System Identification of a Six-Legged Semisubmersible Subjected to Wave Loads through Frequency Domain Analysis

2013 ◽  
Vol 373-375 ◽  
pp. 770-784
Author(s):  
Guo Zheng Yew ◽  
M.S. Liew ◽  
Mohd Shahir Liew ◽  
Cheng Yee Ng
Keyword(s):  
System Identification ◽  
Transfer Function ◽  
Transfer Functions ◽  
Structural Response ◽  
Offshore Structures ◽  
Frequency Domain Analysis ◽  
Random Wave ◽  
Wave Loads ◽  
Sea State ◽  
Wave Heights

Sea state conditions such as wind, wave and current vary in different ocean waters. Two similar offshore structures installed in two different ocean regions will yield different responses. Determining the transfer function of the structure is a system identification exercise that yields the structural response and behaviour given any sea state condition. The transfer function can be determined using available measured sea state data and structural response data. In this paper, a six-legged semisubmersible physical model is developed to a scale of 1:100 and is tested in a wave tank to measure its responses due to simulated random wave loads. The transfer functions of the semisubmersible model are then determined using the measured responses and the measured wave heights.

scholarly journals Comparison of Extreme Surface Elevation for Linear and Nonlinear Random Wave Theory for Offshore Structures

2018 ◽  
Vol 203 ◽  
pp. 01021
Author(s):  
Nurul 'Azizah Mukhlas ◽  
Noor Irza Mohd Zaki ◽  
Mohd Khairi Abu Husain ◽  
Gholamhossein Najafian
Keyword(s):  
Probabilistic Approach ◽  
Wave Theory ◽  
Offshore Structures ◽  
Random Wave ◽  
Linear Wave ◽  
Random Waves ◽  
Sea State ◽  
Higher Order Terms ◽  
Structural Responses ◽  
Nonlinear Random Wave

For offshore structural design, the load due to wind-generated random waves is usually the most important source of loading. While these structures can be designed by exposing them to extreme regular waves (100-year design wave), it is much more satisfactory to use a probabilistic approach to account for the inherent randomness of the wave loading. This method allows the statistical properties of the loads and structural responses to be determined, which is essential for the risk-based assessment of these structures. It has been recognized that the simplest wave generation is by using linear random wave theory. However, there is some limitation on its application as some of the nonlinearities cannot be explained when higher order terms are excluded and lead to underestimating of 100-year wave height. In this paper, the contribution of nonlinearities based on the second order wave theory was considered and being tested at a variety of sea state condition from low, moderate to high. Hence, it was proven that the contribution of nonlinearities gives significant impact the prediction of 100-year wave's design as it provides a higher prediction compared to linear wave theory.

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.

Nonlinear System Identification in Offshore Structural Reliability

1995 ◽  
Vol 117 (3) ◽  
pp. 171-177 ◽  
Author(s):  
P. D. Spanos ◽  
R. Lu
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Structural Reliability ◽  
Transfer Functions ◽  
Nonlinear System Identification ◽  
Simulated Data ◽  
Wave Force ◽  
Ocean Waves ◽  
Offshore Structures ◽  
Analysis And Design

Nonlinear forces acting on offshore structures are examined from a system identification perspective. The nonlinearities are induced by ocean waves and may become significant in many situations. They are not necessarily in the form of Morison’s equation. Various wave force models are examined. The force function is either decomposed into a set of base functions or it is expanded in terms of the wave and structural kinematics. The resulting nonlinear system is decomposed into a number of parallel no-memory nonlinear systems, each followed by a finite-memory linear system. A conditioning procedure is applied to decouple these linear sub-systems; a frequency domain technique involving autospectra and cross-spectra is employed to identify the linear transfer functions. The structural properties and the force transfer parameters are determined with the aid of the coherence functions. The method is verified using simulated data. It provides a versatile and noniterative approach for dealing with nonlinear interaction problems encountered in offshore structural analysis and design.

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 Fatigue Life of Shallow Water Offshore Platforms Using Spectral Fatigue Analysis Method

2010 ◽  
Author(s):  
Qin Feng ◽  
Richard Large
Keyword(s):  
Shallow Water ◽  
Transfer Functions ◽  
Structural Response ◽  
Response Spectra ◽  
Fatigue Analysis ◽  
Offshore Platforms ◽  
Analysis Method ◽  
Technical Approach ◽  
Sea State ◽  
Platform Design

Spectral fatigue analysis approach is highly recommended for fixed offshore platform design and reassessment by API. This method is a computationally efficient method, being able to handle the random nature of environmental ocean wave conditions during calculating wave loads on the offshore platforms and subsequent structural responses. However, its fundamental theory is based on the assumption of linearity of both structural system and wave loading mechanism. Although this method is critically appropriate to be applied in offshore platform design and fatigue assessment for deep water scenarios where wave and force nonlinearities are not very severe, it has still been widely utilized for the design and assessment of shallow water platforms in offshore industry without carefully considering possible errors caused by strong nonlinear factors between ocean waves and forces. The source giving rise to the errors is because of the difficulties in choosing suitably correct wave heights for a series of wave periods required for producing transfer functions between sea state spectra and structural response spectra. Therefore, the studies to justify the possible errors of the spectral fatigue analysis method for shallow water platforms have been provoked. This paper presents the results of the studies of investigating the errors from currently existing spectral fatigue analysis method. A new technical approach that can reduce the errors in the spectral fatigue analysis of shallow water platforms is introduced. The proposed technical approach is mainly focused on producing realistic transfer functions between sea state spectra and structural response spectra, which can reasonably reflect the individually local sea state data by using wave height-period joint probability density function. Hence the fatigue damage and life at the tubular joints of offshore platforms can be more precisely predicted. The spectral fatigue analysis of a practical shallow water jacket platform in the recent platform design project has been performed using the proposed approach and the results are discussed.

