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

M. J. Cassidy; G. T. Houlsby; R. Eatock Taylor

doi:10.1115/1.1600470

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

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.1600470 ◽

2003 ◽

Vol 125 (4) ◽

pp. 249-263 ◽

Cited By ~ 1

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.

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Extreme-response analysis of jack-up platforms

Marine Structures ◽

10.1016/0951-8339(89)90038-5 ◽

1989 ◽

Vol 2 (3-5) ◽

pp. 305-334 ◽

Cited By ~ 5

Author(s):

H. Kjeøy ◽

N.G. Bøe ◽

T. Hysing

Keyword(s):

Response Analysis ◽

Extreme Response ◽

Jack Up

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

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.2828818 ◽

1996 ◽

Vol 118 (2) ◽

pp. 109-114 ◽

Cited By ~ 3

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.

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Short-term extreme response analysis of a jacket supporting an offshore wind turbine

Wind Energy ◽

10.1002/we.1561 ◽

2012 ◽

Vol 17 (1) ◽

pp. 87-104 ◽

Cited By ~ 28

Author(s):

Nilanjan Saha ◽

Zhen Gao ◽

Torgeir Moan ◽

Arvid Naess

Keyword(s):

Wind Turbine ◽

Offshore Wind ◽

Offshore Wind Turbine ◽

Response Analysis ◽

Short Term ◽

Extreme Response

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Long-Term Extreme Response Analysis of Marine Structures Using Inverse SORM

Volume 3A: Structures, Safety and Reliability ◽

10.1115/omae2017-61409 ◽

2017 ◽

Cited By ~ 2

Author(s):

Finn-Idar G. Giske ◽

Bernt Johan Leira ◽

Ole Øiseth

Keyword(s):

Structural Reliability ◽

New Method ◽

Response Analysis ◽

Marine Structures ◽

Short Term ◽

Reliability Method ◽

Extreme Response ◽

Improved Accuracy ◽

Term Response

In this paper the first order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second order reliability method (SORM) is used to improve the accuracy of the approximation. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve improved accuracy for large return periods, yet keep the number of required short-term response analyses within acceptable levels.

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Long-term extreme response analysis for semi-submersible platform mooring systems

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment ◽

10.1177/1475090220976515 ◽

2020 ◽

pp. 147509022097651

Author(s):

Yuliang Zhao ◽

Sheng Dong

Keyword(s):

Environmental Data ◽

Distribution Model ◽

Response Analysis ◽

Accurate Assessment ◽

Response Distribution ◽

Short Term ◽

Floating Structure ◽

Extreme Response ◽

Term Analysis

The accurate assessment of long-term extreme responses of floating-structure mooring system designs is important because of small failure probabilities caused by long-term and complex ocean conditions. The most accurate assessment would involve considering all conceivable sea states in which each sea state is regarded as a stochastic process and performing nonlinear time-domain numerical simulations of mooring systems to estimate the extreme response from a long-term analysis. This procedure would be computationally intensive because of the numerous short-term sea states involved. Here, a more feasible approach to evaluate the long-term extreme response is presented through immediate integration combined with Monte Carlo simulations. A parameter fitting procedure of the short-term extreme response distribution under irregular wave conditions is employed to solve the long-term response integration. Case studies were conducted on a semi-submersible platform using environmental data measurements of the Gulf of Mexico and a joint distribution model of the environmental parameters was considered. This approach was observed to be effective and the results were compared with those of traditional methodologies (univariate extreme value design and environmental contour methods). The differences were reflected using a reliability analysis of mooring lines, which indicated that the design standards must be stricter when using long-term analysis.

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Long-Term Distribution of the Extreme Values of Offshore Structural Response by Finite-Memory Nonlinear System Modelling

Volume 2: Structures, Safety and Reliability ◽

10.1115/omae2011-49460 ◽

2011 ◽

Author(s):

N. I. Mohd Zaki ◽

G. Najafian

Keyword(s):

Nonlinear System ◽

Probability Distribution ◽

Extreme Values ◽

System Modelling ◽

Wave Loading ◽

Offshore Structure ◽

Short Term ◽

Extreme Response ◽

Finite Memory

Offshore structures are exposed to random wave loading in the ocean environment and hence the long-term probability distribution of the extreme values of their response to wave loading is of great value in the design of these structures. Due to nonlinearity of the drag component of Morison wave loading and also due to intermittency of wave loading on members in the splash zone, the response is often non-Gaussian; therefore, simple techniques for derivation of the extreme response probability distributions are not available. However, it has recently been shown that the short-term response of an offshore structure exposed to Morison wave loading can be approximated by the response of an equivalent finite-memory nonlinear system (FMNS). In this paper, the approximate FMNS models are used to determine both the short-term and the long-term probability distribution of the response extreme values with great efficiency.

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Long-Term Extreme Response Analysis of Marine Structures Using Inverse SORM

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.4039718 ◽

2018 ◽

Vol 140 (5) ◽

Cited By ~ 3

Author(s):

Finn-Idar G. Giske ◽

Bernt Johan Leira ◽

Ole Øiseth

Keyword(s):

Structural Reliability ◽

New Method ◽

Response Analysis ◽

Marine Structures ◽

Short Term ◽

Reliability Method ◽

Extreme Response ◽

Improved Accuracy ◽

Term Response

In this paper, the first-order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second-order reliability method (SORM) is used to improve the accuracy of the approximation, resulting in an inverse SORM (ISORM) approach. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve significantly improved accuracy, yet keep the number of required short-term response analyses within acceptable levels.

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Efficient Estimation of Offshore Structural Response Based on Threshold Upcrossing Rates

Volume 2A: Structures, Safety and Reliability ◽

10.1115/omae2013-10385 ◽

2013 ◽

Cited By ~ 1

Author(s):

Luke A. Lambert ◽

G. Najafian ◽

J. E. Cooper ◽

M. Abu Husain ◽

N. I. Mohd Zaki

Keyword(s):

Structural Model ◽

Probability Distributions ◽

Structural Response ◽

Response Probability ◽

Simulation Method ◽

Efficient Estimation ◽

Random Wave ◽

Wave Loading ◽

Time Simulation ◽

Extreme Response

Reliable estimation of offshore structural response due to random wave loading is essential for ensuring safe and economical designs. However, the conventional Monte Carlo time simulation method requires the simulation of an extremely large number of response records in order to derive extreme response probability distributions with acceptably low sampling variability. The Efficient Threshold Upcrossing (ETU) method, presented in this paper, enables rapid calculation of these probability distributions by using information about threshold upcrossing rates in conjunction with an Efficient Time Simulation (ETS) technique. Extreme response probability distributions from this novel technique are compared with those from the conventional and the ETS methods using a simple structural model exposed to Morison wave loading. It is shown that the method allows a very efficient calculation of response statistics.

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