Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach

Shabbir Ahmed, Omar and Syed Mohamed Ali, Jaffar and Aabid, Abdul and Hrairi, Meftah and Mohd Yatim, Norfazrina Hayati (2024) Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach. Materials, 17 (17). pp. 1-27. E-ISSN 1996-1944

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Abstract

This research focuses on investigating the buckling strength of thin-walled composite structures featuring various shapes of holes, laminates, and composite materials. A parametric study is conducted to optimize and identify the most suitable combination of material and structural parameters, ensuring the resilience of structure under both mechanical and thermal loads. Initially, a numerical approach employing the finite element method is used to design the C-section thin-walled composite structure. Later, various structural and material parameters like spacing ratio, opening ratio, hole shape, fiber orientation, and laminate sequence are systematically varied. Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. Various ML techniques such as linear regression, lasso regression, decision tree, random forest, and gradient boosting are employed to assess their accuracy in comparison with finite element results. As a result, the simulation model showcases the variation in critical buckling load when altering the structural and material properties. Additionally, the machine learning models successfully predict the optimal critical buckling load under mechanical and thermal loading conditions. In summary, this paper delves into the study of the stability of C-section thin-walled composite structures with holes under mechanical and thermal loading conditions using finite element analysis and machine learning studies.

Item Type:	Article (Journal)
Uncontrolled Keywords:	C-section channel; composite laminates; buckling analysis; FE analysis; machine learning
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA349 Mechanics of engineering. Applied mechanics T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL500 Aeronautics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering Kulliyyah of Engineering
Depositing User:	Dr Mohamed Ali Jaffar Syed
Date Deposited:	25 Sep 2024 08:57
Last Modified:	25 Sep 2024 09:23
URI:	http://irep.iium.edu.my/id/eprint/114640

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