Use of Markov Piping Reliability Models to Evaluate Time Dependent Frequencies of Loss of Coolant Accidents

Markov model theory has been applied to develop a method to evaluate the influence of alternate strategies for in-service inspection and leak detection on the frequency of leaks and ruptures in nuclear power plant piping systems [1–4]. This approach to quantification of pipe rupture frequency was originally based on a Bayes’ uncertainty analysis approach to derive piping system failure rates from a combination of service experience data and some simple reliability models [5–7]. More recently the Markov model approach has been used in conjunction with probabilistic fracture mechanics methods in the study of flow accelerated corrosion [8]. One interesting property of the Markov model is its capability to evaluate time dependent rupture frequencies via the model hazard rate. In this paper this time dependent modeling capability is used to investigate the age related and time dependent frequencies of loss of coolant accident (LOCA) initiating event frequencies. A case is presented that plant age dependent LOCA frequencies should be used in lieu of other metrics commonly used in probabilistic risk assessments and in risk informed inservice inspection evaluations. Such more commonly used metrics include the assumed constant failure rate method and the lifetime average rupture probability. Both of these methods are shown to provide optimistic estimates of LOCA frequencies for plants in the latter part of their design lifetimes, which most operating plants are approaching.