Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique

For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structu...

Full description

Saved in:
Bibliographic Details
Main Authors: Abu Husain, M. K., Mohd. Zaki, N. I., Johari, M. B., Najafian, G.
Format: Conference or Workshop Item
Published: American Society of Mechanical Engineers (ASME) 2016
Subjects:
Online Access:http://eprints.utm.my/id/eprint/73646/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996569829&doi=10.1115%2fOMAE2016-54200&partnerID=40&md5=ca836c31f424cd9d5d3b4d656fbf26b6
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.73646
record_format eprints
spelling my.utm.736462017-11-28T06:50:01Z http://eprints.utm.my/id/eprint/73646/ Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique Abu Husain, M. K. Mohd. Zaki, N. I. Johari, M. B. Najafian, G. T Technology (General) For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structure is essential for safe and economical design of these structures. Many different techniques have been introduced for evaluation of statistical properties of response. In each case, sea-states are characterised by an appropriate water surface elevation spectrum, covering a wide range of frequencies. In reality, the most versatile and reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the time domain simulation technique. To this end, conventional time simulation (CTS) procedure or commonly called Monte Carlo time simulation method is the best known technique for predicting the short-term and long-term statistical properties of the response of an offshore structure to random wave loading due to its capability of accounting for various nonlinearities. However, this technique requires very long simulations in order to reduce the sampling variability to acceptable levels. In this paper, the effect of sampling variability of a Monte Carlo technique is investigated. American Society of Mechanical Engineers (ASME) 2016 Conference or Workshop Item PeerReviewed Abu Husain, M. K. and Mohd. Zaki, N. I. and Johari, M. B. and Najafian, G. (2016) Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique. In: ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2016, 19-24 June 2016, Busan, South Korea. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996569829&doi=10.1115%2fOMAE2016-54200&partnerID=40&md5=ca836c31f424cd9d5d3b4d656fbf26b6
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Abu Husain, M. K.
Mohd. Zaki, N. I.
Johari, M. B.
Najafian, G.
Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
description For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structure is essential for safe and economical design of these structures. Many different techniques have been introduced for evaluation of statistical properties of response. In each case, sea-states are characterised by an appropriate water surface elevation spectrum, covering a wide range of frequencies. In reality, the most versatile and reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the time domain simulation technique. To this end, conventional time simulation (CTS) procedure or commonly called Monte Carlo time simulation method is the best known technique for predicting the short-term and long-term statistical properties of the response of an offshore structure to random wave loading due to its capability of accounting for various nonlinearities. However, this technique requires very long simulations in order to reduce the sampling variability to acceptable levels. In this paper, the effect of sampling variability of a Monte Carlo technique is investigated.
format Conference or Workshop Item
author Abu Husain, M. K.
Mohd. Zaki, N. I.
Johari, M. B.
Najafian, G.
author_facet Abu Husain, M. K.
Mohd. Zaki, N. I.
Johari, M. B.
Najafian, G.
author_sort Abu Husain, M. K.
title Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
title_short Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
title_full Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
title_fullStr Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
title_full_unstemmed Extreme response prediction for fixed offshore structures by Monte Carlo time simulation technique
title_sort extreme response prediction for fixed offshore structures by monte carlo time simulation technique
publisher American Society of Mechanical Engineers (ASME)
publishDate 2016
url http://eprints.utm.my/id/eprint/73646/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996569829&doi=10.1115%2fOMAE2016-54200&partnerID=40&md5=ca836c31f424cd9d5d3b4d656fbf26b6
_version_ 1643656709451808768
score 13.211869