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

UZUN B., CİVALEK Ö., AYDOĞDU İ.

JOURNAL OF APPLIED AND COMPUTATIONAL MECHANICS, vol.7, no.3, pp.1348-1361, 2021 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 7 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.22055/jacm.2019.31406.1870
  • Journal Name: JOURNAL OF APPLIED AND COMPUTATIONAL MECHANICS
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Directory of Open Access Journals
  • Page Numbers: pp.1348-1361
  • Keywords: Nano beams, Deflection analysis, Social Spider Optimization, PULL-IN INSTABILITY, FREE-VIBRATION ANALYSIS, BUCKLING ANALYSIS, BEHAVIOR, INTELLIGENCE, MICROTUBULES, ELASTICITY
  • Akdeniz University Affiliated: Yes

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.