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Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation

An analysis of the structure based on linear wave analysis is suggested as a preliminary analysis to assess the overall integrity of the structure. In situations where the results of the preliminary analysis are found to be extreme with several critical conditions, a more detailed structural analysi...

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Main Authors: Mukhlas, Nurul Azizah, Mohd. Zaki, Noor Irza, Abu Husain, Mohd. Khairi, Syed Ahmad, Sayyid Zainal Abidin, Najafian, Gholamhossein
Format: Article
Published: Taylor and Francis Group 2022
Subjects:
Q Science (General)
T Technology (General)
Online Access:http://eprints.utm.my/104112/
http://dx.doi.org/10.1080/17445302.2021.1898127
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spelling my.utm.1041122024-01-17T01:12:55Z http://eprints.utm.my/104112/ Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation Mukhlas, Nurul Azizah Mohd. Zaki, Noor Irza Abu Husain, Mohd. Khairi Syed Ahmad, Sayyid Zainal Abidin Najafian, Gholamhossein Q Science (General) T Technology (General) An analysis of the structure based on linear wave analysis is suggested as a preliminary analysis to assess the overall integrity of the structure. In situations where the results of the preliminary analysis are found to be extreme with several critical conditions, a more detailed structural analysis is suggested to conduct a nonlinear wave. Recently, an efficient model has been developed to test the extreme offshore structural response based on the nonlinear wave analysis using the time-domain approach. It is the derivation of non-Gaussian stochastic offshore structural response using the finite-memory nonlinear system, known as (Formula presented.). This paper focuses on the validation on the performance of the (Formula presented.) method in the analysis of short-term 100-year of extreme offshore structural responses. Providing good accuracy, the (Formula presented.) method offered a more efficient approach for an optimum and economical structural analysis. Taylor and Francis Group 2022 Article PeerReviewed Mukhlas, Nurul Azizah and Mohd. Zaki, Noor Irza and Abu Husain, Mohd. Khairi and Syed Ahmad, Sayyid Zainal Abidin and Najafian, Gholamhossein (2022) Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation. Ships and Offshore Structures, 17 (6). pp. 1209-1223. ISSN 1744-5302 http://dx.doi.org/10.1080/17445302.2021.1898127 DOI:10.1080/17445302.2021.1898127
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 Q Science (General)
T Technology (General)
spellingShingle Q Science (General)
T Technology (General)
Mukhlas, Nurul Azizah
Mohd. Zaki, Noor Irza
Abu Husain, Mohd. Khairi
Syed Ahmad, Sayyid Zainal Abidin
Najafian, Gholamhossein
Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
description An analysis of the structure based on linear wave analysis is suggested as a preliminary analysis to assess the overall integrity of the structure. In situations where the results of the preliminary analysis are found to be extreme with several critical conditions, a more detailed structural analysis is suggested to conduct a nonlinear wave. Recently, an efficient model has been developed to test the extreme offshore structural response based on the nonlinear wave analysis using the time-domain approach. It is the derivation of non-Gaussian stochastic offshore structural response using the finite-memory nonlinear system, known as (Formula presented.). This paper focuses on the validation on the performance of the (Formula presented.) method in the analysis of short-term 100-year of extreme offshore structural responses. Providing good accuracy, the (Formula presented.) method offered a more efficient approach for an optimum and economical structural analysis.
format Article
author Mukhlas, Nurul Azizah
Mohd. Zaki, Noor Irza
Abu Husain, Mohd. Khairi
Syed Ahmad, Sayyid Zainal Abidin
Najafian, Gholamhossein
author_facet Mukhlas, Nurul Azizah
Mohd. Zaki, Noor Irza
Abu Husain, Mohd. Khairi
Syed Ahmad, Sayyid Zainal Abidin
Najafian, Gholamhossein
author_sort Mukhlas, Nurul Azizah
title Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
title_short Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
title_full Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
title_fullStr Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
title_full_unstemmed Efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation
title_sort efficient derivation of extreme non-gaussian stochastic structural response using finite-memory nonlinear system. part 2: model validation
publisher Taylor and Francis Group
publishDate 2022
url http://eprints.utm.my/104112/
http://dx.doi.org/10.1080/17445302.2021.1898127
_version_ 1789424380760031232
score 13.211869

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