Skip navigation

Reliability-based analysis and maintenance of buried pipes considering the effect of uncertain variables

Reliability-based analysis and maintenance of buried pipes considering the effect of uncertain variables

Ebenuwa, Andrew Utomi (2018) Reliability-based analysis and maintenance of buried pipes considering the effect of uncertain variables. PhD thesis, University of Greenwich.

[img]
Preview
PDF
Andrew Utomi Ebenuwa 2018 - secured.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (3MB) | Preview

Abstract

The failure of the buried pipeline are rare events, and when it occurs, it poses a significant threat to the environment, human lives, and nearby assets. The performance of the buried pipeline is analysed based on the pipe failure modes such as pipe ovality, buckling pressure, and total axial and circumferential stresses. Also, the input parameters for pipe and soil properties are affected by imprecision and vagueness, particularly in the process of estimating the values. In the literature, many researchers have sought for effective methods to compute the reliability of buried pipe by considering the effect of uncertain variables. However, the existing methods such as Monte Carlo simulation are limited because of their computational capability. Often, they can only account for the aleatory type of uncertainty. Furthermore, with the increasing need in the use of buried pipelines, developing a robust and effective framework becomes necessary to overcome or mitigate against the possibility of failure.

In this research, the concept of Line Sampling (LS), Important Sampling (IS) and a combination of LS and IS have been adapted for time-dependent reliability analysis of buried pipe. Similarly, a fuzzy-subset simulation framework is developed for the performance analysis of buried pipe considering aleatory (random) and epistemic (fuzzy) uncertainty. The structural response of the buried pipe was assessed and quantified based on the structural failure modes. The methods open a new pathway for a structured approach with a good computational efficiency based on complete probability and non-probability description of input parameters. The performance of buried pipe is also assessed based on fuzzy robustness measure, which is a dimensionless measure used to account for the impact of the uncertain variables. The approach gains its efficiency by scrutinising the structural robustness at every membership level with respect to various degrees of uncertainty. The principle of fuzzy set and a Hybrid GA-GAM optimisation algorithm is integrated to form a framework employed to determine a robust and acceptable design for buried pipe. The purpose of the approach is to optimise the design variable while considering the adverse effect of the uncertain fuzzy variables. The outcome based on the methods mentioned above demonstrates the importance of accounting the effects of uncertain variables.

The reliability method based on fuzzy approach has been extended to estimate the optimal time for the maintenance of the buried pipeline. The strategy aimed at assessing the cost-efficiency required for the determination of the optimal time for maintenance using multi-objective optimisation based on the fuzzy reliability, risk, and total maintenance cost. The framework suggested in this study underlines the significance of the analysis of buried pipe and provides valuable guidance for improving safety in the reliability-based design, which is demonstrated using a numerical example. The key outcome of this research shows a new insight into the analysis of buried pipe by considering the effect of aleatory and epistemic type of uncertainty.

Item Type: Thesis (PhD)
Uncontrolled Keywords: Buried pipeline, reliability-based design, fuzzy variables, numerical example,
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Last Modified: 08 May 2020 01:38
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/24776

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics