The University of Southampton
University of Southampton Institutional Repository

A new approach to analyse the underwater vibration of double layer ribbed cylinder

A new approach to analyse the underwater vibration of double layer ribbed cylinder
A new approach to analyse the underwater vibration of double layer ribbed cylinder
Analyzing double layer ribbed cylinder’s underwater vibration is of great importance to the design and evaluation of vessels’ dynamic performance of operation and human comfort level. The two main traditional methods that are applied to solve this work are Flügge’s equations of motion and numerical method, such as FEM. Even though both methods have their own special advantages, complicated model developing process and comparative low accuracy (compared with data from real measurement) are their common drawbacks. In this paper, Neural Network is used to analyze the dynamic character of this double layer ribbed cylinder. Real measurement data are used to construct Neural Network, and after this Neural Network model is well built, comparison studies are processed between the vibration data of some positions of interest on the cylinder acquired from Neural Network and real test, respectively. The results show that Neural Network can be used to analyse the dynamic character of double layer ribbed cylinder and is of high accuracy and timesaving. The next step of this research will be concentrated on using more representative vibration data to develop Neural Network model.
978-1-315-68505-2
175-180
CRC Press
Wang, Fei
d74a565b-35c9-43af-95ba-06782f81a561
Xiong, Yeping
51be8714-186e-4d2f-8e03-f44c428a4a49
Weng, Zhengping
efb60eb7-db31-46e9-9954-4df85e00b962
He, Lin
5ea3d9f4-89a0-4ec2-9ee5-87232c4279de
Guedes Soares, Carlos
Shenoi, R. Ajit
Wang, Fei
d74a565b-35c9-43af-95ba-06782f81a561
Xiong, Yeping
51be8714-186e-4d2f-8e03-f44c428a4a49
Weng, Zhengping
efb60eb7-db31-46e9-9954-4df85e00b962
He, Lin
5ea3d9f4-89a0-4ec2-9ee5-87232c4279de
Guedes Soares, Carlos
Shenoi, R. Ajit

Wang, Fei, Xiong, Yeping, Weng, Zhengping and He, Lin (2015) A new approach to analyse the underwater vibration of double layer ribbed cylinder. In, Guedes Soares, Carlos and Shenoi, R. Ajit (eds.) Analysis and Design of Marine Structures V. Boca Raton. CRC Press, pp. 175-180. (doi:10.1201/b18179-24).

Record type: Book Section

Abstract

Analyzing double layer ribbed cylinder’s underwater vibration is of great importance to the design and evaluation of vessels’ dynamic performance of operation and human comfort level. The two main traditional methods that are applied to solve this work are Flügge’s equations of motion and numerical method, such as FEM. Even though both methods have their own special advantages, complicated model developing process and comparative low accuracy (compared with data from real measurement) are their common drawbacks. In this paper, Neural Network is used to analyze the dynamic character of this double layer ribbed cylinder. Real measurement data are used to construct Neural Network, and after this Neural Network model is well built, comparison studies are processed between the vibration data of some positions of interest on the cylinder acquired from Neural Network and real test, respectively. The results show that Neural Network can be used to analyse the dynamic character of double layer ribbed cylinder and is of high accuracy and timesaving. The next step of this research will be concentrated on using more representative vibration data to develop Neural Network model.

Full text not available from this repository.

More information

Published date: March 2015
Organisations: Fluid Structure Interactions Group

Identifiers

Local EPrints ID: 386536
URI: http://eprints.soton.ac.uk/id/eprint/386536
ISBN: 978-1-315-68505-2
PURE UUID: 25799948-31eb-489e-8bc4-ce23791eb08e
ORCID for Yeping Xiong: ORCID iD orcid.org/0000-0002-0135-8464

Catalogue record

Date deposited: 02 Feb 2016 11:32
Last modified: 15 Jul 2020 00:27

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×