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Risk-Cost Optimization and Reliability Analysis of Underground Pipelines

Risk-Cost Optimization and Reliability Analysis of Underground Pipelines

Tee, Kong Fah ORCID: 0000-0003-3202-873X and Khan, Lutfor Rahman (2012) Risk-Cost Optimization and Reliability Analysis of Underground Pipelines. In: 6th International ASRANet Conference for Integrating Structural Analysis, Risk and Reliablity, 2-4 July 2012, London. (Unpublished)

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The safety of infrastructure facilities such as buried pipelines is the primary objective of engineering design. Due to their low visibility, condition assessment and rehabilitation of underground pipelines are frequently neglected until a catastrophic failure occurs. Time, reliability and cost are the crucial aspects of any underground pipeline projects. Providing an acceptable level of service and overcoming these critical difficulties, the concerned industry has to plan how to operate, maintain and renew (repair or replace) the system under the budget constraints. This paper is concerned with estimating the reliability and deciding when interventions are needed to prevent unexpected failures of underground pipelines subject to externally applied loading and pipe material corrosion during their whole service life at the minimal cost. The probability of system failure with respect to time due to corrosion induced deflection, buckling, wall stress/thrust and bending stress-strain has been estimated and then the study has been extended to minimize the risk and life cycle cost using genetic algorithm. The proposed risk-cost optimization approach can help the management in making correct decisions concerning the intervention year and renewal methodology. An example is presented to validate the proposed method with a view to prevent the unexpected failure of flexible sewer pipes by prioritizing maintenance based on failure severity and system reliability.

Item Type: Conference or Conference Paper (Paper)
Uncontrolled Keywords: risk-cost optimization; reliability analysis; underground pipelines; genetic algorithm
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Pre-2014 Departments: School of Engineering > Department of Civil Engineering
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Last Modified: 14 Oct 2016 09:24

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