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    Rights statement: This is the author’s version of a work that was accepted for publication in Marine Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Marine Structures, 69, 2020 DOI: 10.1016/j.marstruc.2019.102680

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Comparing different contour methods with response-based methods for extreme ship response analysis

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Comparing different contour methods with response-based methods for extreme ship response analysis. / Vanem, E.; Guo, B.; Ross, E. et al.
In: Marine Structures, Vol. 69, 102680, 31.01.2020.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Vanem E, Guo B, Ross E, Jonathan P. Comparing different contour methods with response-based methods for extreme ship response analysis. Marine Structures. 2020 Jan 31;69:102680. Epub 2019 Sept 27. doi: 10.1016/j.marstruc.2019.102680

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Bibtex

@article{60373844b9b8464dafac54af052bc83e,
title = "Comparing different contour methods with response-based methods for extreme ship response analysis",
abstract = "Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours. Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses. In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long time-series of sea-state parameters such as significant wave height and wave period are used to construct N-year environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.",
keywords = "Environmental contours, Environmental loads, Extreme ship response analysis, Marine structures, Ocean environment, Response-based methods, Structural reliability, Bending moments, Learning systems, Ocean currents, Ocean structures, Reliability analysis, Tankers (ships), Time series, Value engineering, Response-based method, Ship response, Structural analysis",
author = "E. Vanem and B. Guo and E. Ross and P. Jonathan",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Marine Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Marine Structures, 69, 2020 DOI: 10.1016/j.marstruc.2019.102680",
year = "2020",
month = jan,
day = "31",
doi = "10.1016/j.marstruc.2019.102680",
language = "English",
volume = "69",
journal = "Marine Structures",
issn = "0951-8339",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Comparing different contour methods with response-based methods for extreme ship response analysis

AU - Vanem, E.

AU - Guo, B.

AU - Ross, E.

AU - Jonathan, P.

N1 - This is the author’s version of a work that was accepted for publication in Marine Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Marine Structures, 69, 2020 DOI: 10.1016/j.marstruc.2019.102680

PY - 2020/1/31

Y1 - 2020/1/31

N2 - Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours. Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses. In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long time-series of sea-state parameters such as significant wave height and wave period are used to construct N-year environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.

AB - Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours. Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses. In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long time-series of sea-state parameters such as significant wave height and wave period are used to construct N-year environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.

KW - Environmental contours

KW - Environmental loads

KW - Extreme ship response analysis

KW - Marine structures

KW - Ocean environment

KW - Response-based methods

KW - Structural reliability

KW - Bending moments

KW - Learning systems

KW - Ocean currents

KW - Ocean structures

KW - Reliability analysis

KW - Tankers (ships)

KW - Time series

KW - Value engineering

KW - Response-based method

KW - Ship response

KW - Structural analysis

U2 - 10.1016/j.marstruc.2019.102680

DO - 10.1016/j.marstruc.2019.102680

M3 - Journal article

VL - 69

JO - Marine Structures

JF - Marine Structures

SN - 0951-8339

M1 - 102680

ER -