Performance evaluation of underground pipelines subjected to landslide thrust with fiber optic strain sensing nerves

Abstract

High-accuracy deformation monitoring is crucial for investigating landslide–pipeline interaction problems, in which the fiber optic nerve system (FONS) holds enormous potential. This paper presents a theoretical framework for interpreting landslide–pipeline interactions using the FONS and proposes a novel method for calculating characteristic parameters of pipe–soil interfaces based on distributed strain measurements. The feasibility of this method is validated through a full-scale model test, and its application for studying pipeline behaviors is demonstrated in the Xinpu landslide, situated in the Three Gorges Reservoir region, China. The field monitoring results reveal that short-duration, high-intensity rainfall events triggered immediate acceleration of landslide movements, leading to pipeline elongation and flexure. Strain measurements of the underground pipeline allow for the identification of the local slipping interface of the landslide. Furthermore, the relationships between reservoir water level (RWL) fluctuations, rainfall events, landslide deformation, and the structural response of the pipe are analyzed. The findings suggest that the deformation of the landslide in the leading and middle parts exhibits high correlations with the combined effect of rainfall and RWL drawdown.