Fuzzy Reliability and Risk-Based Maintenance of Buried Pipelines Using Multiobjective Optimization
Publication: Journal of Infrastructure Systems
Volume 26, Issue 2
Abstract
Structural deterioration of buried pipeline due to adverse corrosion effect is among the leading causes of increasing possibility of pipe failure. As a result, maintenance intervention becomes a fundamental task for good engineering management program. However, in recent years, different probabilistic techniques have been used for the evaluation and estimation of cost-effective maintenance strategies of buried pipe based on performance indicators such as failure probability. Whereas the probabilistic approach is used to account for the variabilities associated with the structural parameters, the nonprobabilistic method has been utilized to deal with the limitations of the probabilistic approach, especially for cases in which the data for proper probability evaluation of the design parameters are not adequate. In this study, a new maintenance technique is developed to determine the optimal time for the maintenance of buried pipeline using a combination of fuzzy and subset simulation (probabilistic and nonprobabilistic) approaches for computing pipe reliability and risk, based on -level cut. The strategy aims at assessing the cost-efficiency required for the determination of the optimal time for maintenance using multiobjective optimization based on the fuzzy-subset annual reliability, risk, and total maintenance cost. The times for essential maintenance schedules are obtained based on a performance indicator (annual reliability or risk), and the optimization is performed using a genetic algorithm. The applicability is demonstrated with a numerical example, and the method provides engineering technicians with the needed tools for the determination of the optimal time interval required to carry out maintenance of the buried pipelines.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request, including the data for the numerical example.
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Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 26 • Issue 2 • June 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Feb 24, 2018
Accepted: Nov 4, 2019
Published online: Mar 3, 2020
Published in print: Jun 1, 2020
Discussion open until: Aug 3, 2020
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