DOI QR코드

DOI QR Code

Structural optimization of stiffener layout for stiffened plate using hybrid GA

  • Putra, Gerry Liston (Dept. of Transportation and Environmental Systems, Hiroshima University) ;
  • Kitamura, Mitsuru (Dept. of Transportation and Environmental Systems, Hiroshima University) ;
  • Takezawa, Akihiro (Dept. of Transportation and Environmental Systems, Hiroshima University)
  • Received : 2019.02.04
  • Accepted : 2019.03.26
  • Published : 2019.02.18

Abstract

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO2 emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.

Acknowledgement

Supported by : JSPS KAKENHI

References

  1. Alinia, M.M., 2005. A study into optimization of stiffeners in plates subjected to shear loading. Thin-Walled Struct. 43 (5), 845-860. https://doi.org/10.1016/j.tws.2004.10.008.
  2. Beasley, David, Bull, David R., Martin, R.R., 1993. "An overview of genetic Algorithms : Part 1, fundamentals. Univ. Comput. 2 (15), 1-16. https://doi.org/10.1017/CBO9781107415324.004.
  3. Biegel, J.E., Davern, J.J., 1990. Genetic algorithms and job shop scheduling. Comput. Ind. Eng. 19 (1-4), 81-91. https://doi.org/10.1016/0360-8352(90)90082-W.
  4. Caprace, J.D., Bair, F., Rigo, P., 2010. Scantling multi-objective optimisation of a LNG carrier. Mar. Struct. 23 (3), 288-302. https://doi.org/10.1016/j.marstruc.2010.07.003.
  5. Department of Aeronautics and Astronautics of MIT, 2009. In: Design Variable Concept, vol. 6. Futuyma, Douglas, 2014. Evolution. Igarss 2014. https://doi.org/10.1007/s13398-014-0173-7.2.
  6. Goncalves, Jos Fernando, De Magalhaes Mendes, Jorge Jos, Resende, Maur cio G.C., 2005. A hybrid genetic algorithm for the job shop scheduling problem. Eur. J. Oper. Res. 167 (1), 77-95. https://doi.org/10.1016/j.ejor.2004.03.012.
  7. Jayalakshmi, G Andal, Sathiamoorthy, S., Rajaram, R., 2001. A hybrid genetic algorithmda new approach to solve traveling salesman problem. Int. J. Comput. Eng. Sci. 2 (2), 339. https://doi.org/10.1142/S1465876301000350.
  8. Kallassy, A., Marcelin, J.L., 1997. Optimization of stiffened plates by genetic search. Struct. Optim. 13 (2-3), 134-141. https://doi.org/10.1007/BF01199232.
  9. Kim, Dae Hun, Paik, Jeom Kee, 2017. Ultimate limit state-based multi-objective optimum design technology for hull structural scantlings of merchant cargo ships. Ocean Eng. 129, 318-334. https://doi.org/10.1016/j.oceaneng.2016.11.033.
  10. Kitamura, Mitsuru, Nobukawa, Hisashi, Yang, Fengxiang, 2000. Application of a genetic algorithm to the optimal structural design of a ship's engine room taking dynamic constraints into consideration. J. Mar. Sci. Technol. 5 (3) https://doi.org/10.1007/s007730070010.
  11. Kitamura, Mitsuru, Hamada, Kunihiro, Takezawa, Akihiro, Uedera, Tetsuya, 2011. Shape optimization system of bottom structure of ship incorporating individual mesh subdivision and multi-point constraint. Int. J. Offshore Polar Eng. 21 (3), 209-215.
  12. Kitamura, Mitsuru, Uedera, Tetsuya, 2003. Optimization of ship structure based on zooming finite element analysis with sensitivities. Int. J. Offshore Polar Eng. 13 (1), 60-65.
  13. Kumar, D Nagesh, 2000. Optimization problem and model formulation. In: Optimization Methods. web.mit.edu.
  14. Maeda, Masahiro, Song, Xin, Takao, Yoshikawa, 2014. Structural optimization of the mid-ship section by applying genetic algorithm and response surface method. J. Jpn. Soc. Nav. Archit. Ocean Eng. 20, 109-117.
  15. Marcelin, J.L., 2001. Genetic optimization of stiffened plates and shells. Int. J. Numer. Methods Eng. 51 (9), 1079-1088. https://doi.org/10.1002/nme.193.
  16. Nonami, Ryota, Kitamura, Mitsuru, Takezawa, Akihiro, Hirakawa, Shinichi, 2014. A Study on Optimization the Structure of Ship in Consideration of Layout of the Stiffeners, vol. 3, pp. 876-882.
  17. Sekulski, Zbigniew, 2009. Least-weight topology and size optimization of high speed vehicle-passenger catamaran structure by genetic algorithm. Mar. Struct. 22 (4), 691-711. https://doi.org/10.1016/j.marstruc.2009.06.003.
  18. Shin, Sang-Hoon, Ko, Dae-Eun, 2017. A study on minimum weight design of vertical corrugated bulkheads for chemical tankers. International Journal of Naval Architecture and Ocean Engineering 821-826. https://doi.org/10.1016/j.ijnaoe.2017.06.005.
  19. Storer, Robert H., Wu, S David, Park, InKyoung, 1993. Genetic algorithms in problem space for sequencing problems. In: Fandel, Günter, Gulledge, Thomas, Jones, Albert (Eds.), Operations Research in Production Planning and Control. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 584-597.
  20. Um, Tae Sub, Roh, Myung Il, 2015. Optimal dimension design of a hatch cover for lightning a bulk carrier. International Journal of Naval Architecture and Ocean Engineering 7 (2), 270-287. https://doi.org/10.1515/ijnaoe-2015-0019.
  21. Vaessens, R.J.M., Aarts, E.H.L., Lenstra, J.K., 1996. Job shop scheduling by local search. Inf. J. Comput. 8 (3), 302-317. https://doi.org/10.1287/ijoc.8.3.302.
  22. Venkataraman, P., 2002. Applied Optimization with MATLAB Programming. John Wiley and Sons.
  23. Wang, Bo, Tian, Kuo, Peng, Hao, Cai, Yuanwu, Li, Yuwei, Sun, Yu, 2015. Hybrid analysis and optimization of hierarchical stiffened plates based on asymptotic homogenization method. Compos. Struct. 132, 136-147. https://doi.org/10.1016/j.compstruct.2015.05.012.