Optimising rig design for sailing yachts with Evolutionary Multi-objective Algorithm

• Autorzy: Pawłusik Mikołaj , Szłapczyński Rafał , Karczewski Artur

Identyfikatory

DOI

10.2478/pomr-2020-0064

• Języki publikacji: EN

Abstrakty

EN

The paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used for optimisation purposes. Considering the contradictory nature of real optimisation objectives, a multi-objective approach has been chosen to address this issue. Once the optimisation process is over, a Multi-criteria Decision Making method based on a w-dominance relation is applied for filtering out the most interesting solutions from the obtained Pareto set. The proposed method has been implemented, and selected results are provided and discussed.

Słowa kluczowe

EN

sailing yacht rig optimization; Bermuda sloop; Multi-Objective Evolutionary Algorithms (MOEA); Multi Criteria Decision Making (MCDM)

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2020
• Tom: nr 4
• Strony: 36--49
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Pawłusik Mikołaj

• Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Szłapczyński Rafał

• Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Karczewski Artur

• Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland

Bibliografia

• 1. C. A. Marchaj, Sailing Theory and Practice. 1964.
• 2. L. Larsson and R. Eliasson, Principles of Yacht Design. 2013.
• 3. N. L. Skene, Elements of yacht design. The Rudder Publishing Company, New York, 1904.
• 4. A. Karczewski and J. Kozak, “Variant designing in the preliminary small ship design process,” Polish Marit. Res., vol. 24, no. 2, pp. 77–82, Jun. 2017, doi: 10.1515/ pomr-2017-0052.
• 5. L. Xiao, J. C. Alves, N. A. Cruz, and J. Jouffroy, “Online speed optimization for sailing yachts using extremum seeking,” 2012, doi: 10.1109/OCEANS.2012.6404876.
• 6. S. S. Knudsen, “Sail Shape Optimization with CFD,” pp. 1–118, Aug. 2013, Accessed: Sep. 12, 2020. [Online]. Available: https://findit.dtu.dk/en/catalog/2292741078.
• 7. A. H. Day, “Sail optimisation for maximal speed,” J. Wind Eng. Ind. Aerodyn., vol. 63, no. 1–3, pp. 131–154, Oct. 1996, doi: 10.1016/S0167-6105(96)00073-6.
• 8. Sugimoto, “A method for optimizing sail design,” Sport. Eng., vol. 2, no. 1, pp. 35–48, Feb. 1999, doi: 10.1046/j.1460-2687.1999.00017.x.
• 9. A. Laveron-Simavilla, V. Lapuerta, S. Franchini, and A. Sanz, “Sail optimization for upwind sailing: application in a Tornado, the Olympic class catamaran.”
• 10. M. Biancolini, M. Sacher, and U. Cella, A CFD-based wing sail optimisation method coupled to a VPP. 2015.
• 11. S. Shankaran and T. Jones, “IMPROVING THE DESIGN OF SAILS USING CFD AND OPTIMIZATION ALGORITHMS,” Jun. 2020.
• 12. A. Zamarin, T. Matulja, and M. Hadjina, “Methodology for Optimal Mast and Standing Rigging Selection of a Racing Yacht Using AHP and FEM,” Brodogradnja, vol. 64, pp. 11–21, Mar. 2013.
• 13. J. Wallace et al., Optimal Rig Design Using Mathematical Programming. 2006.
• 14. S. Malpede and F. Nasato, “A fully integrated sail-rig analysis method,” RINA - Int. Conf. - Innov. High Perform. Sail. Yachts, Pap., pp. 203–210, Jan. 2010.
• 15. Polish Register of Shipping, “Rules for the Classification and Construction of Sea-Going Yachts, Part VII - Rig (available only in polish),” 1999. https://www.prs.pl/ uploads/jac_c7.pdf (accessed Jul. 01, 2020).
