The authors examined the numerical natural frequency analysis of a 2D functionally graded (FG) truncated thick hollow cone using 3D elasticity theory.
The material properties of the 2D-FGM (two dimensional-functionally graded materials) cone are graded along the radial and axial axes of the cone using a power–law distribution. The eigenvalue problem was solved using finite element analysis (FEA) employing graded hexahedral elements, and the verification of the finite element approach was assessed by comparing the current solution to earlier experimental studies.
The effects of semivertex angle, material distribution and the cone configuration on the natural frequencies have been analyzed. For various semivertex angles, thickness, length and power law exponents, many results in the form of natural frequencies and mode shapes are presented for the 2D-FGM cone. As a result, the effects of the given parameters were addressed, and the results were compared, demonstrating the direct efficiency of raising the power–law exponents and cone thickness on the rise of natural frequencies.
For the first time, the numerical natural frequency analysis of a 2D-FG truncated thick hollow truncated cone based on 3D equations of elasticity has been investigated. The material properties of the truncated cone have been distributed along two directions, which has not been considered before in any research for the truncated thick cone. The reason for using these innovative volume fraction functions is the lack of accurate coverage by functions that are available in the literature (Asemi et al., 2011; Babaei et al. 2021).
This work was supported by the Doctoral Scientific Research Foundation of the HUAT under Grant No. BK202205 and the Foundation of the Key Laboratory of Automotive Power Train and Electronics (Hubei University of Automotive Technology) under Grant No. ZDK1202105.
Najibi, A., Kianifar, M. and Ghazifard, P. (2023), "Three-dimensional natural frequency investigation of bidirectional FG truncated thick hollow cone", Engineering Computations, Vol. 40 No. 1, pp. 100-125. https://doi.org/10.1108/EC-05-2022-0377
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