Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

This report reviews the current state of the art of prognostics and health management (PHM) for nuclear power systems and related technology currently applied in field or under development in other technological application areas, as well as key research needs and technical gaps for increased use of PHM in nuclear power systems. The historical approach to monitoring and maintenance in nuclear power plants (NPPs), including the Maintenance Rule for active components and Aging Management Plans for passive components, are reviewed. An outline is given for the technical and economic challenges that make PHM attractive for both legacy plants through Light Water Reactor Sustainability (LWRS) and new plant designs. There is a general introduction to PHM systems for monitoring, fault detection and diagnostics, and prognostics in other, non-nuclear fields. The state of the art for health monitoring in nuclear power systems is reviewed. A discussion of related technologies that support the application of PHM systems in NPPs, including digital instrumentation and control systems, wired and wireless sensor technology, and PHM software architectures is provided. Appropriate codes and standards for PHM are discussed, along with a description of the ongoing work in developing additional necessary standards. Finally, an outline of key research needs and opportunities that must be addressed in order to support the application of PHM in legacy and new NPPs is presented

Technical Needs for Enhancing Risk Monitors with Equipment Condition Assessment for Advanced Small Modular Reactors

Advanced small modular reactors (aSMRs) can provide the United States with a safe, sustainable, and carbon-neutral energy source. The controllable day-to-day costs of aSMRs are expected to be dominated by operation and maintenance costs. Health and condition assessment coupled with online risk monitors can potentially enhance affordability of aSMRs through optimized operational planning and maintenance scheduling. Currently deployed risk monitors are an extension of probabilistic risk assessment (PRA). For complex engineered systems like nuclear power plants, PRA systematically combines event likelihoods and the probability of failure (POF) of key components, so that when combined with the magnitude of possible adverse consequences to determine risk. Traditional PRA uses population-based POF information to estimate the average plant risk over time. Currently, most nuclear power plants have a PRA that reflects the as-operated, as-modified plant; this model is updated periodically, typically once a year. Risk monitors expand on living PRA by incorporating changes in the day-by-day plant operation and configuration (e.g., changes in equipment availability, operating regime, environmental conditions). However, population-based POF (or population- and time-based POF) is still used to populate fault trees. Health monitoring techniques can be used to establish condition indicators and monitoring capabilities that indicate the component-specific POF at a desired point in time (or over a desired period), which can then be incorporated in the risk monitor to provide a more accurate estimate of the plant risk in different configurations. This is particularly important for active systems, structures, and components (SSCs) proposed for use in aSMR designs. These SSCs may differ significantly from those used in the operating fleet of light-water reactors (or even in LWR-based SMR designs). Additionally, the operating characteristics of aSMRs can present significantly different requirements, including the need to operate in different coolant environments, higher operating temperatures, and longer operating cycles between planned refueling and maintenance outages. These features, along with the relative lack of operating experience for some of the proposed advanced designs, may limit the ability to estimate event probability and component POF with a high degree of certainty. Incorporating real-time estimates of component POF may compensate for a relative lack of established knowledge about the long-term component behavior and improve operational and maintenance planning and optimization. The particular eccentricities of advanced reactors and small modular reactors provide unique challenges and needs for advanced instrumentation, control, and human-machine interface (ICHMI) techniques such as enhanced risk monitors (ERM) in aSMRs. Several features of aSMR designs increase the need for accurate characterization of the real-time risk during operation and maintenance activities. A number of technical gaps in realizing ERM exist, and these gaps are largely independent of the specific reactor technology. As a result, the development of a framework for ERM would enable greater situational awareness regardless of the specific class of reactor technology. A set of research tasks are identified in a preliminary research plan to enable the development, testing, and demonstration of such a framework. Although some aspects of aSMRs, such as specific operational characteristics, will vary and are not now completely defined, the proposed framework is expected to be relevant regardless of such uncertainty. The development of an ERM framework will provide one of the key technical developments necessary to ensure the economic viability of aSMRs

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants

This report describes the status of ongoing research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions

Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery

Preprocessing software, which converts large instrumental data sets into a manageable format for data analysis, is crucial for the discovery of chemical signatures in metabolomics, chemical forensics, and other signature-focused disciplines. Here, four freely available and published preprocessing tools known as MetAlign, MZmine, SpectConnect, and XCMS were evaluated for impurity profiling using nominal mass GC/MS data and accurate mass LC/MS data. Both data sets were previously collected from the analysis of replicate samples from multiple stocks of a nerve-agent precursor and method blanks. Parameters were optimized for each of the four tools for the untargeted detection, matching, and cataloging of chromatographic peaks from impurities present in the stock samples. The peak table generated by each preprocessing tool was analyzed to determine the number of impurity components detected in all replicate samples per stock and absent in the method blanks. A cumulative set of impurity components was then generated using all available peak tables and used as a reference to calculate the percent of component detections for each tool, in which 100% indicated the detection of every known component present in a stock. For the nominal mass GC/MS data, MetAlign had the most component detections followed by MZmine, SpectConnect, and XCMS with detection percentages of 83, 60, 47, and 41%, respectively. For the accurate mass LC/MS data, the order was MetAlign, XCMS, and MZmine with detection percentages of 80, 45, and 35%, respectively. SpectConnect did not function for the accurate mass LC/MS data. Larger detection percentages were obtained by combining the top performer with at least one of the other tools such as 96% by combining MetAlign with MZmine for the GC/MS data and 93% by combining MetAlign with XCMS for the LC/MS data. In terms of quantitative performance, the reported peak intensities from each tool had averaged absolute biases (relative to peak intensities obtained using instrument software) of 41, 4.4, 1.3 and 1.3% for SpectConnect, MetAlign, XCMS, and MZmine, respectively, for the GC/MS data. For the LC/MS data, the averaged absolute biases were 22, 4.5, and 3.1% for MetAlign, MZmine, and XCMS, respectively. In summary, MetAlign performed the best in terms of the number of component detections; however, more than one preprocessing tool should be considered to avoid missing impurities or other trace components as potential chemical signatures

Advanced Instrumentation, Information, and Control System Technologies: Nondestructive Examination Technologies - FY11 Report

Licensees of commercial nuclear power plants in the US are expected to submit license renewal applications for the period of operation of 60 to 80 years which has also been referred to as long term operation (LTO). The greatest challenges to LTO are associated with degradation of passive components as active components are routinely maintained and repaired or placed through maintenance programs. Some passive component degradation concerns include stress corrosion cracking (SCC) of metal components, radiation induced embrittlement of the reactor pressure vessel (RPV), degradation of buried piping, degradation of concrete containment structures, and degradation of cables. Proactive management of passive component aging employs three important elements including online monitoring of degradation, early detection of degradation at precursor stages, and application of prognostics for the prediction of remaining useful life (RUL). This document assesses several nondestructive examination (NDE) measurement technologies for integration into proactive aging management programs. The assessment is performed by discussing the three elements of proactive aging management identified above, considering the current state of the industry with respect to adopting these key elements, and analyzing measurement technologies for monitoring large cracks in metal components, monitoring early degradation at precursor stages, monitoring the degradation of concrete containment structures, and monitoring the degradation of cables. Specific and general needs have been identified through this assessment. General needs identified include the need for environmentally rugged sensors are needed that can operate reliably in an operating reactor environment, the need to identify parameters from precursor monitoring technologies that are unambiguously correlated with the level of pre-macro defect damage, and a methodology for identifying regions where precursor damage is most likely to initiate

Technical Report on Preliminary Methodology for Enhancing Risk Monitors with Integrated Equipment Condition Assessment

Small modular reactors (SMRs) generally include reactors with electric output of ~350 MWe or less (this cutoff varies somewhat but is substantially less than full-size plant output of 700 MWe or more). Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. AdvSMRs may provide a longer-term alternative to traditional light-water reactors (LWRs) and SMRs based on integral pressurized water reactor concepts currently being considered. Enhancing affordability of AdvSMRs will be critical to ensuring wider deployment. AdvSMRs suffer from loss of economies of scale inherent in small reactors when compared to large (~greater than 600 MWe output) reactors. Some of this loss can be recovered through reduced capital costs through smaller size, fewer components, modular fabrication processes, and the opportunity for modular construction. However, the controllable day-to-day costs of AdvSMRs will be dominated by operation and maintenance (O&M) costs. Technologies that help characterize real-time risk are important for controlling O&M costs. Risk monitors are used in current nuclear power plants to provide a point-in-time estimate of the system risk given the current plant configuration (e.g., equipment availability, operational regime, and environmental conditions). However, current risk monitors are unable to support the capability requirements listed above as they do not take into account plant-specific normal, abnormal, and deteriorating states of active components and systems. This report documents technology developments that are a step towards enhancing risk monitors that, if integrated with supervisory plant control systems, can provide the capability requirements listed and meet the goals of controlling O&M costs. The report describes research results from an initial methodology for enhanced risk monitors by integrating real-time information about equipment condition and POF into risk monitors

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

This report reviews the current state of the art of prognostics and health management (PHM) for nuclear power systems and related technology currently applied in field or under development in other technological application areas, as well as key research needs and technical gaps for increased use of PHM in nuclear power systems. The historical approach to monitoring and maintenance in nuclear power plants (NPPs), including the Maintenance Rule for active components and Aging Management Plans for passive components, are reviewed. An outline is given for the technical and economic challenges that make PHM attractive for both legacy plants through Light Water Reactor Sustainability (LWRS) and new plant designs. There is a general introduction to PHM systems for monitoring, fault detection and diagnostics, and prognostics in other, non-nuclear fields. The state of the art for health monitoring in nuclear power systems is reviewed. A discussion of related technologies that support the application of PHM systems in NPPs, including digital instrumentation and control systems, wired and wireless sensor technology, and PHM software architectures is provided. Appropriate codes and standards for PHM are discussed, along with a description of the ongoing work in developing additional necessary standards. Finally, an outline of key research needs and opportunities that must be addressed in order to support the application of PHM in legacy and new NPPs is presented

