Stochastic Free Vibration Behavior of Multi-Layered Helicoidal Laminated Composite Shells Under Thermal Conditions

The present work aims to quantify the influence of uncertainties in the ply orientation of multi-layered bio-inspired helicoidal laminated composite conical, hemispherical, and toroidal shells under thermal conditions. Any change in the ply orientation affects the free vibration behavior of the laminates. The present investigation focuses on the different levels of uncertainties in the ply orientation on the free vibration behavior of the shell. Moreover, the study also focuses on the sensitivity of the uncertainties in ply orientations on the free vibration behavior of the shells, which is also quantified. To quantify the stochastic free vibration behavior of the shells, the Gaussian process regression (GPR) machine learning algorithm-based surrogate model is developed to predict the frequencies of the shells. The surrogate is created in the framework of higher-order shear deformation theory. The uncertainties in the ply orientations are introduced using bootstrapping. The present results are compared with the stochastic frequencies obtained using Monte Carlo simulations (MCS) to determine the model’s accuracy. The study highlights the influence of the temperature, type of shell, and end conditions on the stochastic free vibration behavior of bio-inspired laminated shells.