In this work, a 3D finite element (FE) based model was developed to assess the condition of an underground hydrogen transmission pipeline containing a corrosion defect under combined internal pressure and soil movement-induced axial compression. The use of mechanical properties of X100 pipeline steel under different hydrogen charging time models the degree of hydrogen damage in pipelines. Parameter effects, i.e., axial compressive stress, hydrogen damage, defect geometries, and pipeline diameter-to-thickness ratio, were determined. The results demonstrated that the synergistic effect of axial compression, internal pressure, corrosion, and hydrogen damage can lead to a significant decrease in the failure pressure of pipelines. The failure pressure decreased with the wall thickness reduction and increased hydrogen damage, axial compressive stress, defect length, defect depth, and pipe diameter. The competitive effect was observed between the degree of metal loss and hydrogen damage in determining the burst capacity of pipelines. In situations where the pipeline integrity was severely compromised, the failure pressure exhibited minimal reduction despite the increasing severity of hydrogen damage. The stress distribution at the defect zone was influenced by axial compressive stress but remained unaffected by hydrogen damage under normal operating conditions (i.e., an internal pressure of 10 MPa). This work is expected to help operators understand the applicability of elder and in-service pipelines for hydrogen transmission.

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Corrosion poses a significant risk to the safety of energy pipelines, while landslide disasters emerge as the primary threat responsible for triggering pipeline failures across mountainous areas. To date, there is limited research focused on the safety of energy pipelines considering the synergistic effect of corrosion and landslides. The present study proposes a finite element (FE)-based model to assess the condition of corroded pipelines under landslides. The effects of corrosion dimensions (length and depth) and location are determined. A novel equation is finally developed to predict the maximum stress and determine the most disadvantageous position for corroded pipelines under various landslide displacements. The results demonstrate that (1) as the landslide progresses, the pipeline’s stress significantly increases; (2) corrosion depth has a more significant impact on the pipeline condition than the corrosion length, and it is positively correlated with the pipe’s stress; (3) the maximum stress exhibits a nonlinear relationship with the landslide-facing position and the corrosion circumferential location; and (4) when the axial position of the corrosion is more than 6.5 m away from the center of the landslide, the location of maximum stress shifts from the corrosion region to the central section of the pipeline within the landslide. This work contributes to helping pipeline owners to understand the applicability of energy pipelines subjected to the combined effects of corrosion and landslides and provides support for future risk assessment efforts in pipeline integrity management.@en

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.@en