Airgap Statistics for a Tension Leg Platform

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Oleg Gaidai ◽  
Arvid Naess ◽  
Carl Trygve Stansberg
Keyword(s):  
Safety Issue ◽  
Extreme Value Statistics ◽  
Critical Parameters ◽  
Offshore Platforms ◽  
Random Waves ◽  
Tension Leg Platform ◽  
Wave Impact ◽  
Large Wave ◽  
Wave Basin ◽  
Extreme Response

The paper discusses a method for estimating extreme value statistics of the airgap for floating offshore platforms subjected to random seas. It is an adaptation of a recently developed method, which is based on the mean upcrossing rate (MUR) function for univariate time series combined with an optimization procedure that allows prediction at extreme response levels by extrapolation. Extensive model tests were performed in a large wave basin for a tension leg platform (TLP) operating in the Norwegian Sea. Among several critical parameters, the airgap was measured at a number of locations under the platform deck. The wave in deck impact is a critical safety issue with respect to the deck damage and occurrence of extreme tether tensions. The authors have utilized experimental data to look at critical airgaps under the deck in random waves. Conclusions are drawn about extreme airgap statistics, and consequently about the wave impact probability in severe seas.

Airgap Statistics for a Tension Leg Platform

2012 ◽  
Author(s):  
Oleg Gaidai ◽  
Arvid Naess ◽  
Carl Trygve Stansberg
Keyword(s):  
Safety Issue ◽  
Extreme Value Statistics ◽  
Critical Parameters ◽  
Offshore Platforms ◽  
Random Waves ◽  
Tension Leg Platform ◽  
Wave Impact ◽  
Large Wave ◽  
Norwegian Sea ◽  
Wave Basin

The paper discusses a method for estimating extreme value statistics of the airgap for floating offshore platforms subjected to random events. Extensive model tests were performed in a large wave basin for a TLP (Tension Leg Platform) operating in the Norwegian Sea. Among several critical parameters, the airgap was measured at a number of locations under the platform deck. The wave in deck impact is a critical safety issue with respect to the deck damage and occurrence of extreme tether tensions. The authors have utilized experimental data to look at critical airgaps under the deck in random waves. Conclusions are drawn about extreme airgap statistics, and consequently about the wave impact probability in severe seas. This paper can be seen as continuing the efforts in the challenging study of the airgap issue, [2, 6–10].

Statistics of Extreme Events in Airgap Measurements

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
A. Naess ◽  
C. T. Stansberg ◽  
O. Gaidai ◽  
R. J. Baarholm
Keyword(s):  
Extreme Values ◽  
Optimization Procedure ◽  
Extreme Value Statistics ◽  
Alternative Methods ◽  
Scale Model ◽  
Random Waves ◽  
Mean Values ◽  
Fitting Procedure ◽  
Wave Basin ◽  
Extreme Response

The paper presents a study of the extreme value statistics related to airgap measurements on a scale model of a semisubmersible platform subjected to random waves in a wave basin. Relative wave elevation records corresponding to totally 24 h storm duration are considered, made up by 8×3 h realizations. The focus is on a comparison of two alternative methods for the prediction of extreme values from finite recordings at two different locations at the platform. One is a standard method used in the wave basin, making use of a Weibull-tail fitting procedure. The other is a novel method based on the level upcrossing function combined with an optimization procedure that allows prediction at extreme response levels. Similar results are obtained in the mean values by the two methods, while the latter shows less variability in the predictions from single 3 h records.

Statistics of Extreme Events in Airgap Measurements

2008 ◽  
Author(s):  
A. Naess ◽  
C. T. Stansberg ◽  
O. Gaidai ◽  
R. J. Baarholm
Keyword(s):  
Extreme Values ◽  
Optimization Procedure ◽  
Extreme Value Statistics ◽  
Alternative Methods ◽  
Scale Model ◽  
Random Waves ◽  
Mean Values ◽  
Fitting Procedure ◽  
Wave Basin ◽  
Extreme Response

The paper presents a study of the extreme value statistics related to airgap measurements on a scale model of a semisubmersible platform subjected to random waves in a wave basin. Relative wave elevation records corresponding to totally 24 hours storm duration are considered, made up by 8 × 3-hours realizations. The focus is on a comparison of two alternative methods for the prediction of extreme values from finite recordings at two different locations at the platform. One is a standard method used in the wave basin, making use of a Weibull-tail fitting procedure. The other is a novel method based upon the level up-crossing function combined with an optimization procedure that allows prediction at extreme response levels. Similar results are obtained in the mean values by the two methods, while the latter shows less variability in the predictions from single 3-hours records.

