Optimization of piezoelectric fibers in FG panel with PFRC layers using genetic algorithms

In this research the optimization of piezoelectric fibers in a functionally graded cylindrical panel with PFRC layers as sensor and actuator under dynamic load and electrical excitation with various types of supports including: simple, clamped and combination of free and clamped supports is provided. The main goal is to obtain the volume fraction of piezoelectric fibers in a PFRC layer so that the radial displacement of this layer across the circumferential direction is equal to that of piezoelectric layer. For the optimization, Genetic algorithms were used and in each case, the algorithm parameters are obtained by using Parameter Tuning method. In order to saving time and reducing the use of memory, Artificial Neural Networks are trained and employed. In the end, the results for the stresses and displacements of the panel with piezoelectric layers and the one with PFRC layers are presented and compared. The effect of support conditions and on the optimization process and the obtained volume fractions are examined. Results show that with the introduction of clamped supports, increment for maximum Von mises stress in the structure and the volume fraction of piezoelectric fibers can be seen.