Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network
Abstract Subsea pipeline system faces significant challenges in practical engineering applications, including system complexity, environmental variability, and limited historical data. These factors complicate the accurate estimation of component failure rates, leading to fault polymorphism and inhe...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92588-3 |
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| author | Chao Liu Chuankun Zhou Hongyan Wang Shenyu Liu Junguo Cui Wenbo Zhao Shichao Liu Liping Tan Wensheng Xiao Yaqi Chen |
| author_facet | Chao Liu Chuankun Zhou Hongyan Wang Shenyu Liu Junguo Cui Wenbo Zhao Shichao Liu Liping Tan Wensheng Xiao Yaqi Chen |
| author_sort | Chao Liu |
| collection | DOAJ |
| description | Abstract Subsea pipeline system faces significant challenges in practical engineering applications, including system complexity, environmental variability, and limited historical data. These factors complicate the accurate estimation of component failure rates, leading to fault polymorphism and inherent uncertainty. To address these challenges, this study proposes a reliability analysis method based on a Fuzzy Polymorphic Bayesian Network (FPBN). The approach utilizes a multi-state fault tree to construct a polymorphic Bayesian Network (BN), integrating traditional BN techniques with the consideration of multiple failure states and fuzzy failure rates. This extension allows the network to handle uncertainties such as imprecise fault data and unclear logical relationships. The method is applied to subsea pipeline risk analysis by developing a system BN model. Through quantitative analysis, the failure probability of the system is calculated. Reverse fault diagnosis is then conducted to determine the posterior probabilities of root nodes and identify system vulnerabilities. The results demonstrate that the FPBN effectively addresses the ambiguity and uncertainty in component failure rates, providing a robust framework with practical engineering applications. |
| format | Article |
| id | doaj-art-10dc63cedc374da7aba783cc702e5435 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-10dc63cedc374da7aba783cc702e54352025-08-20T02:08:08ZengNature PortfolioScientific Reports2045-23222025-04-0115111510.1038/s41598-025-92588-3Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian networkChao Liu0Chuankun Zhou1Hongyan Wang2Shenyu Liu3Junguo Cui4Wenbo Zhao5Shichao Liu6Liping Tan7Wensheng Xiao8Yaqi Chen9College of Electromechanical Engineering, Qingdao University of Science & TechnologyNational Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, China University of Petroleum (East China)College of Electromechanical Engineering, Qingdao University of Science & TechnologyCollege of Electromechanical Engineering, Qingdao University of Science & TechnologyNational Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, China University of Petroleum (East China)College of Electromechanical Engineering, Qingdao University of Science & TechnologyCollege of Electromechanical Engineering, Qingdao University of Science & TechnologyUlsan ship and ocean college ludong universityNational Engineering Research Center of Marine Geophysical Prospecting and Exploration and Development Equipment, China University of Petroleum (East China)Weichai Power Co., LtdAbstract Subsea pipeline system faces significant challenges in practical engineering applications, including system complexity, environmental variability, and limited historical data. These factors complicate the accurate estimation of component failure rates, leading to fault polymorphism and inherent uncertainty. To address these challenges, this study proposes a reliability analysis method based on a Fuzzy Polymorphic Bayesian Network (FPBN). The approach utilizes a multi-state fault tree to construct a polymorphic Bayesian Network (BN), integrating traditional BN techniques with the consideration of multiple failure states and fuzzy failure rates. This extension allows the network to handle uncertainties such as imprecise fault data and unclear logical relationships. The method is applied to subsea pipeline risk analysis by developing a system BN model. Through quantitative analysis, the failure probability of the system is calculated. Reverse fault diagnosis is then conducted to determine the posterior probabilities of root nodes and identify system vulnerabilities. The results demonstrate that the FPBN effectively addresses the ambiguity and uncertainty in component failure rates, providing a robust framework with practical engineering applications.https://doi.org/10.1038/s41598-025-92588-3Subsea pipeline systemReliabilityBayesian networkFuzzy theory |
| spellingShingle | Chao Liu Chuankun Zhou Hongyan Wang Shenyu Liu Junguo Cui Wenbo Zhao Shichao Liu Liping Tan Wensheng Xiao Yaqi Chen Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network Scientific Reports Subsea pipeline system Reliability Bayesian network Fuzzy theory |
| title | Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| title_full | Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| title_fullStr | Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| title_full_unstemmed | Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| title_short | Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| title_sort | reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network |
| topic | Subsea pipeline system Reliability Bayesian network Fuzzy theory |
| url | https://doi.org/10.1038/s41598-025-92588-3 |
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