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.

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.

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.

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.

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.

Probabilistic Modelling of Extreme Offshore Structural Response due to Random Wave Loading

2013 ◽  
Author(s):  
Y. Wang ◽  
H. Mallahzadeh ◽  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
G. Najafian
Keyword(s):  
Extreme Values ◽  
Structural Response ◽  
Offshore Structures ◽  
Random Wave ◽  
Wave Loading ◽  
Empirical Distributions ◽  
Generalized Pareto ◽  
Economical Design ◽  
Ocean Environment ◽  
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. This paper investigates the suitability of the Gumbel, the Generalized Extreme Value (GEV), and the Generalized Pareto (GP) distributions for modelling of extreme responses by comparing them with empirical distributions derived from extensive Monte Carlo time simulations. It will be shown that none of these distributions can model the extreme values adequately but that a mixed distribution consisting of both GEV and GP distributions seems to be capable of modelling the extreme responses with very good accuracy.

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.

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.

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