Abstract

The US operating fleet of light water reactors (LWRs) is currently undergoing life extensions from the original 40- year license to 60 years of operation. In the US, 74 reactors have been approved for the first round license extension, and 19 additional applications are currently under review. Safe and economic operation of these plants beyond 60 years is now being considered in anticipation of a second round of license extensions to 80 years of operation. Greater situational awareness of key systems, structures, and components (SSCs) can provide the technical basis for extending the life of SSCs beyond the original design life and supports improvements in both safety and economics by supporting optimized maintenance planning and power uprates. These issues are not specific to the aging LWRs; future reactors (including Generation III+ LWRs, advanced reactors, small modular reactors, and fast reactors) can benefit from the same situational awareness. In fact, many small modular reactor (SMR) and advanced reactor designs have increased operating cycles (typically four years up to forty years), which reduce the opportunities for inspection and maintenance at frequent, scheduled outages. Understanding of the current condition of key equipment and the expected evolution of degradation during the next operating cycle allows for targeted inspection and maintenance activities. This article reviews the state of the art and the state of practice of prognostics and health management (PHM) for nuclear power systems. Key research needs and technical gaps are highlighted that must be addressed in order to fully realize the benefits of PHM in nuclear facilities.

Highlights

  • Recent years have seen major shocks to the nuclear power community, including those due to events at Fukushima and subsequent plant closures, such as those in Germany, and changes in economics in the USA due to the widespread availability of cheap natural gas following the introduction of hydraulic fracturing, which is causing some nuclear power plant closures

  • No formalized cost-benefit analysis for applying prognostics and health management (PHM) in a specific nuclear power plants (NPPs) has been found; analyses suggest that fleet-wide savings of over $1 billion per year are possible in the United States alone when PHM is applied to all key equipment in legacy power plants (Bond, Ramuhalli, Tawfik, & Lybeck, 2011)

  • For many of these components, the state of practice does not include prognostics, which has largely remained the purview of research in the nuclear power industry (IAEA, 2013)

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Summary

INTRODUCTION

Recent years have seen major shocks to the nuclear power community, including those due to events at Fukushima and subsequent plant closures, such as those in Germany, and changes in economics in the USA due to the widespread availability of cheap natural gas following the introduction of hydraulic fracturing, which is causing some nuclear power plant closures. Three separate thrusts to safe and economic nuclear power development for energy security are being pursued in the United States: (i) longer term operation for the legacy fleet, considering operating lives of 60–80 years; (ii) near-term new nuclear plants with a 60-year design life; and (iii) small modular reactors, which are expected to employ light water reactor technology at least in the medium term (e.g., integral pressurized water reactors – iPWRs). Within these activities, attention is turning to enhanced methods for plant component and structural health management.

THE CURRENT AND FUTURE NUCLEAR POWER FLEET
MODELING AND ANALYSIS FOR PHM
Monitoring and Anomaly Detection
Diagnostics
Prognostics
PHM APPLICATIONS AND TECHNOLOGIES IN NPPS
Monitoring and Prognostics for Active Components
Sensors
Motors
Valves
Control Rod and Element Drive Mechanisms
Monitoring and Prognostics for Passive Components
Heat Exchangers
Transformers
Cables
Passive Structures
RESEARCH NEEDS AND TECHNICAL GAPS
Sensors and Sensor Placement
Data and Models
Uncertainty Quantification
Online Performance Assessment
Verification and Validation
SUMMARY
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