Maximization of Eigenfrequency Gaps in a Composite Cylindrical Shell Using Genetic Algorithms and Neural Networks

Maximization of Eigenfrequency Gaps in a Composite Cylindrical Shell Using Genetic Algorithms and Neural Networks

This paper presents a novel method for the maximization of eigenfrequency gaps around external excitation frequencies by stacking sequence optimization in laminated structures. The proposed procedure enables the creation of an array of suggested lamination angles to avoid resonance for each excitati...

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Bibliographic Details
Main Authors: Bartosz Miller, Leonard Ziemiański
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Applied Sciences
Subjects:
shell
composite
lamination angles
optimization
genetic algorithms
artificial neural networks
Online Access:https://www.mdpi.com/2076-3417/9/13/2754

Internet

https://www.mdpi.com/2076-3417/9/13/2754

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