Extreme-response analysis of jack-up platforms

1989 ◽  
Vol 2 (3-5) ◽  
pp. 305-334 ◽  
Author(s):  
H. Kjeøy ◽  
N.G. Bøe ◽  
T. Hysing
Keyword(s):  
Response Analysis ◽  
Extreme Response ◽  
Jack Up

Probabilistic Models Applicable to the Short-Term Extreme Response Analysis of Jack-Up Platforms

2003 ◽  
Vol 125 (4) ◽  
pp. 249-263 ◽  
Author(s):  
M. J. Cassidy ◽  
G. T. Houlsby ◽  
R. Eatock Taylor
Keyword(s):  
Probabilistic Models ◽  
Probability Distributions ◽  
Response Analysis ◽  
Wave Loading ◽  
Physical Processes ◽  
Short Term ◽  
Analysis Techniques ◽  
Extreme Response ◽  
Increasing Demand ◽  
Jack Up

There is a steadily increasing demand for the use of jack-up units in deeper water and harsher conditions. Confidence in their use in these environments requires jack-up analysis techniques to reflect accurately the physical processes occurring. However, nearly all analyses are deterministic in nature and do not account for the inherent variability in governing parameters and models. In this paper, probabilistic models are used to develop an understanding of the response behavior of jack-ups, with particular emphasis placed on the extreme deck displacement due to a short-term event. Variables within the structural, foundation and wave loading models are assigned probability distributions and their influence on the response statistics is quantified using a response surface methodology.

Nonlinear Ship Loads: Stochastic Models for Extreme Response

1998 ◽  
Vol 42 (01) ◽  
pp. 46-55
Author(s):  
Rune Torhaug ◽  
Steven R. Winterstein ◽  
Arne Braathen
Keyword(s):  
Time Domain ◽  
Stochastic Models ◽  
Stochastic Analysis ◽  
Short Wave ◽  
Response Analysis ◽  
Correct Result ◽  
Sea State ◽  
Extreme Response ◽  
Computational Resources ◽  
The Cost

In this study we focus on stochastic analysis methods for selective simulations, and we consider the extreme midspan moment of a fast-moving ship subjected to random Gaussian waves. We concentrate on analysis within a stationary sea state and our purpose is to accurately estimate hourly maximum ship response (compared with the correct result per hour) within a sea state with as little computational resources as possible. We consider how the use of a limited number of short simulations with "critical wave episodes" (short wave segments which are likely candidates to produce extreme response in the simulated hour-long history) reduces the cost of nonlinear time-domain ship response analysis.

Extreme Response Predictions for Jack-Up Units in Second Order Stochastic Waves by FORM

2007 ◽  
Author(s):  
Jo̸rgen Juncher Jensen
Keyword(s):  
Second Order ◽  
Sea State ◽  
First Order ◽  
Reliability Method ◽  
Extreme Response ◽  
Stochastic Waves ◽  
Short Time ◽  
Wave Induced ◽  
Jack Up ◽  
Operational Time

The aim of the present paper is to advocate for a very effective stochastic procedure, based on the First Order Reliability Method (FORM), for extreme value predictions related to wave induced loads. All kinds of non-linearities can be included, as the procedure makes use of short time-domain simulations of the response in question. The procedure will be illustrated with a jack-up rig where second order stochastic waves are included in the analysis. The result is the probability of overturning as function of sea state and operational time.

