Maio 2014 vol. 1 num. 1 - 10th World Congress on Computational Mechanics

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SYNTHESIS AND OPTIMIZATION OF SUBMARINE PIPELINE ROUTES

Baioco, J. S. ; Coutinho, D. C. S. ; Albrecht, C. H. ; Lima, B. S. L. P. de ; Jacob, B. P. ; Rocha, D. M. ; Cardoso, C. O. ;

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Traditionally, the selection of a pipeline route for offshore applications has been manually performed by the engineer, by a quick inspection of the seabottom bathymetry and the available information regarding obstacles. Eventually the evaluation of a given route could be performed using analysis tools, but in any case the process is highly dependent on the expertise of the engineer. In this context, this work describes the development of a compu-tational tool for the synthesis and optimization of submarine pipeline routes, using computa-tional tools based in Evolutionary Algorithms. In such optimization procedures, each candidate route is randomly generated and is evaluat-ed, in order to determine its “fitness”, in terms of several criteria that are incorporated in an objective function. Such function takes into account all relevant aspects that should be con-sidered in the selection of a route, such as total pipeline length; geophysical and geotech-nical data obtained from the bathymetry and sonography, including the definition of obstacles and regions that should be avoided; number, length and location of free spans to be mitigated along the routes. Other aspects depend on the structural behavior of the pipe, under hydro-static and environmental loadings; some of these aspects are dealt with by following recom-mendations established in the DNV RP-F105 and RP-F109 codes, related respectively to the on-bottom stability and free spans. This work describes the implementation of the optimization tool, beginning with the assembly of the objective function and the definition of the problem constraints, and proceeding with the association of this function and constraints in the framework of the implementation of a Genetic Algorithm – GA. Case studies are presented to illustrate the use of this optimization tool. It is expected that the application of such tool may reduce the design time needed to as-sess an optimal pipeline route, while reducing computational overheads and providing more accurate results (avoiding mistakes with route interpretation), ultimately minimizing costs with respect to submarine pipeline design and installation.

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Palavras-chave: Pipeline Routes, Optimization, Evolutionary Algorithms,

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DOI: 10.5151/meceng-wccm2012-19493

Referências bibliográficas
  • [1] Vieira LT, de Lima BSLP, Evsukoff AG, Jacob BP (2003), Application of genetic algorithms to the synthesis of riser configurations. In: Proceedings of the 22th International Conference on Offshore Mechanics and Arctic Engineering, CD-ROM, paper OMAE2003-37231, Cancun, Mexico.
  • [2] de Lima BSLP, Jacob BP, Ebecken NFF. A hybrid fuzzy/genetic algorithm for the design of offshore oil production risers. Int J Numer Meth Eng 64:1459–1482, DOI: 10.1002/nme.1416, 2005.
  • [3] Pina AA, Albrecht CH, de Lima BSLP, Jacob BP. Tailoring the particle swarm optimization algorithm for the design of offshore oil production risers. Optimization and Engineering, OnlineFirst, DOI 10.1007/s11081-009-9103-5, 2010.
  • [4] Vieira IM, Albrecht CH, de Lima BSLP, Jacob BP, Rocha DM, Cardoso CO. Towards a Computational Tool for the Synthesis and Optimization of Submarine Pipeline Routes. Procs. of the Twentieth International Offshore and Polar Engineering Conference - ISOPE 2010, Beijing, China.
  • [5] Lima Jr. MHA, Baioco JS, Albrecht CH, de Lima BSLP, Jacob BP, Rocha DM, Cardoso CO, 2011. Synthesis and Optimization of Submarine Pipeline Routes Considering On-Bottom Stability Criteria. In: Proceedings of the ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2011, Rotterdam, Holand.
  • [6] Recommended Practice DNV-RP-F109, On Bottom Stability Design of Submarine Pipelines, Det Norske Veritas, 2008.
  • [7] Baioco JS, Lima Jr. MHA, Albrecht CH, de Lima BSLP, Jacob BP, Rocha DM, Cardoso CO, 2011. Offshore Pipeline Routes Evaluating Weight Ballast to Achieve On-Bottom Stability. In: Proceedings of the Iberian Latin American Congress on Computational Methods in Engineering, CILAMCE 2011, Ouro Preto, Brazil.
  • [8] Goldberg DE. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, 1989.
Como citar:

Baioco, J. S.; Coutinho, D. C. S.; Albrecht, C. H.; Lima, B. S. L. P. de; Jacob, B. P.; Rocha, D. M.; Cardoso, C. O.; "SYNTHESIS AND OPTIMIZATION OF SUBMARINE PIPELINE ROUTES", p. 3606-3624 . In: In Proceedings of the 10th World Congress on Computational Mechanics [= Blucher Mechanical Engineering Proceedings, v. 1, n. 1]. São Paulo: Blucher, 2014.
ISSN 2358-0828, DOI 10.5151/meceng-wccm2012-19493

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