Optimal Inspection Planning for Corroded Pipelines Considering Repair Decision Error

Abstract

The optimal inspection planning of pipelines is mandatory for safe and economical operation under degradation processes, particularly corrosion induced by soil and environmental aggressiveness. In addition to the random nature of corrosion, the applied inspection tools and procedures provide significant uncertainties related to detecting corrosion defects and measuring the observed defect size. This work aims to consider the imperfect inspection results in terms of defect detection and sizing for optimal planning of pipeline maintenance. The pipeline degradation considers the spatial variability of corrosion in different exposure zones and its autocorrelation using the Karhunen–Loève expansion. Monte Carlo simulations compute the time-variant failure probability of a system formed by components in series. Then, the maintenance model is developed based on the inspection decision tree, where imperfect inspections and repair decision errors are considered. The developed model is applied to a gas pipeline under space-variant corrosion to show the effects of the main system parameters. The results show that defect detection and size measurements play a fundamental role in the optimal maintenance strategy, where improving inspection quality decreases the optimal inspection interval. In contrast, a higher inspection cost increases the optimal interval. Moreover, ignoring the impact of spatial variability and unacceptable error results in significant errors in the expected total cost and optimal inspection interval.