Parallel Artificial Immune System in Optimization and Identification of Composite Structures

  • Witold Beluch
  • Tadeusz Burczyński
  • Wacaw Kuś
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6239)


The paper deals with the application of the Artificial Immune System to the optimization and identification of composites. To reduce the computational time parallel computations are performed. Composite structures in form of multilayered laminates are taken into account. Simple and hybrid (with laminas made of different materials) laminates are examined. Different optimization criteria connected with stiffness and modal properties of laminate structures are considered. Continuous and discrete variants of design variables are regarded. The aim of the identification is to find laminate elastic constants on the basis of measurements of state variable values. The Finite Element Method is employed to solve the boundary-value problem for laminates. Numerical examples presenting effectiveness of proposed method are attached.


Artificial Immune System optimization identification parallel computing composite laminate 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adali, S., Richte, A., Verijenko, V.E., Summers, E.B.: Optimal design of symmetric hybrid laminates with discrete ply angles for maximum buckling load and minimum cost. Compos. Struct. 32, 409–415 (1995)CrossRefGoogle Scholar
  2. 2.
    Beluch, W.: Evolutionary Identification and Optimization of Composite Structures. Mech. Adv. Mater. Struct. 14(8), 677–686 (2007)CrossRefGoogle Scholar
  3. 3.
    Beluch, W., Burczyński, T.: Multi-objective optimization of composite structures by means of the evolutionary computations. In: 8th World Congress on Structural and Multidisciplinary Optimization (WCSMO-8), CD-ROM, Lisbon (2009)Google Scholar
  4. 4.
    Beluch, W., Burczyński, T., Kuś, W.: Evolutionary optimization and identification of hybrid laminates. In: Evolutionary Computation and Global Optimization 2006, Warsaw, pp. 39–48 (2006)Google Scholar
  5. 5.
    Bui, H.D.: Inverse Problems in the Mechanics of Materials: An Introduction. CRC Press, Bocca Raton (1994)Google Scholar
  6. 6.
    Burczyński, T.: The Boundary Element Method in Mechanics (in Polish). WNT, Warsaw (1995)Google Scholar
  7. 7.
    Burczyński, T., Beluch, W., Długosz, A., Orantek, P., Nowakowski, M.: Evolutionary methods in inverse problems of engineering mechanics. In: Int. Symposium on Inv. Problems in Eng. Mechanics ISIP 2000, Nagano (2000)Google Scholar
  8. 8.
    de Castro, L.N., Von Zuben, F.J.: Learning and Optimization Using the Clonal Selection Principle. IEEE Transactions on Evolutionary Computation, Special Issue on Artificial Immune Systems 6(3), 239–251 (2002)Google Scholar
  9. 9.
    Dziatkiewicz, G., Fedeliński, P.: Indirect Trefftz method for solving Cauchy problem of linear piezoelecricity. In: Int. Conf. on Comput. Modelling and Advanced Simulations, Bratislava, pp. 29–30 (2009)Google Scholar
  10. 10.
    Ferrero, J.F., Barrau, J.J., Segura, J.M., Sudre, M., Castanie, B.: Analytical theory for an approach calculation of non-balanced composite box beams. Thin-Walled Struct. 39(8), 709–729 (2001)CrossRefGoogle Scholar
  11. 11.
    German, J.: Basics of the fibre-reinforced composites’ mechanics (in Polish). Publ. of the Cracow University of Technology, Cracow (2001)Google Scholar
  12. 12.
    Kathiravan, R., Ganguli, R.: Strength design of composite beam using gradient and particle swarm optimization. Compos. Struct. 81, 471–479 (2007)CrossRefGoogle Scholar
  13. 13.
    Kuś, W., Burczyński, T.: Parallel artificial immune system in optimization of mechanical structures. In: Recent Developments in Artificial Intelligence Methods, Gliwice, pp. 163–166 (2004)Google Scholar
  14. 14.
    Kuś, W., Burczyński, T.: Parallel Bioinspired Algorithms in Optimization of Structures. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds.) PPAM 2007. LNCS, vol. 4967, pp. 1285–1292. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, New York (1992)zbMATHGoogle Scholar
  16. 16.
    Ptak, M., Ptak, W.: Basics of Immunology (in Polish). Jagiellonian University Press, Cracow (2000)Google Scholar
  17. 17.
    Uhl, T.: Computer-aided identification of constructional models (in Polish). WNT, Warsaw (1997)Google Scholar
  18. 18.
    Wierzchoń, S.T.: Artificial Immune Systems. Theory and Applications (in Polish). Akademicka Oficyna Wydawnicza EXIT, Warsaw (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Witold Beluch
    • 1
  • Tadeusz Burczyński
    • 1
    • 2
  • Wacaw Kuś
    • 1
  1. 1.Department of Strength of Materials and Computational MechanicsSilesian University of TechnologyGliwicePoland
  2. 2.Institute of Computer ScienceCracow University of TechnologyCracowPoland

Personalised recommendations