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research-article

PROBABILISTIC ANALYSIS OF EXTREME RISER RESPONSES FOR A WEATHER-VANING FPSO IN TROPICAL CYCLONES

[+] Author and Article Information
Curtis Armstrong

University of Tasmania - The Australian Maritime College, Maritime Way, Newnham, Tasmania, Australia 7248
curtis.armstrong@utas.edu.au

Yuriy Drobyshevski

WorleyParsons Ltd (INTECSEA Pty Ltd), 600 Murray St, West Perth, Australia 6005
yuriy.drobyshevski@intecsea.com

Christopher Chin

University of Tasmania - The Australian Maritime College, Maritime Way, Newnham, Tasmania, Australia 7248
c.chin@utas.edu.au

Irene Penesis

University of Tasmania - The Australian Maritime College, Maritime Way, Newnham, Tasmania, Australia 7248
i.penesis@utas.edu.au

1Corresponding author.

ASME doi:10.1115/1.4041069 History: Received March 08, 2018; Revised July 26, 2018

Abstract

The probability distributions of extreme responses of a flexible riser connected to a weather-vaning FPSO are developed and investigated numerically for two tropical cyclones. Statistical properties of riser responses provide the foundation for Response Based Analysis (RBA), a comprehensive approach for the prediction of extreme responses and design metocean conditions of offshore systems. The storm-based probabilistic analysis is applied to responses of flexible risers with the objective to develop their distributions in a storm and to determine their most probable maximum values. An asymptotic form of the response distribution in a storm is formulated, which can be used in the random event, method of Tromans and Vandersohuren [22]. The methodology is illustrated by two case studies for an FPSO in cyclonic storms at a location offshore Australia. Time domain simulations are employed to predict the FPSO motions, critical riser responses and their probability distributions. It is shown that the maximum storm responses can be reproduced by governing "equivalent" metocean intervals with increased percentiles or inflated durations. Effects of different environmental excitation upon the risers and their impact on the statistical properties of responses are discussed, providing important insights for extension towards a multi-storm RBA approach. The study also discusses issues with practices such as the analysis for a 3-hour design event and presents observations on the variability of several types of responses, which reveal their environmental sensitivities.

Copyright (c) 2018 by ASME
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