Combining discrete-time Markov processes and probabilistic fracture mechanics in RI-ISI risk estimates

Based on the research conducted in the Finnish SAFIR project, which is a national nuclear energy research program, discrete-time Markov processes and probabilistic fracture mechanics (PFM) methods are further developed and applied in this paper. The purpose of this work is to increase the accuracy of risk estimates used in RI-ISI, and to quantitatively evaluate the effects of different inspection strategies on risk. Piping failure probabilities are obtained by using PFM analyses. PFM has the advantage that its results are not affected by existing in-service inspection (ISI) activities at the nuclear power plants (NPPs), unlike failure probabilities assessed from existing failure data. The PFM results for crack growth are used to construct transition matrices used in a discrete-time Markov process. The application of Markov process allows the examination of effects of inspections on the failure probabilities. Finally, the developed method and results are showcased by applying them to a selected piping system in an existing Finnish NPP.