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Vibrational analysis of carbon nanotubes using molecular mechanics and artificial neural network
Authors:Mir Masoud Seyyed Fakhrabadi  Mostafa Samadzadeh  Abbas Rastgoo  Mohammadreza Haeri Yazdi  Mahmoud Mousavi Mashhadi
Institution:aKaraj Branch, Islamic Azad University, Karaj, Iran;bSchool of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Abstract:This paper presents the molecular mechanics based finite element modeling of carbon nanotubes (CNTs) and their applications as mass sensors. The beam element with elastic behavior is considered as the bond between the carbon atoms and its properties are obtained using equating continuum and molecular characteristics. The first five natural frequencies of CNTs in cantilever and doubly clamped boundary conditions (BCs) and their corresponding mode shapes are studied in detail. Furthermore, a multilayer perceptron neural network is used to predict the fundamental vibration frequencies of the CNTs with different diameters and lengths. In addition, variations of the natural frequencies of the CNTs with distorted cross sections are investigated. Moreover, the effects of some attached masses with various values on the first three natural frequencies of a considered CNT are studied here.
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