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An automatic multi-objective optimization tool for the optimum design of a cracked pressure vessel with composite coating

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Abstract

This paper proposes an automatic multi-objective optimization tool for the optimum design of a cracked pressure vessel with composite coating based on the non-dominated sorting genetic algorithm (NSGA-II) and maximum tangential strain energy density (MTSED) criterion. The proposed tool takes into consideration all the important parameters of the optimization of composite materials such as the angle, thickness, number, and material of each layer, as well as the effective parameters of fracture mechanics such as the orientation, length, and aspect ratio of cracks in the metallic liner of vessels. The optimization processes have been conducted for 3D longitudinal, circumferential and inclined semi-elliptical cracks in the sample composite pressure vessel and optimal stacking sequences and Pareto’s front for each kind of crack are presented. The in-plane and out of plane fracture envelop predicted by the MTSED criterion before and after optimization under mixed mode I/II/III have been investigated. The proposed tool is validated against collected results from existing literature and these results have largely agreed with each other.

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Correspondence to Mahdi Fakoor.

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Recommended by Associate Editor Gil-Ho Yoon

Seyed Mohammad Navid Ghoreishi received his Ph.D. in Aerospace Engineering from University of Tehran in 2018. His research interests include the fields of fracture mechanics, composite materials, and optimization.

Mahdi Fakoor is currently an Associate Professor in the Faculty of New Sciences and Technologies, Department of Aerospace Engineering, University of Tehran, Tehran, Iran. His research interests include the fields of fracture mechanics, composite materials, and optimization.

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Ghoreishi, S.M.N., Fakoor, M. & Aminjafari, M. An automatic multi-objective optimization tool for the optimum design of a cracked pressure vessel with composite coating. J Mech Sci Technol 33, 4867–4875 (2019). https://doi.org/10.1007/s12206-019-0927-4

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  • DOI: https://doi.org/10.1007/s12206-019-0927-4

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