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Non-linear free and forced vibration analysis of sandwich nano-beam with FG-CNTRC face-sheets based on nonlocal strain gradient theory

  • Arani, Ali Ghorbanpour (Department of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan) ;
  • Pourjamshidian, Mahmoud (Department of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan) ;
  • Arefi, Mohammad (Department of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan)
  • Received : 2016.12.29
  • Accepted : 2018.04.16
  • Published : 2018.07.25
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Abstract

In this paper, the nonlinear free and forced vibration responses of sandwich nano-beams with three various functionally graded (FG) patterns of reinforced carbon nanotubes (CNTs) face-sheets are investigated. The sandwich nano-beam is resting on nonlinear Visco-elastic foundation and is subjected to thermal and electrical loads. The nonlinear governing equations of motion are derived for an Euler-Bernoulli beam based on Hamilton principle and von Karman nonlinear relation. To analyze nonlinear vibration, Galerkin's decomposition technique is employed to convert the governing partial differential equation (PDE) to a nonlinear ordinary differential equation (ODE). Furthermore, the Multiple Times Scale (MTS) method is employed to find approximate solution for the nonlinear time, frequency and forced responses of the sandwich nano-beam. Comparison between results of this paper and previous published paper shows that our numerical results are in good agreement with literature. In addition, the nonlinear frequency, force response and nonlinear damping time response is carefully studied. The influences of important parameters such as nonlocal parameter, volume fraction of the CNTs, different patterns of CNTs, length scale parameter, Visco-Pasternak foundation parameter, applied voltage, longitudinal magnetic field and temperature change are investigated on the various responses. One can conclude that frequency of FG-AV pattern is greater than other used patterns.

Keywords

Acknowledgement

Supported by : University of Kashan

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