Journal of Applied and Computational Mechanics (Jul 2021)
Optimum Design of Nano-Scaled Beam Using the Social Spider Optimization (SSO) Algorithm
Abstract
In this research study, the optimum cross-sectional dimensions of nano-scale beam elements are investigated under different load conditions. Euler-Bernoulli beam model based on nonlocal elasticity theory is utilized for the analysis of the beam. Two types of nano-scaled beams are modeled; carbon nanotubes (CNTs) and Boron nitride nanotubes (BNNTs). The novel meta-heuristic based optimization algorithm called Social Spider Optimization (SSO) algorithm is employed to find the beam designs with the objective of minimizing the cross-sectional area. Furthermore, the obtained optimum cross-sectional dimensions, critical stress and displacement values of the beams are compared according to the material type, beam length, and load conditions.
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