The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm
The most commonly used subsea pipeline installation method is the S-Lay method. A very important and complex task in an S-Lay installation engineering analysis is to find the optimal pipelay vessel installation configuration for every distinctive pipeline route section. Installation loads in the pip...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/1/156 |
| _version_ | 1797343251490930688 |
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| author | Damir Karabaić Marko Kršulja Sven Maričić Lovro Liverić |
| author_facet | Damir Karabaić Marko Kršulja Sven Maričić Lovro Liverić |
| author_sort | Damir Karabaić |
| collection | DOAJ |
| description | The most commonly used subsea pipeline installation method is the S-Lay method. A very important and complex task in an S-Lay installation engineering analysis is to find the optimal pipelay vessel installation configuration for every distinctive pipeline route section. Installation loads in the pipeline are very sensitive to small changes in the configuration of the pipeline supports during laying and other influential parameters, such as the tensioner force, stinger angle, trim and draft of the pipelay vessel. Therefore, the process of an engineering installation analysis is very demanding, and there is a need for an automated optimization process. For that purpose, installation engineering methodology criteria and requirements are formalized into a nonlinear optimization problem with mixed continuous and discrete variables. A special tailored multi-objective genetic algorithm is developed that can be adjusted to any desired combination of criteria and offshore standards’ requirements. The optimization algorithm is applied to the representative test cases. The optimization procedure efficiency and quality of the achieved solution prove that the developed genetic algorithm operators and the whole optimization approach are adequate for the presented application. |
| first_indexed | 2024-03-08T10:45:04Z |
| format | Article |
| id | doaj.art-2722a45253da48f29ef35bf0299d6812 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-08T10:45:04Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-2722a45253da48f29ef35bf0299d68122024-01-26T17:17:22ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-01-0112115610.3390/jmse12010156The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic AlgorithmDamir Karabaić0Marko Kršulja1Sven Maričić2Lovro Liverić3Faculty of Engineering, Juraj Dobrila University of Pula, 52100 Pula, CroatiaFaculty of Engineering, Juraj Dobrila University of Pula, 52100 Pula, CroatiaFaculty of Engineering, Juraj Dobrila University of Pula, 52100 Pula, CroatiaFaculty of Engineering, University of Rijeka, 51000 Rijeka, CroatiaThe most commonly used subsea pipeline installation method is the S-Lay method. A very important and complex task in an S-Lay installation engineering analysis is to find the optimal pipelay vessel installation configuration for every distinctive pipeline route section. Installation loads in the pipeline are very sensitive to small changes in the configuration of the pipeline supports during laying and other influential parameters, such as the tensioner force, stinger angle, trim and draft of the pipelay vessel. Therefore, the process of an engineering installation analysis is very demanding, and there is a need for an automated optimization process. For that purpose, installation engineering methodology criteria and requirements are formalized into a nonlinear optimization problem with mixed continuous and discrete variables. A special tailored multi-objective genetic algorithm is developed that can be adjusted to any desired combination of criteria and offshore standards’ requirements. The optimization algorithm is applied to the representative test cases. The optimization procedure efficiency and quality of the achieved solution prove that the developed genetic algorithm operators and the whole optimization approach are adequate for the presented application.https://www.mdpi.com/2077-1312/12/1/156subsea pipelinepipelaying vesselpipelay analysisoptimizationgenetic algorithm |
| spellingShingle | Damir Karabaić Marko Kršulja Sven Maričić Lovro Liverić The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm Journal of Marine Science and Engineering subsea pipeline pipelaying vessel pipelay analysis optimization genetic algorithm |
| title | The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm |
| title_full | The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm |
| title_fullStr | The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm |
| title_full_unstemmed | The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm |
| title_short | The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm |
| title_sort | optimization of a subsea pipeline installation configuration using a genetic algorithm |
| topic | subsea pipeline pipelaying vessel pipelay analysis optimization genetic algorithm |
| url | https://www.mdpi.com/2077-1312/12/1/156 |
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