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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

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