Diagnostic and prognostic tools for residual life estimation in aging nuclear power plant components

A central issue in life extension for the current fleet of light water nuclear power reactors (LWR) is the early detection and monitoring of significant materials degradation. To meet this need, nondestructive methods that are suitable for continuous monitoring over extended time periods (months to years) are needed. A related issue is the ability to estimate remaining useful life (RUL) of components and systems based on condition assessment or degradation information. Monitoring for early detection of materials degradation requires novel sensors and enhanced data integration techniques. A range of acoustic and electromagnetic measurement methods may be suitable, including acoustic microscopy, eddy current and magnetic Barkhausen emission. Prognostic methods that predict rate of degradation and remaining life based on phenomena that can be described by linear elastic fracture mechanics have been reported by several researchers. However, the challenge of predicting remaining life starting from earlier phases of degradation is largely unsolved. This paper discusses an assessment of selected diagnostic techniques, and the application of Bayesian prognostic algorithms to detection of early degradation and rate of degradation/life prediction. Such measurement and modeling methods are expected to form the basis for a new range of advanced diagnostic and prognostic approaches for assessing and monitoring life extension of ageing light water reactors.