Automated Selection of Optimal Material for Pressurized Multi-Layer Composite Tubes Based on an Evolutionary Approach
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Date
2018
Authors
Azad, Saeid Kazemzadeh
Akış, Tolga
Akis, Tolga
Azad, Saeıd Kazemzadeh
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Volume Title
Publisher
Springer London Ltd
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Abstract
Decision making on the configuration of material layers as well as thickness of each layer in composite assemblies has long been recognized as an optimization problem. Today, on the one hand, abundance of industrial alloys with different material properties and costs facilitates fabrication of more economical or light weight assemblies. On the other hand, in the design stage, availability of different alternative materials apparently increases the complexity of the design optimization problem and arises the need for efficient optimization techniques. In the present study, the well-known big bang-big crunch optimization algorithm is reformulated for optimum design of internally pressurized tightly fitted multi-layer composite tubes with axially constrained ends. An automated material selection and thickness optimization approach is employed for both weight and cost minimization of one-, two-, and three-layer tubes, and the obtained results are compared. The numerical results indicate the efficiency of the proposed approach in practical optimum design of multi-layer composite tubes under internal pressure and quantify the optimality of different composite assemblies compared to one-layer tubes.
Description
Akis, Tolga/0000-0002-6754-4497; Kazemzadeh Azad, Saeid/0000-0001-9309-607X
Keywords
Metaheuristics, Composite assembly, Evolutionary algorithm, Multi-layer composite tubes, Big bang-big crunch algorithm, Design optimization
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Fields of Science
Citation
10
WoS Q
Q2
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Source
Volume
29
Issue
7
Start Page
405
End Page
416