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Reliability based life cycle cost optimization for underground pipeline networks

Reliability based life cycle cost optimization for underground pipeline networks

Tee, Kong Fah, Khan, Lutfor Rahman, Chen, Hua-Peng and Alani, Morteza (2014) Reliability based life cycle cost optimization for underground pipeline networks. Tunnelling and Underground Space Technology incorporating Trenchless Technology Research, 43. pp. 32-40. ISSN 0886-7798 (doi:10.1016/j.tust.2014.04.007)

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Abstract

The safety of underground pipelines is the primary focus of water and wastewater industry. Due to low visibility and lack of proper information regarding the condition of underground pipes, assessment and maintenance are frequently neglected until a disastrous failure occurs. The reduction of pipe thickness due to corrosion undermines the pipe resistance capacity which in turn reduces the factor of safety of the whole distribution system. Providing an acceptable level of service and overcoming practical 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 reliability of non-pressure flexible underground pipes subjected to externally applied loading and material corrosion during the whole service life. The reliability with respect to time due to corrosion induced deflection, buckling, wall thrust, bending stress is estimated. Then the study is extended to determine intervention year for maintenance and to identify the most appropriate renewal solution by minimizing the risk of failure and whole life cycle cost using Genetic Algorithm (GA). An example is presented to validate the proposed method with a view to prevent unexpected failure of flexible pipes at the minimal cost by prioritizing maintenance based on failure severity and system reliability.

Item Type: Article
Uncontrolled Keywords: Risk and cost optimization, Probability of failure, Genetic Algorithm, Pipe renewal methods, Life cycle cost, Failure cost, Condition Index
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science > Department of Engineering Science
Last Modified: 21 Apr 2017 10:49
Selected for GREAT 2016: GREAT b
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/14513

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