A Review of Sensor Calibration Monitoring for Calibration Interval Extension in Nuclear Power Plants

Currently in the United States, periodic sensor recalibration is required for all safety-related sensors, typically occurring at every refueling outage, and it has emerged as a critical path item for shortening outage duration in some plants. Online monitoring can be employed to identify those sensors that require calibration, allowing for calibration of only those sensors that need it. International application of calibration monitoring, such as at the Sizewell B plant in United Kingdom, has shown that sensors may operate for eight years, or longer, within calibration tolerances. This issue is expected to also be important as the United States looks to the next generation of reactor designs (such as small modular reactors and advanced concepts), given the anticipated longer refueling cycles, proposed advanced sensors, and digital instrumentation and control systems. The U.S. Nuclear Regulatory Commission (NRC) accepted the general concept of online monitoring for sensor calibration monitoring in 2000, but no U.S. plants have been granted the necessary license amendment to apply it. This report presents a state-of-the-art assessment of online calibration monitoring in the nuclear power industry, including sensors, calibration practice, and online monitoring algorithms. This assessment identifies key research needs and gaps that prohibit integration of the NRC-approved online calibration monitoring system in the U.S. nuclear industry. Several needs are identified, including the quantification of uncertainty in online calibration assessment; accurate determination of calibration acceptance criteria and quantification of the effect of acceptance criteria variability on system performance; and assessment of the feasibility of using virtual sensor estimates to replace identified faulty sensors in order to extend operation to the next convenient maintenance opportunity. Understanding the degradation of sensors and the impact of this degradation on signals is key to developing technical basis to support acceptance criteria and set point decisions, particularly for advanced sensors which do not yet have a cumulative history of operating performance

Light Water Reactor Sustainability (LWRS) Program ? Non-Destructive Evaluation (NDE) R&D Roadmap for Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants

The purpose of the non-destructive evaluation (NDE) R&D Roadmap for Cables is to support the Materials Aging and Degradation (MAaD) R&D pathway. The focus of the workshop was to identify the technical gaps in detecting aging cables and predicting their remaining life expectancy. The workshop was held in Knoxville, Tennessee, on July 30, 2012, at Analysis and Measurement Services Corporation (AMS) headquarters. The workshop was attended by 30 experts in materials, electrical engineering, U.S. Nuclear Regulatory Commission (NRC), U.S. Department of Energy (DOE) National Laboratories (Oak Ridge National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, and Idaho National Engineering Laboratory), NDE instrumentation development, universities, commercial NDE services and cable manufacturers, and Electric Power Research Institute (EPRI). The motivation for the R&D roadmap comes from the need to address the aging management of in-containment cables at nuclear power plants (NPPs)

A Review of Sensor Calibration Monitoring for Calibration Interval Extension in Nuclear Power Plants

Currently in the United States, periodic sensor recalibration is required for all safety-related sensors, typically occurring at every refueling outage, and it has emerged as a critical path item for shortening outage duration in some plants. Online monitoring can be employed to identify those sensors that require calibration, allowing for calibration of only those sensors that need it. International application of calibration monitoring, such as at the Sizewell B plant in United Kingdom, has shown that sensors may operate for eight years, or longer, within calibration tolerances. This issue is expected to also be important as the United States looks to the next generation of reactor designs (such as small modular reactors and advanced concepts), given the anticipated longer refueling cycles, proposed advanced sensors, and digital instrumentation and control systems. The U.S. Nuclear Regulatory Commission (NRC) accepted the general concept of online monitoring for sensor calibration monitoring in 2000, but no U.S. plants have been granted the necessary license amendment to apply it. This report presents a state-of-the-art assessment of online calibration monitoring in the nuclear power industry, including sensors, calibration practice, and online monitoring algorithms. This assessment identifies key research needs and gaps that prohibit integration of the NRC-approved online calibration monitoring system in the U.S. nuclear industry. Several needs are identified, including the quantification of uncertainty in online calibration assessment; accurate determination of calibration acceptance criteria and quantification of the effect of acceptance criteria variability on system performance; and assessment of the feasibility of using virtual sensor estimates to replace identified faulty sensors in order to extend operation to the next convenient maintenance opportunity. Understanding the degradation of sensors and the impact of this degradation on signals is key to developing technical basis to support acceptance criteria and set point decisions, particularly for advanced sensors which do not yet have a cumulative history of operating performance