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Structures and Safety Reliability

A Joint Probability Model for Environmental Parameters

[+] Author and Article Information
Luís Volnei Sudati Sagrilo1

Department of Civil Engineering, COPPE/UFRJ Centro de Tecnologia, Sala B100, Ilha do Fundão, Rio de Janeiro, 21945-970, Brazilsagrilo@coc.ufrj.br

Edison Castro Prates de Lima

Department of Civil Engineering, COPPE/UFRJ Centro de Tecnologia, Sala B100, Ilha do Fundão, Rio de Janeiro, 21945-970, Braziledison@coc.ufrj.br

Arnaldo Papaleo

 CENPES/PETROBRAS, Av. Brigadeiro Trompovsky s/n, Ilha do Fundão, Rio de Janeiro, 21945-970, Brazilpapaleo@petrobras.com.br

1

Corresponding author.

J. Offshore Mech. Arct. Eng 133(3), 031605 (Apr 01, 2011) (7 pages) doi:10.1115/1.4001962 History: Received January 07, 2010; Revised May 21, 2010; Published April 01, 2011; Online April 01, 2011

Joint probabilistic models (JPMs) for the environmental parameters such as wave, wind, and current are nowadays of paramount importance in order to perform the reliability analysis of marine structures. These JPMs are also essential for long-term statistics-based design of offshore structures and to perform dynamic response analysis of floating units that are strongly dependent on the directionality of the environmental actions such as turret-moored floating, production, storage, and offloading vessels (FPSOs). Recently, some JPMs have been proposed in literature to represent the joint statistics of a reduced number of environmental parameters. However, it is a difficult task to obtain practical and reliable models to express the complete statistical dependence among the environmental parameters intensities and their correspondent directions. This paper presents a methodology, based on the Nataf transformation, to create a JPM of wave, wind, and current environmental parameters taking into account, also, the statistical correlation between intensities and directions. The proposed model considers ten short-term environmental variables: the significant wave height, peak period, and direction of the sea waves, the significant wave height, peak period, and direction of the swell waves, the amplitude and direction of the 1 h wind velocity, and, finally, the amplitude and direction of the surface current velocity. The statistical dependence between them is modeled using concepts of linear-linear, linear-circular, and circular-circular variables correlation. Some results of the proposed JPM methodology are presented based on simultaneous environmental data gathered in an offshore Brazil location.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 1

Marginal probability density function for wind sea significant height

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Figure 2

Marginal probability density function for wind sea peak period

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Figure 10

Marginal probability density function for wind direction (on the circle)

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Figure 12

Nataf-based joint distribution of wind sea parameters: significant wave height and spectral peak period

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Figure 13

Empirical joint distribution of wind sea significant wave height and wind velocity

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Figure 14

Nataf-based joint distribution of wind sea significant wave height and wind velocity

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Figure 11

Empirical joint distribution of wind sea parameters: significant wave height and spectral peak period

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Figure 9

Marginal probability density function for current direction (on the circle)

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Figure 8

Marginal probability density function for swell direction (on the circle)

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Figure 7

Marginal probability density function for wind sea direction (on the circle)

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Figure 6

Marginal probability density function for wind velocity

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Figure 5

Marginal probability density function for current velocity

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Figure 4

Marginal probability density function for swell peak period

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Figure 3

Marginal probability function for swell significant height

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