Loading…

Optimization Design of Fairings for VIV Suppression Based on Data-Driven Models and Genetic Algorithm

Vortex induced vibration (VIV) is a challenge in ocean engineering. Several devices including fairings have been designed to suppress VIV. However, how to optimize the design of suppression devices is still a problem to be solved. In this paper, an optimization design methodology is presented based...

Full description

Saved in:
Bibliographic Details
Published in:China ocean engineering 2021-02, Vol.35 (1), p.153-158
Main Authors: Liu, Xiu-quan, Jiang, Yong, Liu, Fu-lai, Liu, Zhao-wei, Chang, Yuan-jiang, Chen, Guo-ming
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Vortex induced vibration (VIV) is a challenge in ocean engineering. Several devices including fairings have been designed to suppress VIV. However, how to optimize the design of suppression devices is still a problem to be solved. In this paper, an optimization design methodology is presented based on data-driven models and genetic algorithm (GA). Data-driven models are introduced to substitute complex physics-based equations. GA is used to rapidly search for the optimal suppression device from all possible solutions. Taking fairings as example, VIV response database for different fairings is established based on parameterized models in which model sections of fairings are controlled by several control points and Bezier curves. Then a data-driven model, which can predict the VIV response of fairings with different sections accurately and efficiently, is trained through BP neural network. Finally, a comprehensive optimization method and process is proposed based on GA and the data-driven model. The proposed method is demonstrated by its application to a case. It turns out that the proposed method can perform the optimization design of fairings effectively. VIV can be reduced obviously through the optimization design.
ISSN:0890-5487
2191-8945
DOI:10.1007/s13344-021-0014-3