• 16. G. S. Lloyd, “Rules for Classification and Construction I Ship Technology 3 Special Craft 3 Yachts and Boats up to 24 m,” 2003. Accessed: Jul. 29, 2020. [Online]. Available: www.gl-group.com.
• 17. “Rhino 6 for Windows and Mac.” Accessed: Jun. 29, 2020. [Online]. Available: https://www.rhino3d.com/.
• 18. “Grasshopper - New in Rhino 6.” 2019, Accessed: Jun. 29, 2020. [Online]. Available: https://www.rhino3d.com/6/ new/grasshopper.
• 19. R. Vierlinger, “Multi Objective Design Interface,” vol. 2013, no. April, pp. 1–61, 2013, doi: 10.13140/RG.2.1.3401.0324.
• 20. M. T. M. Emmerich and A. H. Deutz, “A tutorial on multiobjective optimization: fundamentals and evolutionary methods,” Nat. Comput., vol. 17, no. 3, pp. 585–609, Sep. 2018, doi: 10.1007/s11047-018-9685-y.
• 21. E. Zitzler, M. Laumanns, and L. Thiele, “{SPEA2}: Improving the {S}trength {P}areto {E}volutionary {A} lgorithm,” EUROGEN 2001. Evol. Methods Des. Optim. Control with Appl. to Ind. Probl., pp. 95–100, 2002, doi: 10.1.1.28.7571.
• 22. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. 1989.
• 23. R. Vierlinger and A. Hofmann, A Framework for Flexible Search and Optimization in Parametric Design. 2013.
• 24. S. Bechikh, M. Kessentini, L. Ben Said, and K. Ghédira, “Preference Incorporation in Evolutionary Multiobjective Optimization: A Survey of the State-of-the-Art,” Adv. Comput., vol. 98, pp. 141–207, 2015, doi: 10.1016/ bs.adcom.2015.03.001.
• 25. K. Deb and H. Jain, “An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints,” IEEE Trans. Evol. Comput., vol. 18, no. 4, pp. 577–601, 2014, doi: 10.1109/TEVC.2013.2281535.
• 26. P. K. Shukla, C. Hirsch, and H. Schmeck, “A Framework for Incorporating Trade-Off Information Using MultiObjective Evolutionary Algorithms,” in Parallel Problem Solving from Nature, PPSN XI, 2010, pp. 131–140.
• 27. J. Szlapczynska and R. Szlapczynski, “Preference-based evolutionary multi-objective optimization in ship weather routing,” Appl. Soft Comput. J., vol. 84, p. 105742, 2019, doi: 10.1016/j.asoc.2019.105742.
• 28. International Yacht Brokers, “s/y DISCOVERER (Challenge 67’) yacht brochure.” 2019.
• 29. “Navtec Catalog.” https://www.oysterbayboatshop.com/ library/nav/index.html#p=4 (accessed Jun. 30, 2020).
• 30. “Continuous vs Discontinuous Standing Rigging.” https:// info.upffront.com/blog/continuous-vs-discontinuousstanding-rigging (accessed Nov. 23, 2020).
• 31. J. Kozak and W. Tarełko, “Case study of masts damage of the sail training vessel POGORIA,” Eng. Fail. Anal., vol. 18, no. 3, pp. 819–827, Apr. 2011, doi: 10.1016/j. engfailanal.2010.11.016.
• 32. “SailboatData.com - the worlds largest sailboat database.” https://sailboatdata.com/ (accessed Aug. 05, 2020).
• 33. S. Ghelardi, A. Garavaglia, C. M. Rizzo, and M. Paci, “On the rig dock tuning of large sail yachts,” Ocean Eng., vol. 183, pp. 384–397, Jul. 2019, doi: 10.1016/j.oceaneng.2019.04.080.
• 34. L. Samson and M. Kahsin, “A method to determine the tightening sequence for standing rigging of a mast,” Polish Marit. Res., vol. 26, no. 4, pp. 47–55, Dec. 2020, doi: 10.2478/ pomr-2019-0065.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).