Predictive modelling of internal pitting corrosion of aged non-piggable pipelines
© 2015 The Electrochemical Society. A multivariate regression analysis and time-dependent maximum pit depth growth model was developed using maximum pit depths and pipeline operational parameters, which includes temperature, CO<inf>2</inf> partial pressure, flow rate, pH,...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Electrochemical Society Inc.
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/38787 |
| _version_ | 1848755414609428480 |
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| author | Ossai, C. Boswell, B. Davies, Ian |
| author_facet | Ossai, C. Boswell, B. Davies, Ian |
| author_sort | Ossai, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2015 The Electrochemical Society. A multivariate regression analysis and time-dependent maximum pit depth growth model was developed using maximum pit depths and pipeline operational parameters, which includes temperature, CO<inf>2</inf> partial pressure, flow rate, pH, sulfate ion, chloride ion and water cut. This statistical analysis, which used ten years Ultrasonic Thickness Measurement (UTM) data from non-piggable onshore pipelines, accounted for different categories of maximum pitting rates - low, moderate, high and severe. The model was validated using field data from twelve operating pipelines and the results agreed well with the field data. |
| first_indexed | 2025-11-14T08:55:56Z |
| format | Journal Article |
| id | curtin-20.500.11937-38787 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:55:56Z |
| publishDate | 2015 |
| publisher | Electrochemical Society Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-387872017-09-13T14:19:00Z Predictive modelling of internal pitting corrosion of aged non-piggable pipelines Ossai, C. Boswell, B. Davies, Ian © 2015 The Electrochemical Society. A multivariate regression analysis and time-dependent maximum pit depth growth model was developed using maximum pit depths and pipeline operational parameters, which includes temperature, CO<inf>2</inf> partial pressure, flow rate, pH, sulfate ion, chloride ion and water cut. This statistical analysis, which used ten years Ultrasonic Thickness Measurement (UTM) data from non-piggable onshore pipelines, accounted for different categories of maximum pitting rates - low, moderate, high and severe. The model was validated using field data from twelve operating pipelines and the results agreed well with the field data. 2015 Journal Article http://hdl.handle.net/20.500.11937/38787 10.1149/2.0701506jes Electrochemical Society Inc. restricted |
| spellingShingle | Ossai, C. Boswell, B. Davies, Ian Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title | Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title_full | Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title_fullStr | Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title_full_unstemmed | Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title_short | Predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| title_sort | predictive modelling of internal pitting corrosion of aged non-piggable pipelines |
| url | http://hdl.handle.net/20.500.11937/38787 |