Extreme Response Statistics of Fixed Offshore Structures Subjected to Ringing Loads

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Oleg Gaidai ◽  
Jørgen Krokstad
Keyword(s):  
Structural Response ◽  
Offshore Structures ◽  
Wave Impact ◽  
Structural Support ◽  
Random Seas ◽  
Wave Basin ◽  
Extreme Response ◽  
Time Histories ◽  
Short Time ◽  
Diffraction Effects

This paper describes an efficient Monte Carlo based method for prediction of extreme response statistics of fixed offshore structures subjected to random seas. The nonlinear structural response known as “ringing” is studied, which is caused by the wave impact force on structural support units. Common challenge for design of such structures is a sound estimate of the hydrodynamic load including diffraction effects. The aim of the work was to develop specific methods which make it possible to extract the necessary information about the extreme response from relatively short time histories. The method proposed in this paper opens up the possibility to predict simply and efficiently both short-term and long-term extreme response statistics. The results presented are based on extensive simulation results for the large fixed platform operating on the Norwegian continental shelf. Structural response time histories, measured in MARINTEK (MT) wave basin lab, were used to validate numerical results.

Prediction of Extreme Tether Tension for a TLP

2009 ◽  
Author(s):  
A. Naess ◽  
C. T. Stansberg ◽  
O. Batsevych
Keyword(s):  
Time Series ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Extreme Value Statistics ◽  
Alternative Methods ◽  
Scale Model ◽  
Statistical Dependence ◽  
Wave Basin ◽  
Extreme Response

The paper presents a study of the extreme value statistics related to measurements on a scale model of a large tension leg platform (TLP) subjected to random waves in a wave basin. Extensive model tests were carried out in three irregular sea states. Time series of the motion responses and tether tension were recorded for a total of 18 three hour tests (full scale). In this paper we discuss the statistics of the measured tether tension. The focus is on a comparison of two alternative methods for the prediction of extreme tether tension from finite time series records. One method is based on expressing the extreme value distribution in terms of the average upcrossing rate. The other is a novel method that can account for statistical dependence in the recorded time series by utilizing a cascade of conditioning approximations. Both methods rely on introducing a specific parametric form for the tail part of the extreme value distribution. This is combined with an optimization procedure to determine the parameters involved, which allows prediction of various extreme response levels.

Green Water Flow on a Fixed Model Structure in a Large Wave Basin Under Random Waves

2018 ◽  
Author(s):  
Wei-Liang Chuang ◽  
Kuang-An Chang ◽  
Richard Mercier
Keyword(s):  
Velocity Distribution ◽  
Flow Behavior ◽  
Green Water ◽  
Wave Crest ◽  
Breaking Wave ◽  
Model Structure ◽  
Random Waves ◽  
Large Wave ◽  
Geometry Model ◽  
Wave Basin

Green water generated by random waves on a fixed, simplified geometry model structure was measured in a large wave basin. The velocity field of the flow that is aerated and highly turbulent was quantified using the bubble image velocimetry (BIV) technique. BIV utilizes shadow textures created by air-water interfaces as tracers in backlit images recorded by a high speed camera. The tracers in consecutive images are then cross-correlated to obtain the corresponding two-dimensional velocities. Random waves were generated by the JONSWAP spectrum with a significant wave height close to the freeboard. An image-based triggering method was employed to detect the green water events and trigger image acquisition. A total of 179 green water events were collected and categorized into three different types, based on the flow behavior. That includes the collapse of overtopping wave, fall of bulk water, and breaking wave crest. Statistical distributions of maximum green water velocities under random waves were developed, while the lognormal distribution was found as the best fit. By modeling the green water as a dam break flow, the Ritter solution was found to be able to capture the horizontal velocity distribution for the random green water events. A prediction equation for the green water velocity distribution under random waves was also obtained.

Prediction of Extreme Tether Tension for a TLP by the AUR and ACER Methods

2011 ◽  
Vol 134 (2) ◽  
Author(s):  
A. Naess ◽  
C. T. Stansberg ◽  
O. Batsevych
Keyword(s):  
Time Series ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Extreme Value Statistics ◽  
Alternative Methods ◽  
Scale Model ◽  
Statistical Dependence ◽  
Wave Basin ◽  
Extreme Response

The paper presents a study of the extreme value statistics related to measurements on a scale model of a large tension leg platform (TLP) subjected to random waves in a wave basin. Extensive model tests were carried out in three irregular sea states. Time series of the motion responses and tether tension were recorded for a total of 18 three hour tests (full scale). In this paper we discuss the statistics of the measured tether tension. The focus is on a comparison of two alternative methods for the prediction of extreme tether tension from finite time series records. One method is based on expressing the extreme value distribution in terms of the average upcrossing rate (AUR). The other is a novel method that can account for statistical dependence in the recorded time series by utilizing a cascade of conditioning approximations obtained by defining the average conditional exceedance rates (ACER). Both methods rely on introducing a specific parametric form for the tail part of the extreme value distribution. This is combined with an optimization procedure to determine the parameters involved, which allows prediction of various extreme response levels.

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