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

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.

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 Offshore Structural Response Extreme Values by Modified Finite-Memory Nonlinear System Modeling

2016 ◽  
Author(s):  
N. I. Mohd Zaki ◽  
M. K. Abu Husain ◽  
N. A. Mukhlas ◽  
G. Najafian
Keyword(s):  
Nonlinear System ◽  
Probability Distribution ◽  
Extreme Values ◽  
Offshore Structures ◽  
Horizontal Distance ◽  
Wave Loading ◽  
Offshore Structure ◽  
Short Term ◽  
Finite Memory ◽  
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 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 has shown that the developed FMNS models perform better for high Hs values and that their performance for low Hs value is not particularly good. In this paper, MFMNS technique, a modified version of FMNS models is discussed. The improvement in MFMNS model is simply achieved 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 wavelengths. It is shown that MFMNS technique can be used to determine the short-term probability distribution of the extreme responses accurately with great efficiency.

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.

Finite-Memory Nonlinear System Modelling of Offshore Structural Response Accounting for Extreme Values Residues

2013 ◽  
Author(s):  
N. I. Mohd Zaki ◽  
M. K. Abu Husain ◽  
H. Mallahzadeh ◽  
G. Najafian
Keyword(s):  
Nonlinear System ◽  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
System Modelling ◽  
Wave Loading ◽  
Offshore Structure ◽  
Finite Memory ◽  
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 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. Monte Carlo time simulation technique can be used to derive the probabilistic properties of offshore structural response, but the procedure is computationally demanding. Finite-memory nonlinear system (FMNS) modeling of the response of an offshore structure exposed to Morison’s wave loading has been used to reduce the computational effort, but the predictions are not always of high accuracy. In this paper, further development of this technique, which leads to more accurate estimates of the probability distribution of the extreme responses, is reported.

Finite-Memory Nonlinear System Modelling of Offshore Structural Response Accounting for Extreme Values Residues

2012 ◽  
Author(s):  
H. Mallahzadeh ◽  
N. I. Mohd Zaki ◽  
M. K. Abu Husain ◽  
G. Najafian
Keyword(s):  
Nonlinear System ◽  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
System Modelling ◽  
Wave Loading ◽  
Offshore Structure ◽  
Finite Memory ◽  
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 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. Monte Carlo time simulation technique can be used to derive the probabilistic properties of offshore structural response, but the procedure is computationally demanding. Finite-memory nonlinear system (FMNS) modeling of the response of an offshore structure exposed to Morison’s wave loading has been used to reduce the computational effort, but the predictions are not always of high accuracy. In this paper, further development of this technique, which leads to more accurate estimates of the probability distribution of the extreme responses, is reported.

The Accuracy of the MFMNS and FMNS Models in Predicting Long-Term Distribution of the Extreme Values of Offshore Structural Response

2014 ◽  
Author(s):  
N. I. Mohd Zaki ◽  
M. K. Abu Husain ◽  
G. Najafian
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
Computational Effort ◽  
Random Wave ◽  
Wave Loading ◽  
Offshore Structure ◽  
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 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. Monte Carlo time simulation technique can be used to derive the probabilistic properties of offshore structural response, but the procedure is computationally demanding. Finite-memory nonlinear system (FMNS) modeling of the response of an offshore structure exposed to Morison’s wave loading has been introduced to reduce the computational effort, but the predictions are not very good for low intensity sea states. To overcome this deficiency, a modified version of the FMNS technique (referred to as MFMNS modeling) was proposed which improves the accuracy, but is computationally less efficient than the FMNS modeling. In this study, the accuracy of the 100-year responses derived from the long-term probability distribution of extreme responses from FMNS and MFMNS methods 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.

Long-Term Analysis Applied to Mooring Systems Design

2020 ◽  
Author(s):  
Pedro Seabra ◽  
Luis Volnei Sudati Sagrilo ◽  
Paulo Esperança
Keyword(s):  
Time Domain ◽  
Environmental Conditions ◽  
Systems Design ◽  
Environmental Data ◽  
Coupled Analysis ◽  
Offshore Structure ◽  
Short Term ◽  
Extreme Response ◽  
Term Analysis

Abstract Nowadays, the most used methodology to predict line tensions is the short-term coupled analysis, where the mooring system responses are obtained by a time-domain analysis for only some specific design combinations of extreme environmental conditions. This mooring analysis demands certain considerations and it is not the best way to obtain the offshore structure responses. The advances in both quantity and quality of collected environmental data and the increase of the computers processing power has enabled to consider the approach of more accurate long-term methodologies for mooring systems design. This paper proposes a numerical/computational procedure to obtain the extreme loads (ULS) acting on offshore platforms’ mooring lines. The work is based on the methodology of long-term analysis, employing a 10-yr long short-term environmental dataset of 3-h sea-states, where each short-term environmental condition is composed of the simultaneously observed environmental parameters of wave (sea and swell), wind and current. The methodology is applied to the analysis of three different mooring systems: a) spread-moored FPSO, b) Semi-Submersible platform and c) turret-moored FPSO. The Bootstrap approach is employed in order to take into account the statistical uncertainty associated to the estimated long-term most probable extreme response due to the limited number of short-term environmental conditions. The work was carried out using Dynasim software [1] to generate the time domain tension time series, which were later post-processed by using computational codes developed with Python software. Longer short-term numerical simulations lengths than the short-term period (3-h) have been investigated in order to understand the influence of this parameter on the final extreme long-term top tensions.

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.

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.

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