Risk-Based Assessment of Hard Spot Defects in Pipelines Using Probabilistic Fracture Mechanics and In-Line Inspection Data

Pipeline operators are increasingly applying In-Line Inspection (ILI) tools to detect and address manufacturing defects known as hard spots. Hard spots are areas of localized high hardness in steel that are associated with an increased likelihood of crack formation and rupture. These regions are generally brittle; therefore, if a crack forms, it may propagate rapidly. Hard spots have contributed to recent pipeline failures, such as the 30” transmission line incident in Danville, KY. [1] ILI technology is advancing rapidly and has demonstrated some capability in detecting and characterizing hard spots. However, assessing these hard spots remains challenging due to uncertainties regarding tool accuracy, crack formation probabilities, and potential outcomes post crack initiation. This paper proposes a methodology that utilizes probabilistic fracture mechanics (PFM) to develop a risk-based approach for determining the probability of hard spot failure (leakage or rupture), including the likelihood of crack initiation within the hard spot. The model incorporates statistical distributions of key parameters used in deterministic Fitness-for-Service (FFS) evaluations, applying a Monte Carlo analysis algorithm to sample randomly from each distribution and perform millions of simulations. This process estimates the probability of leakage, rupture, or subcritical conditions in the hard spot. The method is then applied to a set of ILI features to establish the risk associated with each feature and the line segment from which the ILI was run.