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.

Efficient Derivation of the Probability Distribution of the Extreme Values of Offshore Structural Response: Comparison of Three Different Methods

2013 ◽  
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 ◽  
Time Simulation ◽  
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. To this end, the conventional (Monte Carlo) time 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 responses (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. In this paper, three different versions of a more efficient time simulation technique (ETS) are compared by exposing a test structure to sea states of different intensity. The three different versions of the ETS technique take advantage of the good correlation between extreme responses and their corresponding surface elevation extreme values, or quasi-static and dynamic linear extreme responses.

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.

An Efficient Monte Carlo Simulation Technique for Derivation of the Probability Distribution of the Extreme Values of Offshore Structural Response

2010 ◽  
Author(s):  
M. K. Abu Husain ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
Simulation Technique ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Monte Carlo Simulation Technique ◽  
Ocean Environment

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. In this paper, a more efficient version of the time simulation technique (ETS) is introduced to derive the probability distribution of response extreme values from a much smaller sample of simulated extreme values.

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.

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.

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.

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.

Short-Term Distribution of the Extreme Values of Offshore Structural Response by Modified Finite-Memory Nonlinear System Modeling

2013 ◽  
Author(s):  
N. I. Mohd Zaki ◽  
M. K. Abu Husain ◽  
Y. Wang ◽  
G. Najafian
Keyword(s):  
Nonlinear System ◽  
Probability Distribution ◽  
Extreme Values ◽  
Offshore Structures ◽  
Random Wave ◽  
Horizontal Distance ◽  
Wave Loading ◽  
Offshore Structure ◽  
Short Term ◽  
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’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. 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). Previous investigation shows that the developed FMNS models perform better for high Hs values and their performance for low Hs value is not particularly good. In this paper, the modified version of FMNS models is referred to as MFMNS models is discussed. The improvement of MFMNS model is simply by dividing the structure into two zones (Zones 1 and 2) so that the horizontal distance between the nodes in each zone is relatively small compared to the wavelength. The modified version of MFMNS is used to determine the short-term probability distribution of the response extreme values with great efficiency.

scholarly journals Derivation of the Probability Distribution of Extreme Values of Offshore Structural Response by Efficient Time Simulation Method

2013 ◽  
Vol 7 (1) ◽  
pp. 261-272 ◽  
Author(s):  
M.K. Abu Husain ◽  
N.I. Mohd Zaki ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Simulation Method ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loading ◽  
Sampling Variability ◽  
Economical Design ◽  
Ocean Environment

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 num-ber 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 cor-relation between the extreme values of surface elevation and their corresponding response extreme values. The method has proved to be very efficient for high-intensity sea states; however, the correlation and hence the efficiency and accura-cy of the technique reduces for sea states of lower intensity. In this paper, a more efficient version of the ETS technique is introduced which takes advantage of the correlation between the extreme values of the nonlinear response and their corre-sponding linear response values.

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.

Sign in / Sign up

Export Citation Format

Share Document