A Bayesian Network for Slope Geohazard Management of Buried Energy Pipelines

Abstract

Geohazards are the ground movement events that impose displacement demands on buried pipelines leading to excessive inelastic strains and possible loss of containment. Lack of data, as well as large uncertainties in the prediction of ground movement and inelastic pipe response are common challenges in geohazard management. A simple Bayesian network is presented in this study to demonstrate the integration of data from multiple sources, as well as prediction of the pipeline condition under a hypothetical ground movement scenario. The methodology used to obtain the network parameters and the challenges associated with the implementation are discussed.