Optimization of material composition to minimize the thermal stresses induced in FGM plates with temperature-dependent material properties

A hybrid genetic algorithm with the complex method is developed for the optimization of the material composition of a multi-layered functionally graded material plate with temperature-dependent material properties in order to minimize the thermal stresses induced in the plate when it is subjected to steady-state thermal loads. In the formulation, the plate is artificially divided into an n_l-layered plate, and a weak-form-based finite layer method is developed to obtain the displacement and stress components induced in the n_l-layered plate using the Reissner mixed variational theorem. Two thermal conditions, namely the specified temperature and heat convection conditions, imposed on the top and bottom surfaces of the plate are considered. The through-thickness distributions of the volume fractions of the constituents are assumed as certain specific/non-specific function distributions, such as power-law, sigmoid, layerwise step and layerwise linear function distributions, and the effective material properties of the plate are estimated using the Mori–Tanaka scheme. Comparisons with regard to the minimization for the peak values of the stress ratios induced in the FGM plates with various optimal material compositions are conducted.