Modelling the buckling behaviour of composite hemispherical dome ends under external pressure using artificial neural networks
In this study, artificial neural network (ANN) was used in modelling the buckling behaviour of fully clamped composite hemispherical dome ends under external pressure. Due to ability of ANN in learning by examples, this method can be used to simulate a wide range of non-linear complex scientific systems. ANN can be used in medical applications; image recognition and control of dynamic systems and recently have been used for the prediction of the mechanical behaviour of composite materials. This work is an attempt to use finite element analysis and a multi-layered neural network in the modelling of buckling behaviour composite hemispherical dome ends. Keywords: Artificial neural networks, composite materials, buckling behaviour, hemispherical dome;
Abstract A numerical scheme, based upon the Kobayashi-Tranter method with certain modifications, is given for axisymmetric punch and crack problems in elasticity. The problems are reduced to solving a system of linear algebraic equations instead of a Fredholm integral equation of the second kind. A standard program thus allows the treatment of a range of different cases. The indentation of a rigid punch on an elastic layer overlying an elastic foundation is formulated in this fashion and numerical results for various cases are presented.