Estimating Iceberg-Wave Companion Loads Using Probabilistic Methods

2015 ◽  
Author(s):  
Mark Fuglem ◽  
Paul Stuckey ◽  
Somchat Suwan
Keyword(s):  
Hydrodynamic Pressure ◽  
Offshore Structures ◽  
Probabilistic Methods ◽  
Wave Loads ◽  
Wave Loading ◽  
Wave Load ◽  
Sea State ◽  
Load Factors ◽  
Induced Velocity ◽  
The Impact

Many challenges arise when designing offshore structures for iceberg loads in arctic and subarctic regions. To help the designer, the ISO 19906:2010 standard provides guidance for the calculation of design ice loads using both deterministic and probabilistic approaches. In determining design loads for different environmental factors, both principal and companion actions must be taken into account; an example is iceberg actions and companion wave actions. ISO 19906 allows the designer to calculate the companion wave action as a specified fraction (combination factor) of the extreme level (EL) design wave load. Alternatively, the designer can calculate appropriate companion wave loads explicitly. A methodology has been developed at C-CORE in which representative iceberg actions are determined using a software package, the Iceberg Load Software (ILS). This is a probabilistic tool which uses Monte Carlo simulation to obtain a distribution of global impact forces based on the expected range of iceberg and environmental conditions that a structure would likely encounter. The software provides a reasonably accurate representation of the iceberg loading situation, following the provisions of ISO 19906:2010, without introducing unnecessary conservatism in the design load. In the software, the influence of waves on the iceberg actions are considered, but companion wave loads must be calculated and added externally to the software, The software accounts for the probability of different sea state conditions and the influence of the sea state on the probability and severity of iceberg impact, given the correlations between the sea state, iceberg management effectiveness and iceberg drift and wave-induced velocity. The additional hydrodynamic pressure due to the wave during the period of the impact; is not considered. This wave loading will be complicated by the influence that the presence the iceberg and structure have on the local sea state. In this paper, brief descriptions are provided of background studies on companion wave loading and the application of companion load factors in ISO 19906. The companion load factors allow the designer to apply the design wave load, which is calculated for situations with no iceberg present, to the case of iceberg impacts. In this study, a methodology is presented for determining companion wave loads based on the distribution of sea states expected during an iceberg impact. These sea states are significantly less severe than that associated with the design wave load as iceberg impacts are rare events. The companion wave loads are determined without accounting for the influence of the iceberg; this is thought to be quite conservative. An example application of the methodology is presented for a hypothetical platform located on the Grand Banks, off the east coast of Newfoundland. Iceberg actions, wave actions and combined iceberg-wave actions are estimated using the described methodology. Comparisons are provided for the resulting companion loads and those based on ISO 19906:2010 companion load factors applied to the extreme level wave load.

Identifying a Transfer Function From a Frequency Response

2007 ◽  
Author(s):  
Manuel Duarte Ortigueira ◽  
Duarte Vale´rio ◽  
Jose´ Sa´ da Costa
Keyword(s):  
System Identification ◽  
Transfer Function ◽  
Frequency Response ◽  
Transfer Functions ◽  
Sea Waves ◽  
Low Frequencies ◽  
Wide Range ◽  
Simulation Results ◽  
New Formulation ◽  
Pseudo Inverse

In this paper, the classic Levy identification method is reviewed and reformulated using a complex representation. This new formulation is able to solve the well known bias of the classic method at low frequencies. The formulation is generic, addressing both integer order and fractional order transfer functions. A new algorithm based on a stacked matrix and its pseudo-inverse is proposed to accommodate the data over a wide range of frequencies. Several simulation results are presented, together with a real system identification. This system is the Archimedes Wave Swing, a prototype of a device to convert the energy of sea waves into electricity.

scholarly journals The Wave Heights Distribution of Random Wave Based on Ocean Basin

Kapal ◽  
2020 ◽  
Vol 17 (3) ◽  
pp. 114-122
Author(s):  
Nurman Firdaus ◽  
Baharuddin Ali ◽  
Mochammad Nasir ◽  
M Muryadin
Keyword(s):  
Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ocean Basin ◽  
Distribution Model ◽  
Exceedance Probability ◽  
Random Wave ◽  
Theoretical Spectrum ◽  
Sea State ◽  
Wave Heights

The wave height parameter in ocean waves is one of the important information for a marine structure design. The present paper investigates the results of wave heights distribution from laboratory-generated for single sea state. Data of the random wave time series collected at the ocean basin are analyzed using the wave spectrum and compared with the theoretical spectrum in this study. The random wave data is varied with four sea states consisting of sea states 3, 4, 5 and 6 obtained from laboratory measurements. The parameter conditions of generated sea waves are represented by a value of significant wave height and wave peak period in the range of sea states. The individual wave heights data in each sea state are presented in the form of exceedance probability distribution and the predictions using a linear model. This study aims to estimate the wave heights distribution using the Rayleigh and Weibull distribution model. Furthermore, the accuracy of the wave heights distribution data's prediction results in each sea state has been compared and examined for both models. The applied linear models indicate similar and reasonable estimations on the observed data trends.

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.

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