Non-Normally Distributed Extreme ValueStatistics in Offshore Design
Extreme value behavior of a moored semi-submersible vessel is investigated. There is a need for alternative methods other than the Rayleigh peak model when investigating non-Gaussian processes. In this context the Rayleigh peak model will generally underestimate extreme values. Four methods are inve...
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ndltd-UPSALLA1-oai-DiVA.org-kth-1575022014-12-11T04:48:35ZNon-Normally Distributed Extreme ValueStatistics in Offshore DesignengGharanfoli, DanielKTH, Marina system2013Extreme value behavior of a moored semi-submersible vessel is investigated. There is a need for alternative methods other than the Rayleigh peak model when investigating non-Gaussian processes. In this context the Rayleigh peak model will generally underestimate extreme values. Four methods are investigated in this study with data from 1000 seeds. They are; construction of an empirical cumulative distribution function, mean of maximas, a LF/WF spectral partition and peak distribution tail tting. In turn six peak distributions are investigated. It was found that global motions are more sensitive than point accelerations to estimation errors, and the more accurate methods should be applied to global motions. A tted Weibull peak distribution proved to be the most conservative for both MPM value and 90 th percentile estimations. It was also found that a mean of 10 maxima was a good estimation of a MPM value. Longer seeds than three hours are recommended in order to include higher maxima and lower minima. Further comparison studies are recommended. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157502TRITA-AVE, 1651-7660 ; 2013:46application/pdfinfo:eu-repo/semantics/openAccess |
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NDLTD |
language |
English |
format |
Others
|
sources |
NDLTD |
description |
Extreme value behavior of a moored semi-submersible vessel is investigated. There is a need for alternative methods other than the Rayleigh peak model when investigating non-Gaussian processes. In this context the Rayleigh peak model will generally underestimate extreme values. Four methods are investigated in this study with data from 1000 seeds. They are; construction of an empirical cumulative distribution function, mean of maximas, a LF/WF spectral partition and peak distribution tail tting. In turn six peak distributions are investigated. It was found that global motions are more sensitive than point accelerations to estimation errors, and the more accurate methods should be applied to global motions. A tted Weibull peak distribution proved to be the most conservative for both MPM value and 90 th percentile estimations. It was also found that a mean of 10 maxima was a good estimation of a MPM value. Longer seeds than three hours are recommended in order to include higher maxima and lower minima. Further comparison studies are recommended. |
author |
Gharanfoli, Daniel |
spellingShingle |
Gharanfoli, Daniel Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
author_facet |
Gharanfoli, Daniel |
author_sort |
Gharanfoli, Daniel |
title |
Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
title_short |
Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
title_full |
Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
title_fullStr |
Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
title_full_unstemmed |
Non-Normally Distributed Extreme ValueStatistics in Offshore Design |
title_sort |
non-normally distributed extreme valuestatistics in offshore design |
publisher |
KTH, Marina system |
publishDate |
2013 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157502 |
work_keys_str_mv |
AT gharanfolidaniel nonnormallydistributedextremevaluestatisticsinoffshoredesign |
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1716726676186988544 |