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Optimization of Temperature-Dependent Functionally Graded Material Based on Colonial Competitive Algorithm

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Abstract:

A functionally graded material is optimized for thermal buckling. The buckling problem is formulated where temperature-dependence constituents’ properties are included. Then the Colonial Competitive Algorithm (CCA) is used for optimization of critical thermal buckling load with variation thickness. The results CCA optimization is compared with third order shear deformation theory and another optimum method based on Genetic Algorithm (GA).

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Periodical:

Applied Mechanics and Materials (Volumes 121-126)

Pages:

4575-4580

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.121-126.4575

Citation:

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Online since:

October 2011

Authors:

Hamid Mozafari, Behzad Abdi, Ayob Amran

Keywords:

Colonial Competitive Algorithm (CCA), Functional Graded Material (FGM), Genetic Algorithm (GA), Variation Thickness

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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