Burst pressure strength of corroded subsea pipelines repaired with composite fiber-reinforced polymer patches
Article
Muda, Mohd Fakri, Hashim, Mohd Hisbany Mohd, Kamarudin, Mohd Khairul, Mohd, Mohd Hairil, Tafsirojjaman, T., Rahman, Marzuki Abdul and Paik, Jeom Kee. 2022. "Burst pressure strength of corroded subsea pipelines repaired with composite fiber-reinforced polymer patches." Engineering Failure Analysis. 136, pp. 1-11. https://doi.org/10.1016/j.engfailanal.2022.106204
| Article Title | Burst pressure strength of corroded subsea pipelines repaired with composite fiber-reinforced polymer patches |
|---|---|
| ERA Journal ID | 3667 |
| Article Category | Article |
| Authors | Muda, Mohd Fakri, Hashim, Mohd Hisbany Mohd, Kamarudin, Mohd Khairul, Mohd, Mohd Hairil, Tafsirojjaman, T., Rahman, Marzuki Abdul and Paik, Jeom Kee |
| Journal Title | Engineering Failure Analysis |
| Journal Citation | 136, pp. 1-11 |
| Article Number | 106204 |
| Number of Pages | 11 |
| Year | 2022 |
| Publisher | Elsevier |
| Place of Publication | United Kingdom |
| ISSN | 1350-6307 |
| 1873-1961 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.engfailanal.2022.106204 |
| Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1350630722001789 |
| Abstract | To repair corroded subsea pipelines, composite fiber-reinforced polymer (CFRP) patches are often attached to the defected area. The aim of this paper is to present a method to assure if the strength of repaired subsea pipelines is sufficient enough to sustain burst pressure loads. A computational model for predicting the burst pressure strength of repaired pipelines with CFRP patches is presented. An algorithm of artificial neural networks (ANN) is applied. The geometry of corrosion damage is defined by three physical parameters, namely length, width and depth. The computational model is validated by comparison with refined finite element method solutions. The proposed method will be useful for developing a quick procedure for the CFRP based repair scheme of corroded subsea pipelines. |
| Keywords | Artificial Neural Networks (ANN); Burst pressure strength; Composite Fiber-Reinforced Polymer (CFRP) patches; Corroded subsea pipelines; Repair scheme |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Funder | Ministry of Higher Education, Malaysia |
| Byline Affiliations | University of Technology Malaysia, Malaysia |
| University of Malaysia, Terengganu, Malaysia | |
| Centre for Future Materials (Operations) | |
| Pusan National University, Korea | |
| Library Services |
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