Optimum Design of Nano-Scaled Beam Using the Social Spider Optimization (SSO) Algorithm
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 nan...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Shahid Chamran University of Ahvaz
2021-07-01
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| Series: | Journal of Applied and Computational Mechanics |
| Subjects: | |
| Online Access: | https://jacm.scu.ac.ir/article_15044_dab7fc19134d339fdbcddd726dab1676.pdf |
| Summary: | 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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| ISSN: | 2383-4536 2383-4536 |