Static bending response of axially randomly oriented functionally graded carbon nanotubes reinforced composite nanobeams

Ahmed Amine Daikh , Ahmed Drai , Mohamed Ouejdi Belarbi , Mohammed Sid Ahmed Houari , Benoumer Aour , Mohamed A. Eltaher , Norhan A. Mohamed

Abstract

In this work, an analytical model employing a new higher-order shear deformation beam theory is utilized to investigate the bending behavior of axially randomly oriented functionally graded carbon nanotubes reinforced composite nanobeams. A modified continuum nonlocal strain gradient theory is employed to incorporate both microstructural effects and geometric nano-scale length scales. The extended rule of mixture, along with molecular dynamics simulations, is used to assess the equivalent mechanical properties of functionally graded carbon nanotubes reinforced composite (FG-CNTRC) beams. Carbon nanotube reinforcements are randomly distributed axially along the length of the beam. The equilibrium equations, accompanied by nonclassical boundary conditions, are formulated, and Navier's procedure is used to solve the resulting differential equation, yielding the response of the nanobeam under various mechanical loadings, including uniform, linear, and sinusoidal loads. Numerical analysis is conducted to examine the influence of inhomogeneity parameters, geometric parameters, types of loading, as well as nonlocal and length scale parameters on the deflections and stresses of axially functionally graded carbon nanotubes reinforced composite (AFG CNTRC) nanobeams. The results indicate that, in contrast to the nonlocal parameter, the beam stiffness is increased by both the CNTs volume fraction and the length-scale parameter. The presented model is applicable for designing and analyzing microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) constructed from carbon nanotubes reinforced composite nanobeams.

Key Words

axially CNTs distribution; Navier's solution; nonlocal strain gradient higher order shear deformation theory; static bending and stress analyses

Address

Ahmed Amine Daikh — Artificial Intelligence Laboratory for Mechanical and Civil Structures, and Soil, University Centre of Naama, Naama, Algeria/ Laboratoire d'Etude des Structures et de Mécanique des Matériaux, Département de Génie Civil, Faculté des Sciences et de la Technologie, Université Mustapha Stambouli B.P. 305, R.P. 29000 Mascara, Algérie
Ahmed Drai — Department of Mechanical Engineering, Mustapha STAMBOULI University of Mascara, 29000, Algeria/ LABAB Laboratory of ENPO, Oran, 31000, Algeria
Mohamed Ouejdi Belarbi — Laboratoire de Génie Energétique et Matériaux, LGEM, Université de Biskra, B.P. 145, R.P. 07000, Biskra, Algeria/ Department of Civil Engineering, Lebanese American University, Byblos, Lebanon
Mohammed Sid Ahmed Houari — Laboratoire d'Etude des Structures et de Mécanique des Matériaux, Département de Génie Civil, Faculté des Sciences et de la Technologie, Université Mustapha Stambouli B.P. 305, R.P. 29000 Mascara, Algérie
Benoumer Aour — LABAB Laboratory of ENPO, Oran, 31000, Algeria
Mohamed A. Eltaher — Faculty of Engineering, Mechanical Engineering Department, King Abdulaziz University, P.O. Box 80204, Jeddah, Saudi Arabia/ Faculty of Engineering, Mechanical Design and Production Department, Zagazig University, Zagazig, Egypt
Norhan A. Mohamed — Engineering Mathematics Department, Faculty of Engineering, Zagazig University, Zagazig Egypt

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