Optimum Design of Nano-Scaled Beam Using the Social Spider Optimization (SSO) Algorithm

In the present study, the optimum cross-sectional dimensions of nano-scale beam elements have been investigated under different load conditions. Euler-Beoulli beam model based on non-local elasticity theory was used 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 was utilized to find the beam designs with the objective of minimizing the cross-sectional area. Finally, obtained optimum cross-sectional dimensions, critical stress and displacement values of the beams were compared according to the material type, beam length, and load conditions.