Buckling optimization of variable stiffness cylindrical shells through artificial intelligence techniques

Stefano Francesco Pitton*, Sergio Ricci, Chiara Bisagni

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

33 Citations (Scopus)


Thin-walled cylindrical shells are nowadays widely used for principal structures in the aerospace field. Despite the capacity to sustain high levels of axial compressive loads they are also easily prone to fall into buckling. One of the methods currently studied to increase the value of the critical load associated with this phenomenon consists in the use of curvilinear fibers, through which it is possible to continuously change the stiffness, and consequently the local behavior of the structure. The paper describes an optimization methodology developed for the buckling optimization of thin-walled variable stiffness cylindrical shells subjected to axial load, together with a general fibers path formulation. The framework proposed involves a synergic work between the finite element method and artificial intelligence techniques. The optimal configuration shows an increase of the buckling load of about 4% together with an increase of the pre-buckling stiffness of about 6%.

Original languageEnglish
Article number111513
Number of pages9
JournalComposite Structures
Publication statusPublished - 15 Dec 2019


  • Artificial neural networks
  • Buckling
  • Cylindrical shells
  • Fibers path
  • Particle swarm optimization
  • Variable stiffness


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