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Dynamic response of FG carbon nanotubes nanoplates embedded in elastic media under moving point load

  • Mohamed A Eltaher (Mechanical Engineering Department, Faculty of Engineering, King Abdulaziz University) ;
  • Ismail Esen (Department of Mechanical Engineering, Karabuk University) ;
  • Alaa A. Abdelrahman (Mechanical Design & Production Department, Faculty of Engineering, Zagazig University) ;
  • Azza M. Abdraboh (Physics Department, Faculty of Science, Benha University)
  • Received : 2021.12.30
  • Accepted : 2024.09.10
  • Published : 2024.09.25
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Abstract

This work aims to study and analyse the dynamic size dependent behvior of functionally graded carbon nanotubes (FGCNTs) nanoplates embedded in elastic media and subjected to moving point load. The non-classical effect is incorporated into the governing equations using the nonlocal strain gradient theory (NSGT). Four different reinforcement configurations of the carbon nanotubes (CNTs) are considered to show the effect of reinforcement configuration on the dynamic behvior of the FGCNTs nanoplates. The material characteristics of the functionally graded materials are assumed to be continuously distributed throughout the thickness direction according to the power law. The Hamiltonian principle is exploited to derive the dynamic governing equations of motion and the associated boundary conditions in the framework of the first order shear deformation plate theory. The Navier analytical approach is adopted to solve the governing equations of motion. The obtained solution is checked by comparing the obtained results with the available results in the literature and the comparison shows good agreement. Numerical results are obtained and discussed. Obtained results showed the significant impact of the elastic foundation parameters, the non-classical material parameters, the CNT configurations, and the volume fractions on the free and forced vibration behaviors of the FGCNT nanoplate embedded in two parameters elastic foundation and subjected to moving load.

Keywords

Acknowledgement

This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grand no. (GPIP: 375-135-2024). The Authors, therefore, acknowledge with thanks DSR for technical and financial support.

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