Application of monitoring and prognostics to small modular reactors

Prognostics is one component of a full health monitoring system, which generally includes plant condition monitoring, fault detection, fault diagnostics, and estimation of remaining useful life. Empirical methods for prognostics have been widely studied, and the efficacy of these models is well accepted. However, these methods typically require large amounts of run-to-failure data for accurate model development. This has been one of the main roadblocks for developing prognostic models for high reliability or safety critical systems: equipment rarely malfunctions; when it does, it is often times repaired before failure occurs. This paper presents the work completed in developing and validating an accurate prognostic system for several potential IRIS system fault modes using high-fidelity simulated data before any plant operation takes place. Fault modes under investigation include heat exchanger fouling, sensor calibration drifts, and pump degradation. Prognostic models are developed which can be applied to the IRIS plant from day one of operation to facilitate the final step in a full health monitoring system. These estimates of remaining useful life can be used to inform both operations and maintenance planning to reduce plant downtime and provide the highest level of power production from the beginning of operation.