This document provides a printout of the "Fuel Activity Database" (version U6) generated by the Hanford DKPRO code and transmitted to the Los Alamos National Laboratory for input to their "Hanford Defined Waste" model of waste tank inventories. This fuel activity file consists of 1,276 records--each record representing the activity associated with a batch of spent reactor fuel processed by month (or shorter period) through individual Hanford separations plants between 1944 and 1989. Each record gives the curies for 46 key radionuclides, decayed t o a common reference date of January 1, 1994.

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 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 ...

A key national energy priority to promote energy security is sustainable nuclear power. Nuclear energy currently contributes approximately 20% of baseload electrical needs in the United States and is considered a reliable generation source to meet future electricity needs. Advanced small modular reactors (AdvSMRs) using non-light-water reactor coolants such as liquid metal, helium, or liquid salt are promising mid-to long-term options being explored for added functionality and affordability in future reliable nuclear power deployment. AdvSMRs can offer potential advantages over more conventional technologies in the areas of safety and reliability, sustainability, affordability, functionality, and proliferation resistance. However, a number of technical challenges will need to be addressed before AdvSMRs are ready for deployment, given their potential for remote deployment with minimal staffing, longer operating cycles between planned refueling and maintenance outages, and support for multiple energy applications. In addition, AdvSMRs (like SMRs based on more conventional light-water reactor technologies) will have reduced economy-of-scale savings when compared to current generation lightwater reactors (LWRs). Issues related to AdvSMR deployment can be addressed through cross-cutting RD&D involving instrumentation, controls, and human-machine interface (ICHMI) technologies. Specifically, diagnostics and prognostics technologies provide a mechanism for improving safety and reliability of AdvSMRs through integrated health management of passive components. This report identifies activities and develops an outline of a research plan to address the high-priority technical needs for demonstrating prototypic prognostic techniques to manage degradation of passive AdvSMR components. Concepts for AdvSMRs span a wide range of design maturity, specificity, and concepts of operation, including multi-unit, multi-product-stream generating stations. Key to the development and deployment of AdvSMRs will be the ability to ensure safe and affordable operation of these reactor designs. AdvSMR designs generally place more emphasis on passive systems to assure safety. However, degradation in all passive components will need to be well-managed to maximize safety, operational lifetimes, and plant reliability while minimizing maintenance demands, if reduced economies-of-scale are to be overcome. Traditional approaches such as periodic in-service nondestructive inspections are likely to have limited applicability to AdvSMRs, given the expectation of longer operating periods and potential difficulties with inspection access to critical components. Advanced instrumentation and control (I&C) technologies can provide a mechanism for achieving these goals. However, the significant technology and environmental differences between AdvSMRs and conventional LWRs and the potential for modularized deployment result in unique challenges and needs for advanced ICHMI applications in AdvSMRs. v prognostics is also documented. This assessment, combined wi...

vii in risk is seen to reduce under certain circumstances. This appears to depend on the contribution of the component to the overall risk (i.e., the "importance" of the component). Repairs or replacements (bringing the components to as-new condition) reduce the risk, although aging of other components may still drive the overall risk higher. As well, we assume that the uncertainty associated with the component condition after repair or replacement is reduced. While this contributes to reducing the uncertainty bounds in the risk metric, uncertainty in the aging of other components may still drive the overall uncertainty higher as well. These pieces of information, when compared to traditional PRA analysis, appear to provide useful information for scheduling maintenance activities based on actual degradation condition and consequent failure probabilities. Specifically, if thresholds may be set on the risk metric of interest, the projected risk and uncertainty bounds provide a mechanism for scheduling maintenance activities whenever the risk (plus uncertainty) exceeds the threshold. Key to accurate uncertainty quantification within the ERM will be the ability to accurately identify failure probabilities of typical components used in AdvSMRs. Such reliability data is not readily available, and for AdvSMR concepts, may comprise data from instrumented test reactors that were operated between the 1970s and 1990s. Available data from such test reactors is being examined for applicability to this project. The ERM can provide additional value through the development of alternative risk metrics. Metrics associated with quantities such as cost or losses due to lost generation or unanticipated plant shutdown may provide valuable insights into the tradeoffs associated with continued plant operation while maintaining adequate safety margins. To this end, alternative risk metrics associated with these quantities are being identified and will be evaluated next. Ongoing and planned research is focused on evaluating alternative risk metrics (including the options described earlier) and the impact of uncertainty on these risk metrics. In addition, we anticipate integrating the ERM methodology with simulation tools that simulate advanced reactor/AdvSMR modules and the impact of component degradation on their performance to perform comprehensive evaluations of the ERM methodology. In addition, we will explore the possibility of evaluations using experimental data, and to this end, will continue to evaluate sources of relevant reliability data, including data from test reactors, and available test-beds. xi Acronyms AC alternating current AdvSMR advanced small modular reactor CAFTA Computer Aided Fault Tree Analysis (system) CCF common cause failure CDF core damage frequency CREDO Centralized Reliability Data Organization (component reliability database

High-Temperature Gas-Cooled Reactor in-Containment Sensing and Control Systems .

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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...