Stochastic normal mode frequency analysis of hybrid angle ply laminated composite skew plate with opening using a novel approach

In the present work, for the first time, stochastic normal mode frequency analysis of hybrid angle ply laminated composite skew plate with an opening is attempted by a novel approach. The present novel approach employed 2 D C-0 stochastic finite element (FE) model based on higher-order shear deformation theory (HSDT) in conjunction with artificial neural network (ANN) and artificial neural network-particle swarm optimization (ANN-PSO). HSDT model used eliminates the requirement of shear correction factor owing to consideration of the actual parabolic distribution of transverse shear stress. Zero transverse shear stress at the top and bottom of the plate is enforced to compute higher-order unknowns. C-0 FE model makes it commercially viable. Stochastic vibration using FE analysis with Monte Carlo simulation, design of experiment (DOE), and soft computing with ANN, ANN-PSO is implemented. With the DOE method, a total of 128 design points are generated. Since there are no results for the present problem in the literature is available. Hence suitable comparisons have been made and found in the good agreement. The stochastic parameters are Young's elastic modulus, shear modulus, and the Poisson ratio. Lognormal distribution of properties is assumed in the present work. The present soft computation models shrink the trial and are found computationally in agreement with the Monte Carlo simulation-based finite element modeling (MCS-FEM). Current work reveals that ANN-PSO is a fast and straightforward method with result accuracy close to MCS-FEM, and the future researcher in this area may use ANN-PSO.