Structural reliability-based optimisation of inspection intervals for large-diameter water pipelines

Ageing large-diameter water pipelines require inspection strategies that ensure structural reliability while minimising maintenance burden and lifecycle costs. This study develops a structural reliability-based framework to optimise inspection intervals for pipeline structures under corrosion-induced deterioration. An artificial neural network–based corrosion prediction model was applied to estimate age-dependent wall loss and the associated failure probabilities of individual pipeline segments, enabling the representation of nonlinear deterioration behaviour. Monte Carlo simulation was then used to evaluate lifecycle costs under varying inspection thresholds, explicitly incorporating diagnostic inspection, preventive or reactive maintenance, and failure consequences such as service disruption and ground settlement. The optimal inspection threshold was defined as the failure probability that minimised the expected total cost within a state-dependent decision framework, allowing inspection timing to adapt dynamically to segment-specific deterioration conditions. Application to a regional pipeline network demonstrated that approximately 34% of the network required inspection within 10 years, whereas approximately 37% exhibited sufficient structural robustness to extend intervals beyond 30 years. In contrast, 12 segments exceeded accepted safety thresholds, necessitating immediate reassessment or rehabilitation. The proposed approach provides a quantitative basis for segment-specific, condition-based inspection planning and supports risk-informed management to enhance safety and cost efficiency of buried infrastructure.