Enabling real-time decisions on stress-relief for risk-significant equipment susceptible to degradation and damage, thereby supporting optimized lifetime management. As described in previous reports in this series, probabilistic risk assessment (PRA) provides a static representation of risk associated with operation and maintenance (O&M) of nuclear power plants. Technologies for characterizing real-time risk (so called Enhanced Risk Monitors or ERMs) take into account plant-specific normal, abnormal, and deteriorating states of systems, structures, and components (SSCs) in the estimation of current and future risk to safe and economic operation. Additionally, technologies for characterizing real-time risk provide a mechanism for compensating for the relatively small amount of long-term reliability data from AR systems, structures, and components. The ability to monitor performance and characterize changes in operational risk in real-time can reduce the level of dependence on such performance data. Proactively establishing a viable ERM methodology before AR component design specifications are established also supports: (i) building in opportunities for automated monitoring (on-line and off-line) of those components for optimizing performance with respect to anticipated demands on these reactors; and (ii) improving the maintainability of components from the perspective of time-to-repair and component cost. This research report summaries the development and evaluation of a prototypic ERM methodology (framework) that includes alternative risk metrics and uncertainty analysis. This updated ERM methodology accounts for uncertainty in the equipment condition assessment (ECA), the prognostic result, and the PRA model. It is anticipated that the ability to characterize uncertainty in the estimated risk and update the risk estimates in real-time based on ECA will provide a mechanism for optimizing plant performance while staying within specified safety margins. The report provides an overview of the methodology for integrating time-dependent failure probabilities into risk monitors. This prototypic ERM methodology was evaluated using a hypothetical PRA model, generated using a simplified design of a liquid-metal-cooled AR. Component failure data from industry compilation of failures of components similar to those in the simplified AR model were used to initialize the PRA model. By using time-dependent probability of failure (POF) that grows from the initial probability when equipment is in like-new condition to a maximum POF, which occurs before a scheduled maintenance action that restores or repairs the component to "as-new" condition, the changes in core damage frequency (CDF) over time were computed and analyzed. vii Acronyms and Abbreviations AC alternating current AdvSMR advanced small modular reactor AFI aging fractional increase AST aging start time CAFTA Computer Aided Fault Tree Analysis (system) CCF common cause failure CDF core damage frequency CREDO Centralized Reliability Data Organization (component reliabili...