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Articles

Application of particle swarm optimization and genetic algorithm methods for maximizing the phase velocity in the multi-layer nanoscale system

Pages 2302-2322 | Received 09 Jan 2021, Accepted 21 Feb 2021, Published online: 16 Mar 2021
 

Abstract

In this article, as a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the propagated waves in the sandwich nanoplate via finding optimum phase velocity value. The FSE method is used to solve the governing equations of the nanosystem. For increasing the performance of GAs for solving the problem, the PSO technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 30%. A useful suggestion is that the magnetic field’s effect on the phase velocity is greater than the electric field’s impact on the wave propagation of the magneto-electro-elastic (MEE) nanosystem. As the related industry’s relevant result, the optimum value of angle play of layers is equal to 37.5 degrees that should be attention to this value.

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