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Automatic design of marine structures by using successive response surface method

  • Sami PajunenEmail author
  • Ossi Heinonen
INDUSTRIAL APPLICATION

Abstract

An automated optimization procedure based on successive response surface method is presented. The method is applied to weight optimization of a stiffened plate used in marine structures. In the design space the surrogate model is spanned sequentially into an optimally restricted subspace that is converging towards at least a local optimum. Both objective function and all constraint functions are modeled using linear response surface method enabling the use of a robust and efficient simplex algorithm for the optimizations. Special attention is paid to CAD and FEM-model linking that plays a central role in practical industrial applications. In this project SOLIDWORKS and ANSYS software are adopted for structural modeling and analysis, respectively, and the optimization is carried out in a MatLab environment. The reported results achieved in this project prove the robustness and effectiveness of the proposed approach.

Keywords

Surrogate model Response surface method Optimal design Simplex-algorithm 

Notes

Acknowledgments

Support from the Finnish Metals and Engineering Competence Cluster (FIMECC) Innovations & Network- research and the research project Computational methods in mechanical engineering product development - SIMPRO are gratefully acknowledged.

References

  1. Abu-Odeh A-Y, Jones H-L (1998) Optimum design of composite plates using response surface method. Compos Struct 43:233–242CrossRefGoogle Scholar
  2. Acar E, Guler MA, Gerceker B, Cerit ME, Bayram B (2011) Multi-objective crashworthiness optimization of tapered thin-walled tubes with axisymmetric indentations. Thin-Walled Struct 49:94–105CrossRefGoogle Scholar
  3. Arai M, Shimizu T (2001) Optimization of the design of ship structures using response surface methodology. In: Wu Y-S, Cui W-C, Zhou G-J (eds) Practical design of ships and other floating structures. pp 331–339Google Scholar
  4. Eldred MS, Dunlavy DM (2006) Formulations for surrogate-based optimization with data fit, multifidelity, and reduced-order models. In: Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, paper AIAA-2006-7117. Portsmouth, VA, 6-8 SeptGoogle Scholar
  5. Gupta KC, Li J (2000) Robust design optimization with mathematical programming neural networks. Comput Struct 76:507–516CrossRefGoogle Scholar
  6. Heinonen O, Pajunen S (2011) Optimal design of stiffened plate using metamodeling techniques. J Struct Mech 44(3):218–230Google Scholar
  7. Hock W, Schittkowski K (1981). Test examples for nonlinear programming codes. Lecture Notes in Economics and Mathematical Systems, 187. SpringerGoogle Scholar
  8. Huang Z, Wang C, Chen J, Tian H (2011) Optimal design of aeroengine turbine disc based on kriging surrogate models. Comput Struct 89:27–37CrossRefGoogle Scholar
  9. IACS (2009) Common Structural Rules for Bulk CarriersGoogle Scholar
  10. Khuri AI, Cornell JA (1987) Response surfaces: design and analyses. Marcel Dekker IncGoogle Scholar
  11. Kleijnen JPC (2008) Response surface methodology for constrained simulation optimization: an overview. Simul Model Pract Theory 16:50–64CrossRefGoogle Scholar
  12. Montgomery DC (2001) Design and analysis of experiments. WileyGoogle Scholar
  13. Nemhauser GL, Laurence AW (1988) Integer and Combinatorial Optimization. WileyGoogle Scholar
  14. Park H-S, Dang X-P (2010) Structural optimization based on CAD-CAE integration and metamodeling techniques. Comput Aided Des 42:889–902CrossRefGoogle Scholar
  15. Queipo KN, Haftka RT, Shyy W, Goel T, Vaidyanathan R, Tucker PK (2005) Surrogate-based analysis and optimization. Prog Aerosp Sci 41:1–28CrossRefGoogle Scholar
  16. Ren W-X, Chen H-B (2010) Finite element model updating in structural dynamics by using response surface method. Eng Struct 32:2455–2465CrossRefGoogle Scholar
  17. Roux WJ, Stander N, Haftka RT (1998) Response surface approximations for structural optimization. Int J Numer Methods Eng 42:517–534CrossRefzbMATHGoogle Scholar
  18. Sakata S, Ashida F, Zako M (2003) Structural optimization using Kriging approximation. Comput Methods Appl Mech Eng 192:923–939CrossRefzbMATHGoogle Scholar
  19. Simpson TW, Mauery TM, Korte JJ, Mistree F (2001) Kriging models for global approximation in simulation-based multidisciplinary design optimization. AIAA J 39(12):2233–2241CrossRefGoogle Scholar
  20. Stander N, Craig KJ (2002) On the robustness of a simple domain reduction scheme for simulation-based optimization. Eng Comput 19(4):431–450CrossRefzbMATHGoogle Scholar
  21. Yoo K-S, Eom Y-S, Park J-Y, Im M-G, Han S-Y (2011) Reliability-based topology optimization using successive standard response surface method. Finite Elem Anal Des 47:843–849CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Mechanics and DesignTampere University of TechnologyTampereFinland

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