The University of Southampton
University of Southampton Institutional Repository

Offshore crane non-linear stochastic response: novel design and extreme response by a path integration

Offshore crane non-linear stochastic response: novel design and extreme response by a path integration
Offshore crane non-linear stochastic response: novel design and extreme response by a path integration
In this paper, the novel pendulum tuned mass damper model has been suggested as a potential practical engineering modification to an existing offshore crane setup. A number of potential numerical singularities have been circumvented and substantial numerical model accuracy has been reached. Main application of this study would be extreme value statistics, in case of e.g. extreme weather conditions causing collision between vessel and payload. Next, extreme statistics of random vibrations has been studied in this paper for a suggested pendulum tuned mass damper model under white noise excitation. Restoring force has been modelled as the elastic non-linear, and numerical comparison has been performed with the linearised restoring force model case to see the force non-linearity effect on the vessel payload response statistics. The statistics of non-linear case has been studied by applying the path integration method, based on the Markov property of the coupled dynamic system.
Offshore crane, path integration, FFT, non-linear restoring force, extreme value statistics, pendulum tuned mass dampers
1744-5302
Gaidai, Oleg
258bf054-5f95-44e8-8e7a-ff2b18cee3a5
Yurchenko, Daniil
51a2896b-281e-4977-bb72-5f96e891fbf8
Ye, Renchuan
84628350-0154-4165-bd27-37c652a97202
Xu, Xiaosen
84b7da06-c5bf-4878-96bc-d095a7a4f8f2
Wang, Junlei
7afcea11-129b-4a82-b572-95b443c2c643
Gaidai, Oleg
258bf054-5f95-44e8-8e7a-ff2b18cee3a5
Yurchenko, Daniil
51a2896b-281e-4977-bb72-5f96e891fbf8
Ye, Renchuan
84628350-0154-4165-bd27-37c652a97202
Xu, Xiaosen
84b7da06-c5bf-4878-96bc-d095a7a4f8f2
Wang, Junlei
7afcea11-129b-4a82-b572-95b443c2c643

Gaidai, Oleg, Yurchenko, Daniil, Ye, Renchuan, Xu, Xiaosen and Wang, Junlei (2021) Offshore crane non-linear stochastic response: novel design and extreme response by a path integration. Ships and Offshore Structures. (doi:10.1080/17445302.2021.1912455).

Record type: Article

Abstract

In this paper, the novel pendulum tuned mass damper model has been suggested as a potential practical engineering modification to an existing offshore crane setup. A number of potential numerical singularities have been circumvented and substantial numerical model accuracy has been reached. Main application of this study would be extreme value statistics, in case of e.g. extreme weather conditions causing collision between vessel and payload. Next, extreme statistics of random vibrations has been studied in this paper for a suggested pendulum tuned mass damper model under white noise excitation. Restoring force has been modelled as the elastic non-linear, and numerical comparison has been performed with the linearised restoring force model case to see the force non-linearity effect on the vessel payload response statistics. The statistics of non-linear case has been studied by applying the path integration method, based on the Markov property of the coupled dynamic system.

Text
17445302.2021 (1) - Version of Record
Restricted to Repository staff only
Request a copy
Text
Pendulum_OG_DY
Restricted to Registered users only
Download (519kB)
Request a copy

More information

Accepted/In Press date: 24 March 2021
e-pub ahead of print date: 20 April 2021
Keywords: Offshore crane, path integration, FFT, non-linear restoring force, extreme value statistics, pendulum tuned mass dampers

Identifiers

Local EPrints ID: 468125
URI: http://eprints.soton.ac.uk/id/eprint/468125
ISSN: 1744-5302
PURE UUID: f13b4fbb-a7a6-43d0-94d9-22f39c426acb
ORCID for Daniil Yurchenko: ORCID iD orcid.org/0000-0002-4989-3634

Catalogue record

Date deposited: 03 Aug 2022 16:31
Last modified: 17 Mar 2024 04:11

Export record

Altmetrics

Contributors

Author: Oleg Gaidai
Author: Daniil Yurchenko ORCID iD
Author: Renchuan Ye
Author: Xiaosen Xu
Author: Junlei Wang

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.

×