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.

Extreme Response Prediction for Fixed Offshore Structures by Monte Carlo Time Simulation Technique

2016 ◽  
Author(s):  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
M. B. Johari ◽  
G. Najafian
Keyword(s):  
Monte Carlo ◽  
Statistical Properties ◽  
Simulation Technique ◽  
Random Wave ◽  
Wave Loading ◽  
Offshore Structure ◽  
Sampling Variability ◽  
Time Simulation ◽  
Wide Range ◽  
Extreme Response

For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structure is essential for safe and economical design of these structures. Many different techniques have been introduced for evaluation of statistical properties of response. In each case, sea-states are characterised by an appropriate water surface elevation spectrum, covering a wide range of frequencies. In reality, the most versatile and reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the time domain simulation technique. To this end, conventional time simulation (CTS) procedure or commonly called Monte Carlo time simulation method is the best known technique for predicting the short-term and long-term statistical properties of the response of an offshore structure to random wave loading due to its capability of accounting for various nonlinearities. However, this technique requires very long simulations in order to reduce the sampling variability to acceptable levels. In this paper, the effect of sampling variability of a Monte Carlo technique is investigated.

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.

Efficient Derivation of the Probability Distribution of Extreme Responses due to Random Wave Loading From the Probability Distribution of Extreme Surface Elevations

2013 ◽  
Author(s):  
H. Mallahzadeh ◽  
Y. Wang ◽  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Extreme Surface ◽  
Ocean Environment ◽  
Non Gaussian ◽  
Extreme Responses

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. Due to nonlinearity of the drag component of Morison’s 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 probability distribution of extreme responses are not available. To this end, the conventional Monte Carlo time simulation technique is frequently used for predicting the probability distribution of the extreme responses. However, this technique suffers from excessive sampling variability and hence a large number of simulated response records are required to reduce the sampling variability to acceptable levels. This paper takes advantage of the correlation between extreme responses and their corresponding extreme surface elevations to derive the probability distribution of the extreme responses accurately and efficiently, i.e. without the need for extensive simulations.

A New Method of Moments for Reducing the Sampling Variability of Estimated Values of Probability Distribution Parameters

2007 ◽  
Author(s):  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Method Of Moments ◽  
Probability Model ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Minimum Requirement ◽  
Distribution Parameters ◽  
Non Gaussian

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of their response to wave loading is the minimum requirement for probabilistic analysis of these structures. Even if the structural system can be assumed to be linear, due to nonlinearity of the wave loading mechanism and also due to the intermittency of wave loading on members in the splash zone, the response is often non-Gaussian. The method of moments is frequently used to determine the parameters of an adopted probability model from a simulated or measured record of response. However, when higher order moments (e.g. 3rd or 4th order moments) are required for estimation of the distribution parameters, the estimated values show considerable scatter due to high sampling variability. In this paper, a more efficient form of the method of moments is introduced, which will lead to more accurate estimates of the distribution parameters by reducing their sampling variability.

Finite-Memory Nonlinear System Modelling of Offshore Structures

2008 ◽  
Author(s):  
G. Najafian ◽  
N. I. Mohd Zaki
Keyword(s):  
Nonlinear System ◽  
Probability Distribution ◽  
Extreme Values ◽  
Offshore Structures ◽  
Random Wave ◽  
System Modelling ◽  
Wave Loading ◽  
Offshore Structure ◽  
Extreme Response ◽  
Finite Memory

Offshore structures are exposed to random wave loading in the ocean environment, and hence the 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 their extreme response probability distributions are not available. However, according to a recent paper, in the absence of current, the response of an offshore structure exposed to Morison wave loading, can be approximated by the response of an equivalent finite-memory nonlinear system (FMNS). These models can then be used, with great efficiency, to determine the probability distribution of response extreme values. In this paper, the progress made so far in extending these FMNS models to account for the effect of current on response is discussed.

Prediction of Extreme Values of Offshore Structural Response by an Efficient Time Simulation Technique

2014 ◽  
Author(s):  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
Simulation Technique ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Monte Carlo Simulation Technique ◽  
Extreme Response

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. Due to nonlinearity of the drag component of Morison’s 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 probability distribution of extreme responses are not available. To this end, the conventional Monte Carlo simulation technique (CTS) is frequently used for predicting the probability distribution of the extreme values of response. However, this technique suffers from excessive sampling variability and hence a large number of simulated extreme response values (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. In this paper, the efficiency of an alternative technique in comparison with the conventional simulation technique is investigated.

Long-Term Probability Distribution of Extreme Offshore Structural Response via an Efficient Time Simulation Method

2013 ◽  
Author(s):  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
L. Lambert ◽  
Y. Wang ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Simulation Method ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Extreme Response

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. To this end, the conventional simulation technique (CTS) is frequently used for predicting the probability distribution of the extreme values of response. However, this technique suffers from excessive sampling variability and hence a large number of simulated response extreme values (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. A more efficient method (ETS) was recently introduced which takes advantage of the correlation between the extreme values of linear response and their corresponding response extreme values. The method has proved to be very efficient for both low and high-intensity sea states. In this paper, further development of this technique, which leads to more accurate estimates of the long term probability distribution of the extreme response, is reported.

Polynomial Approximation of Morison Wave Loading

1997 ◽  
Vol 119 (1) ◽  
pp. 30-36 ◽  
Author(s):  
V. Bouyssy ◽  
R. Rackwitz
Keyword(s):  
Polynomial Approximation ◽  
Order Approximation ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loads ◽  
Wave Loading ◽  
Gaussian Models ◽  
Response Variance ◽  
Non Gaussian ◽  
Fifth Order

For offshore structures with slender elements, the modeling of random wave loads by the Morison equation yields an equation of motion which has no analytical solution for response moments except in a few limiting cases. If polynomial approximations of the Morison drag loads are introduced, some procedures are available to obtain the stationary moments of the approximate response. If the response process is fitted by non-Gaussian models such as proposed by Winterstein (1988), the first four statistical moments of the response are necessary. The paper investigates how many terms should be included in the polynomial approximation of the Morison drag loading to accurately estimate the first four response moments. It is shown that a cubic approximation of the drag loading is necessary to accurately predict the response variance for any excitation. For the fit of the first four response moments, at least a fifth-order approximation appears necessary.

Efficient Estimation of Offshore Structural Response Based on Threshold Upcrossing Rates

2013 ◽  
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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