Joint Distribution of Environmental Condition at Five European Offshore Sites for Design of Combined Wind and Wave Energy Devices

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Lin Li ◽  
Zhen Gao ◽  
Torgeir Moan
Keyword(s):  
Renewable Energy ◽  
Wave Energy ◽  
Environmental Data ◽  
Offshore Wind ◽  
Response Analysis ◽  
Energy Devices ◽  
Joint Distributions ◽  
Wave Parameters ◽  
Extreme Response

The design of wind turbines requires information about joint data for wind and wave conditions. Moreover, combining offshore wind and wave energy facilities is a potential way to reduce the cost of offshore wind farms. To design combined offshore renewable energy concepts, it is important to choose sites where both wind and wave energy resources are substantial. This paper deals with joint environmental data for five European offshore sites which serve as basis for the analysis and comparison of combined renewable energy concepts developed in the EU FP7 project—MARINA Platform. The five sites cover both shallow and deep water, with three sites facing the Atlantic Ocean and two sites in the North Sea. The long-term joint distributions of wind and wave parameters are presented for these sites. Simultaneous hourly mean wind and wave hindcast data from 2001 to 2010 are used as a database. The joint distributions are modeled by fitting analytical distributions to the hindcast data. The long-term joint distributions can be used to estimate the wind and wave power output from each combined concept and to estimate the fatigue lifetime of the structure. The marginal distributions of wind and wave parameters are also provided. Based on the joint distributions, contour surfaces are established for combined wind and wave parameters for which the probability of exceedance corresponds to a return period of 50 years. The design points on the 50-year contour surfaces are suggested for extreme response analysis of combined concepts.

The Influence of Alternative Wave Loading and Support Modeling Assumptions on Jack-Up Rig Response Extremes

1996 ◽  
Vol 118 (2) ◽  
pp. 109-114 ◽  
Author(s):  
L. Manuel ◽  
C. A. Cornell
Keyword(s):  
Nonlinear Models ◽  
Random Wave ◽  
Force Model ◽  
Wave Loading ◽  
Force Modeling ◽  
Hydrodynamic Damping ◽  
Extreme Response ◽  
The Absolute ◽  
Non Gaussian ◽  
Jack Up

A study is conducted of the response of a jack-up rig to random wave loading. Steady current and wind load effects are also included. The effects of varying the relative motion assumption (in the Morison equation) and of varying the bottom fixity assumptions are investigated. One “fixity” model employs nonlinear soil springs. Time domain simulations are performed using linearized as well as fully nonlinear models for the jack-up rig. Comparisons of response statistics are made for two seastates. Hydrodynamic damping causes the rms response to be lower in the relative Morison case. The absence of this source of damping in the absolute Morison force model gives rise to larger resonance/dynamic effects—this tends to “Gaussianize” the response. Hence, the relative Morison model leads to stronger non-Gaussian behavior than the absolute Morison model. This is reflected in moments as well as extremes. The different support conditions studied are seen to significantly influence extreme response estimates. In general, stiffer models predict smaller rms response estimates, but also exhibit stronger non-Gaussian behavior. The choice of the Morison force modeling assumption (i.e., the relative versus the absolute motion formulation) is seen to have at least a secondary role in influencing response moments and extremes.

Long-Term Extreme Response of a Vessel Rolling in Random Seas

2016 ◽  
Author(s):  
Wei Chai ◽  
Arvid Naess ◽  
Bernt J. Leira
Keyword(s):  
Nonlinear Effects ◽  
Roll Motion ◽  
Response Analysis ◽  
Linear Filter ◽  
Beam Seas ◽  
Random Seas ◽  
Extreme Response ◽  
High Level ◽  
Nonlinear Roll Motion

In this paper, the long-term extreme response of a vessel rolling in random beam seas is addressed. The long-term response analysis is based on the upcrossing rates of the roll motion under different sea states. However, the nonlinear effects associated with the restoring and damping terms have a significant influence on the high-level response, assessing the corresponding statistics, such as the upcrossing rate, with low probability levels is difficult and time-consuming. In this work, the Markov theory is introduced in order to tackle this problem. Specifically, the random roll excitation moment is approximated as a filtered white noise process by applying a linear filter technique and an efficient four-dimensional (4D) path integration (PI) procedure is applied in order to calculate the response statistics. The long-term analysis of nonlinear roll motion in random seas that takes into considerations of the response statistics obtained by the 4D PI method as well as the variation of the sea states could be a valuable reference for ship stability research.

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