Fragility analysis of continuous pipelines subjected to transverse permanent ground deformation

The structural integrity of buried continuous pipelines can be jeopardized by transverse permanent ground deformation (PGD) induced by landslides. A probabilistic analysis can facilitate understanding the likelihood of damage to pipelines in landslide regions, further minimizing the risk. However, empirical fragility curves for the landslide-pipeline interaction problem are not available due to the lack of field data. The problem can be addressed by numerical approaches. In this study, a simplified two-dimensional numerical model is developed. It characterizes the pipes as beam-type structures and the surrounding soil as Winkler springs. It is compared here against three-dimensional continuum-based analyses, which could save extensively on computational efforts. All input parameters were sampled randomly and paired with the displacement demands to form a limited set of statistically significant, yet nominally identical, pipeline samples, and the demand models for the maximum tensile strain were evaluated. A supervised machine learning technique, called Lasso regression, was then used to establish a predictive relation between the input and the output using the limited dataset, based on which a large dataset (one million) was calculated for the fragility analysis. The use of a Winkler-based analysis and the supervised machine learning technique makes it possible to generate fragility curves for pipelines subjected to transverse PGD for the first time.

Перевод пока недоступен