current alpha factor model, with the partial alpha factor model being identified as the preferred CCF model that could be used for event assessment in the SPAR models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors

This report is a revision of the original report, INL/LTD-17-43723. Distribution of the original report was to the Nuclear Regulatory Commission (NRC) only, and the report was not made available to the public. The original report was revised as this report for public distribution. This report presents the latest update of generic prior distributions for common cause failure (CCF) alpha factors, as well as the development of new generic prior distributions for CCF causal alpha factors. The history of CCF treatment and parameter estimations is reviewed. The existing process for developing generic prior distributions is reviewed and used to develop new priors for CCF alpha factors and causal alpha factors. For causal alpha factors, different priors are developed for the five different CCF cause groups: Component (GC), Design (GD), Environment (GE), Human (GH), and Other (GO). These generic prior distributions could be used in the Standardized Plant Analysis Risk (SPAR) models for CCF parameter estimation. The issues and preliminary thoughts regarding prior distribution development are documented. Potential future work is then proposed for improving the process of developing priors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Here, this paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

42 ENGINEERING↗
DOE OSTI2022

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Technical Basis for Evaluating Software-Related Common-Cause Failures

The instrumentation and control (I&C) system architecture at a nuclear power plant (NPP) incorporates protections against common-cause failures (CCFs) through the use of diversity and defense-in-depth. Even for well-established analog-based I&C system designs, the potential for CCFs of multiple systems (or redundancies within a system) constitutes a credible threat to defeating the defense-in-depth provisions within the I&C system architectures. The integration of digital technologies into the I&C systems provides many advantages compared to the aging analog systems with respect to reliability, maintenance, operability, and cost effectiveness. However, maintaining the diversity and defense-in-depth for both the hardware and software within the digital system is challenging. In fact, the introduction of digital technologies may actually increase the potential for CCF vulnerabilities because of the introduction of undetected systematic faults. These systematic faults are defined as a “design fault located in a software component” and at a high level, are predominately the result of (1) errors in the requirement specification, (2) inadequate provisions to account for design limits (e.g., environmental stress), or (3) technical faults incorporated in the internal system (or architectural) design or implementation. Other technology-neutral CCF concerns include hardware design errors, equipment qualification deficiencies, installation or maintenance errors, instrument loop scaling and setpoint mistakes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures

Digital Instrumentation and Control (I&C) systems have a key role in nuclear power plants in the upgrade of aging analog systems. Digital systems improve plant safety and reliability through features such as increased hardware reliability and stability and improved failure detection capability. There is no consensus on which of the current probabilistic risk assessment methods are most suitable for use in the reliability analysis of digital I&C systems. While the traditional event-tree/fault-tree (ET/FT) approach is still used for their reliability modeling, there are concerns regarding this approach in properly accounting for dynamic interactions among system components since potentially significant dependencies among failure events may not be identified and/or their likelihood may not be properly quantified. Dynamic methodologies are expected to provide a much more accurate representation of probabilistic evolution of the I&C systems in time due to their capability to more properly account for complex interactions than the static approach. The applicability of dynamic PRA methodologies for digital I&C system is investigated using the criteria presented in the NUREG/CR-6901, and the comparisons made in NUREG/CR-6901 are updated in light of the latest studies. The Dynamic Event Tree (DET) approach has been identified as one of the top dynamic methods when evaluated against the requirements for the reliability modeling of digital I&C systems. The DET method is a strong candidate for integration into existing PRA studies, as it bears many similarities to the traditional ET approach. In this study, the DET approach has been applied to the Plant Protection System of the APR1400 design, and the results are compared to results from its available traditional ET/FT analysis. Possible approaches to evaluate and quantify the effects of common cause failures on system safety using dynamic methods are also examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