A hybrid algorithm for modeling and studying of the effect of material and mechanical uncertainties on stability of sandwich FGM materials under thermal shock

Abstract

Functionally graded material (FGM) structures are commonly used to withstand thermal stresses. These structures are very likely to experience thermal shocks. Given their nature, cylindrical shells are often subjected to a variety of dynamic loads so that the risk of instability (particularly dynamic instability) is very anticipated if they are subjected to a sudden thermal stress and a dynamic load, simultaneously. In fact, the possibility of uncertainty is very high in the fundamental parameters which determine thermal stresses. There is also uncertainty in the other properties of the structure including mechanical and thermal properties. Therefore, the present study addresses the dynamic stability of FGM cylindrical shells subjected to thermal and mechanical stresses based on Budiansky and Ruth’s criterion. The point estimation method and the artificial neural network-based algorithm were used to simulate the sources of uncertainty and to extract the statistical properties including the mean value, standard deviation, probability density functions (PDF), and cumulative distribution functions (CDF). The higher-order sheardeformationtheory (HSDT) was used to obtain the equilibrium equations, while the differential quadrature (DQ) method was used for their discretization. Functionally graded materials were assumed to change gradually along the thickness. The thermal shock distributions were based on a laboratory model (aerodynamic heating conditions) and two mathematical functions. The primary conditions, the type of thermal shock distribution, and the properties of the FGM core had the highest influence on the different stochastic properties of sandwich FGM cylindrical shells.