Chapter 9 ON ESTIMATING PIPELINES RELIABILITY AT SLOPE CROSSINGS
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Published:2020
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ABSTRACT
Transmission pipelines often traverse land slopes along the right-of-way; whereby some of these slopes might have a potential for instability related movements. In order to analyze the risk of failure of pipelines due to slope movement it is beneficial to establish probabilistic approaches that can quantify the likelihood of failure at each site given both aleatory and epistemic uncertainties. Estimation of such likelihood would support comparison of a pipelines’ safety to reliability targets, validate whether slope management programs are acceptable, and support selection of mitigation alternatives. There is currently a gap in pipeline integrity literature in terms of available probabilistic approaches to analyze, assess, and manage pipelines crossing potentially moving slopes.
Three probabilistic approaches are presented herein: (1) A qualitative ranking analysis of slope hazards (QuRASH) which adopts site scores based on readily available slope crossing characteristics; (2) A semi-quantitative analysis of slope hazards (SQuASH) which is a reliability-based explicit limit state approach; and (3) A fully quantitative analysis of slope hazards (QuASH), which utilizes finite element modelling to establish a probabilistic strain demand for evaluating the pipeline’s probability of failure through implicit limit state functions. The resulting slope threat prioritizations from these probabilistic approaches compared favorably with those slopes evaluated by experts to exhibit elevated threats.
The reliability approaches were applied to support decision making at a pipeline slope crossing that required mitigation. Various remediation/integrity mitigation designs were proposed by the project team, each with varying benefits. Determination of the probability of failure associated with each mitigation option/design enabled quantification of associated risks. Such information was considered by the decision makers for selection of the most favorable mitigation option.