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%.

Buckling optimization of variable stiffness cylindrical shells through artificial intelligence techniques

Pitton, Stefano Francesco;Ricci, Sergio;Bisagni, Chiara
2019-01-01

Abstract

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%.
2019
Variable stiffness
Buckling
Cylindrical shells
Fibers path
Artificial neural networks
Particle swarm optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1110131
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