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Reliability analysis and service life prediction of pipelines

Reliability analysis and service life prediction of pipelines

Mahmoodian, Mojtaba (2013) Reliability analysis and service life prediction of pipelines. PhD thesis, University of Greenwich.

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Abstract

Pipelines are extensively used engineering structures for conveying of fluid from one place to another. Most of the time, pipelines are placed underground, surcharged by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on two different types of buried pipes including concrete pipes in sewage systems (concrete sewers) and cast iron water pipes used in water distribution systems. This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of these two types of pipes. Then two probabilistic time dependent reliability analysis methods including first passage probability theory and the gamma distributed degradation model are developed and applied for service life prediction of the pipes. The obtained results are verified by using Monte Carlo simulation technique. Sensitivity analysis is also performed to identify the most important parameters that affect pipe failure.

For each type of the pipelines both individual failure mode and multi failure mode assessment are considered. The factors that affect and control the process of deterioration and their effects on the remaining service life are studied in a quantitative manner. The reliability analysis methods which have been developed in this research, contribute as rational tools for decision makers with regard to strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the pipeline system.

The output of this research is a methodology that will help infrastructure managers and design professionals to predict service life of pipeline systems and to optimize materials selection and design parameters for designing pipelines with longer service life.

Item Type: Thesis (PhD)
Additional Information: uk.bl.ethos.601728
Uncontrolled Keywords: pipeline systems, probability theory,
Subjects: T Technology > TJ Mechanical engineering and machinery
Pre-2014 Departments: School of Engineering
School of Engineering > Department of Civil Engineering
Last Modified: 14 Oct 2016 09:27
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/11374

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