The structural integrity of buried pipelines is threatened by the effects of Permanent Ground Deformation (PGD), resulting from seismic-induced landslides and lateral spreading due to liquefaction, requiring accurate analysis of the system performance. Analytical fragility functions allow us to estimate the likelihood of seismic damage along the pipeline, supporting design engineers and network operators in prioritizing resource allocation for mitigative or remedial measures in spatially distributed lifeline systems. To efficiently and accurately evaluate the seismic fragility of a buried operating steel pipeline under longitudinal PGD, this study develops a new analytical model, accounting for the asymmetric pipeline behavior in tension and compression under varying operational loads. This validated model is further implemented within a fragility function calculation framework based on the Monte Carlo Simulation (MCS), allowing us to efficiently assess the probability of the pipeline exceeding the performance limit states, conditioned to the PGD demand. The evaluated fragility surfaces showed that the probability of the pipeline exceeding the performance criteria increases for larger soil displacements and lengths, as well as cover depths, because of the greater mobilized soil reaction counteracting the pipeline deformation. The performed Global Sensitivity Analysis (GSA) highlighted the influence of the PGD and soil-pipeline interaction parameters, as well as the effect of the service loads on structural performance, requiring proper consideration in pipeline system modeling and design. Overall, the proposed analytical fragility function calculation framework provides a useful methodology for effectively assessing the performance of operating pipelines under longitudinal PGD, quantifying the effect of the uncertain parameters impacting system response.

This study assesses the performance of a memory surface constitutive model (SANISAND-MS) in capturing vertical cyclic loading on a suction bucket foundation in sand. The model has been calibrated against drained cyclic triaxial responses and validated against corresponding centrifuge experiments on suction buckets. The model was found to satisfactorily capture the effects of increasing accumulated strain with increasing mean stress level and reducing density. The performance of the model was further investigated through a parametric study on suction buckets at different mean stress levels, densities and loading sequences. The insights gained from investigating the strain and stress responses, along with the movement of the memory surface, reveal that the model can satisfactorily capture the strain accumulation and ratcheting effects under different load histories.