Optimization of time-dependent displacements of the axially graphene nanoplatelets reinforced micro-curved panels via swarm and genetic algorithm approaches

Abstract

Micro-curved panels with moving micro/nanoparticles included are essential microstructures in the engineering field. So, improving its stability for use in various situations is an essential key for biomechanical engineers. There is potential for using graphene nanoplatelets (GPLs)-reinforced epoxy as the matrix phase in a fiber composite as it has been shown that GPLs successfully improve the properties of epoxy materials when compared to clean epoxy. So, in the current work, dynamic deflection of the axially reinforced thick micro-curved panel under a moving load is presented. Optimizing the geometry of composite materials is essential in structural design if you want to achieve the highest possible levels of strength or stability. In the present study, we use the genetic algorithm and particle swarm optimization to find the optimal radius ratio for lowering the displacement fields. For modeling the micro-size structure, modified couple stress theory with one length scale parameter is presented. The displacement fields are modeled using Taylor’s series higher-order terms considering strain in the thickness direction. Using forced vibration analysis, the space and time-dependent equations are solved via double Fourier series and state-space method, respectively. It is shown that reinforcing a microstructure with GPLs in the axial direction has lower deflection than in other directions. The results show that velocity and external loading of moving micro/nanoparticle, geometry properties, and length scale parameters have an important role in the time-dependent deflections of the axially reinforced thick micro-curved panel under moving micro/nanoparticles. The current outputs can be used in the biomechanical engineering field for modeling a micro-curved panel under moving micro/nanoparticles.