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AuthorElmasry,Mohamed
AuthorZayed, Tarek
AuthorHawari, Alaa
Available date2021-09-05T05:40:16Z
Publication Date2016
Publication NamePipelines 2016: Out of Sight, Out of Mind, Not Out of Risk - Proceedings of the Pipelines 2016 Conference
ResourceScopus
URIhttp://dx.doi.org/10.1061/9780784479957.056
URIhttp://hdl.handle.net/10576/22704
AbstractIn order to successfully implement an asset management program, an accurate and reliable deterioration model for assets should be available. Deterioration models are considered as the basis for predicting and prioritizing future maintenance, rehabilitation, or replacement activities of assets. Sewer agencies are seeking different methods to prioritize inspection of sewer pipes in presence of financial constraints and deteriorating pipelines. This paper presents the development of a defect based deterioration model using Bayesian belief network (BBN) in sewer pipelines to be used in inspection prioritization. Different types of defects found in an existing sewage network were collected from closed circuit television (CCTV) inspection reports and used in creating the model to determine the likelihood of a sewage pipeline to be in a certain condition state. The BBN is used to generate dependency between different defects and their effect on the overall condition of the pipe. Monte-Carlo simulation (MCS) was introduced to eliminate the uncertainties that could arise in the model due to independent events that would be propagated through the BBN to assess the final dependent posterior probabilities. BBN is considered as an efficient tool because it deals with inherent uncertainties and handles complex interdependencies using conditional probabilities. The developed model could be used as a decision support tool by which decision makers could plan inspection of deteriorated sections. 2016 ASCE.
Languageen
PublisherAmerican Society of Civil Engineers (ASCE)
SubjectComplex networks
Decision making
Decision support systems
Defects
Deterioration
Inspection
Intelligent systems
Monte Carlo methods
Pipelines
Sewage
Sewers
Television networks
Uncertainty analysis
Bayesian belief network models
Closed circuit television
Conditional probabilities
Decision support tools
Deterioration modeling
Deterioration models
Financial constraints
Posterior probability
Bayesian networks
TitleSewer Inspection Prioritization Using a Defect-Based Bayesian Belief Network Model
TypeConference Paper
Pagination613-625
dc.accessType Abstract Only


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