2019
DOI: 10.5194/ms-10-145-2019
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Buckling of elastically restrained nonlocal carbon nanotubes under concentrated and uniformly distributed axial loads

Abstract: Abstract. Buckling of elastically restrained carbon nanotubes is studied subject to a combination of uniformly distributed and concentrated compressive loads. Governing equations are based on the nonlocal model of carbon nanotubes. Weak formulation of the problem is formulated and the Rayleigh quotients are obtained for distributed and concentrated axial loads. Numerical solutions are obtained by Rayleigh–Ritz method using orthogonal Chebyshev polynomials. The method of solution is verified by checking against… Show more

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Cited by 2 publications
(2 citation statements)
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“…where 𝑞 (𝑥), 𝑞 (𝑥) and 𝑞 (𝑥) are the distributed loads and 𝑞 (𝑥) corresponds to the distributed torque. Finally, according to Robinson and Adali [6], the variation of the work due to the Winkler-Pasternak elastic foundation is given by…”
Section: Internal Work External Work and Elastic Workmentioning
confidence: 99%
“…where 𝑞 (𝑥), 𝑞 (𝑥) and 𝑞 (𝑥) are the distributed loads and 𝑞 (𝑥) corresponds to the distributed torque. Finally, according to Robinson and Adali [6], the variation of the work due to the Winkler-Pasternak elastic foundation is given by…”
Section: Internal Work External Work and Elastic Workmentioning
confidence: 99%
“…Traditional semiconductor principles cannot explain this phenomenon. In recent years, scientists have proposed a method of using carbon nanotubes instead of existing wires to achieve the functionality of connected nanodevices (Mohsin et al, 2013;Bocko et al, 2018;Robinson and Adali, 2019). Carbon nanotube wires can be used to connect microelectrodes and macroscopic devices owing to their excellent electrical conductivity and microscopic properties, which can build the construction of cross-scale systems to satisfy the high-sensitivity and high-performance functions required in the fields of biology and information (Wang et al, 2013;Yuan et al, 2018;Bocko and Lengvarský, 2017).…”
Section: Introductionmentioning
confidence: 99%