Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/97536
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building and Real Estate | en_US |
| dc.creator | Zakikhani, K | en_US |
| dc.creator | Nasiri, F | en_US |
| dc.creator | Zayed, T | en_US |
| dc.date.accessioned | 2023-03-06T01:19:56Z | - |
| dc.date.available | 2023-03-06T01:19:56Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/97536 | - |
| dc.language.iso | en | en_US |
| dc.publisher | SAGE Publications | en_US |
| dc.rights | This is the accepted version of the publication Zakikhani K, Nasiri F, Zayed T., A failure prediction model for corrosion in gas transmission pipelines, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability (2021;235(3)) pp. 374-390. Copyright © 2020 IMechE. DOI: 10.1177/1748006X20976802. | en_US |
| dc.subject | External corrosion | en_US |
| dc.subject | Gas transmission | en_US |
| dc.subject | Multiple regression | en_US |
| dc.subject | Petroleum | en_US |
| dc.subject | Pipelines | en_US |
| dc.subject | Time of failure | en_US |
| dc.title | A failure prediction model for corrosion in gas transmission pipelines | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 374 | en_US |
| dc.identifier.epage | 390 | en_US |
| dc.identifier.volume | 235 | en_US |
| dc.identifier.issue | 3 | en_US |
| dc.identifier.doi | 10.1177/1748006X20976802 | en_US |
| dcterms.abstract | Transmission pipelines comprise a major part of a gas network, conveying natural gas within jurisdictions, and across international boundaries. In the United States, more than 10,000 failure incidents have been reported in gas transmission pipelines in a 20-year period from 1996 to 2016 leading to a cumulative property damage of more than $748 million. Among different failure sources, corrosion is ranked as the most frequent one, corresponding to approximately a quarter of total failures. Though in-line inspection is counted as the most frequently applied corrosion monitoring technique for oil and gas pipelines, it imposes considerable costs due to the necessity of implementing frequent inspections using smart devices. For this reason, several failure prediction models have been developed to estimate the corrosion failure. However, the majorities of these prediction models rely solely on experimental tests or limited historical records which undermine the extent of their applicability and ignore pipeline environmental and geographical circumstances. The objective of this research is to develop failure prediction models for external corrosion in underground gas transmission pipelines by considering both conventional and environmental/geographical variables. For this objective, multiple regression analysis was performed on the accessible historical data reported for gas transmission pipelines. Two main climate regions of Great Plains and South East in the US were selected, and their corresponding failure prediction models were developed. Such development was based on a step by step procedure analyzing different scenarios. Considering diagnostic measures, null hypothesis and residual analysis, scenario 3 was selected as satisfactory. The validation tests of the developed models present a root mean square error (RMSE) of 0.04 and 0.07 and R-Sq of 0.93 and 0.75, respectively. The results of this research can be applied in maintenance planning of gas transmission pipeline to estimate the critical time in which a pipeline may encounter external corrosion failure, and to accordingly schedule the maintenance activities. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Proceedings of the Institution of Mechanical Engineers. Part O: Journal of risk and reliability, 1 June 2021, v. 235, no. 3, p. 374-390 | en_US |
| dcterms.isPartOf | Proceedings of the Institution of Mechanical Engineers. Part O: Journal of risk and reliability | en_US |
| dcterms.issued | 2021-06-01 | - |
| dc.identifier.scopus | 2-s2.0-85097258491 | - |
| dc.description.validate | 202303 bcww | - |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | BRE-0076 | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 54514404 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Zayed_Failure_Prediction_Model.pdf | Pre-Published version | 1.43 MB | Adobe PDF | View/Open |
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