Probability of detection curves for dissimilar metal welds as input to probabilistic fracture mechanics code

The U.S. Nuclear Regulatory Commission (NRC) in cooperation with the nuclear industry has developed a probabilistic fracture mechanics code called xLPR (extremely Low Probability of Rupture). xLPR is a modular-based probabilistic assessment tool for determining probability of leakage and rupture for pressure boundary piping. One of the modules in xLPR is the In-Service Inspection (ISI) module which models the probability of detection (POD) and sizing performance of NDE performed during in-service inspection to account for and predict the influence of periodic inspections on the probability of component leakage and rupture. The accuracy of the ISI module in xLPR is dependent on the quality of the estimates of detection and sizing performance that are input to the module. Multiple efforts have been attempted to quantify the detection and sizing performance of NDE in the nuclear industry. These efforts include an analysis of inspection data collected as part of the industry’s Performance Demonstration Initiative (PDI) and data collected from NRC sponsored round robin studies such as PINC-Program for the Inspection of Nickel Alloy Components and PARENT-Program to Assess the Reliability of Emerging Nondestructive Techniques. Usage of a given data set in the xLPR ISI module requires understanding of which set of data is most representative for the specific scenario under consideration. A comparative analysis of detection performance data from PDI, PINC, and PARENT is provided in this paper in an effort to elucidate for users of xLPR types of applications the above mentioned data sets may be most appropriate for.