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  • TowEADmn21

    Rights statement: This is the author’s version of a work that was accepted for publication in Ocean Engineering. 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 Ocean Engineering, 238, 2021 DOI: 10.1016/j.oceaneng.2021.109642

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Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows

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Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows. / Towe, R.; Zanini, E.; Randell, D. et al.
In: Ocean Engineering, Vol. 238, 109642, 15.10.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Towe R, Zanini E, Randell D, Feld G, Jonathan P. Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows. Ocean Engineering. 2021 Oct 15;238:109642. Epub 2021 Sept 3. doi: 10.1016/j.oceaneng.2021.109642

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Bibtex

@article{adb7c58c6f834f099bd06f79b3bd6247,
title = "Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows",
abstract = "Methods of computational statistics allow efficient estimation of extreme ocean environments, and facilitate optimal operational decision making. We describe estimation of extreme quantiles of total water level and related quantities from a non-stationary hierarchical model for ocean storms. The model incorporates a directional–seasonal extreme value model for occurrences of storm peak significant wave height, a conditional directional model for within-storm evolution of sea states relative to storm peak, a conditional model for the maximum crest within a sea state, and models for total water level. Importance sampling is used for efficient computation of marginal total water level characteristics. We use the model to estimate an optimal un-manning procedure for a notional North Sea offshore structure in severe conditions. ",
keywords = "Covariate, Extreme, Hierarchical statistical model, Importance sampling, Return value, Un-manning, Weather window, Computational efficiency, Decision making, Hierarchical systems, Ocean currents, Offshore oil well production, Offshore structures, Water levels, Covariates, Distributional property, Efficient estimation, Hierarchical description, Sea state, Storms",
author = "R. Towe and E. Zanini and D. Randell and G. Feld and P. Jonathan",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Ocean Engineering. 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 Ocean Engineering, 238, 2021 DOI: 10.1016/j.oceaneng.2021.109642",
year = "2021",
month = oct,
day = "15",
doi = "10.1016/j.oceaneng.2021.109642",
language = "English",
volume = "238",
journal = "Ocean Engineering",
issn = "0029-8018",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows

AU - Towe, R.

AU - Zanini, E.

AU - Randell, D.

AU - Feld, G.

AU - Jonathan, P.

N1 - This is the author’s version of a work that was accepted for publication in Ocean Engineering. 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 Ocean Engineering, 238, 2021 DOI: 10.1016/j.oceaneng.2021.109642

PY - 2021/10/15

Y1 - 2021/10/15

N2 - Methods of computational statistics allow efficient estimation of extreme ocean environments, and facilitate optimal operational decision making. We describe estimation of extreme quantiles of total water level and related quantities from a non-stationary hierarchical model for ocean storms. The model incorporates a directional–seasonal extreme value model for occurrences of storm peak significant wave height, a conditional directional model for within-storm evolution of sea states relative to storm peak, a conditional model for the maximum crest within a sea state, and models for total water level. Importance sampling is used for efficient computation of marginal total water level characteristics. We use the model to estimate an optimal un-manning procedure for a notional North Sea offshore structure in severe conditions.

AB - Methods of computational statistics allow efficient estimation of extreme ocean environments, and facilitate optimal operational decision making. We describe estimation of extreme quantiles of total water level and related quantities from a non-stationary hierarchical model for ocean storms. The model incorporates a directional–seasonal extreme value model for occurrences of storm peak significant wave height, a conditional directional model for within-storm evolution of sea states relative to storm peak, a conditional model for the maximum crest within a sea state, and models for total water level. Importance sampling is used for efficient computation of marginal total water level characteristics. We use the model to estimate an optimal un-manning procedure for a notional North Sea offshore structure in severe conditions.

KW - Covariate

KW - Extreme

KW - Hierarchical statistical model

KW - Importance sampling

KW - Return value

KW - Un-manning

KW - Weather window

KW - Computational efficiency

KW - Decision making

KW - Hierarchical systems

KW - Ocean currents

KW - Offshore oil well production

KW - Offshore structures

KW - Water levels

KW - Covariates

KW - Distributional property

KW - Efficient estimation

KW - Hierarchical description

KW - Sea state

KW - Storms

U2 - 10.1016/j.oceaneng.2021.109642

DO - 10.1016/j.oceaneng.2021.109642

M3 - Journal article

VL - 238

JO - Ocean Engineering

JF - Ocean Engineering

SN - 0029-8018

M1 - 109642

ER -