Multi-objective optimal design of thick two-dimensional functionally graded flywheels

Aytac Arikoglu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In this study, optimal design of two-dimensional functionally graded thick flywheels is obtained by the generalized differential quadrature method (GDQM) and the non-dominated sorting genetic algorithm II (NSGA II). The flywheel cross section is parameterized with the Bezier surface, and a mapping procedure to discretize non-rectangular solution domain by the GDQM is introduced. The results of this novel technique are compared with the results available in open literature and the ANSYS finite element solution, and a very good agreement is observed. Pareto optimal solutions for minimum mass and maximum energy storage capability are obtained for two types of bearing, one being mechanical and the other magnetic. Consequently, the optimal cross-section geometry and the two-dimensional material distribution of functionally graded (FG) flywheel are obtained.

Original languageEnglish
Pages (from-to)1547-1561
Number of pages15
JournalStructural and Multidisciplinary Optimization
Issue number3
Publication statusPublished - Mar 2021

Bibliographical note

Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.


This research has been supported by The Scientific and Technological Research Council of Turkey (Project number: 115M436).

FundersFunder number
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu115M436


    • 2D functionally graded materials
    • Differential quadrature
    • Genetic algorithm
    • Thick flywheel


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