Abstract
RBI, referring to a risk-based approach to inspection planning, is an established pipeline integrity management method. Both corrosion and dents are the primary threats to pipeline integrity. However, they are often treated separately in RBI without considering their interactions. This coupling may lead to a synergic effect on integrity degradation. The present study proposes an RBI planning framework for pipelines considering external corrosion and dents. Time-dependent pipeline deterioration by dents and corrosion is modeled probabilistically using a Dynamic Bayesian Network (DBN), in-line inspection (ILI) data, and corrosion propagation knowledge. Two failure scenarios (leakage and burst) are considered. The hybrid method, integrating Monte Carlo Simulation (MCS) and Latin Hypercube Sampling (LHS) technique, estimates the pipeline's Probability of Failure (PoF) over time. The pipeline failure risk is quantified by monetizing the Consequence of Failure (CoF). An optimization model of loss-maintenance total expected cost is introduced to determine the optimum inspection period using maximum acceptable risk (MAR) and the lowest total expected cost. A cost-benefit analysis (CBA) is finally implemented to choose appropriate risk reduction measures. The proposed framework is robust and well-validated by a case study on an in-service pipeline.
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