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

Document Type : Research Paper


1 Department of Civil Engineering, Faculty of Engineering, UludağUniversity, Bursa, Turkey

2 Research Center for Interneural Computing, China Medical University, Taiwan

3 Department of Civil Engineering, Faculty of Engineering, Akdeniz University, Antalya, 07050, Turkey


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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