Bivariate Extreme Value Statistics of Offshore Jacket Support Stresses in Bohai Bay

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Zhang Jian ◽  
Oleg Gaidai ◽  
Junliang Gao
Keyword(s):  
Offshore Structures ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Bohai Bay ◽  
Wave Load ◽  
Offshore Structure ◽  
Response Dynamics ◽  
Extreme Response ◽  
Hydrodynamic Wave

This paper presents a generic Monte Carlo-based approach for bivariate extreme response prediction for fixed offshore structures, particularly jacket type. The bivariate analysis of extremes is often poorly understood and generally not adequately considered in most practical measurements/situations; that is why it is important to utilize the recently developed bivariate average conditional exceedance rate (ACER) method. According to the current literature study, there is not yet a direct application of the bivariate ACER method to coupled offshore jacket stresses. This study aims at being first to apply bivariate ACER method to jacket critical stresses, aiming at contributing to safety and reliability studies for a wide class of fixed offshore structures. An operating jacket located in the Bohai bay was taken as an example to demonstrate the proposed methodology. Satellite measured global wave statistics was used to obtain realistic wave scatter diagram in the jacket location area. Second-order wave load effects were taken into account, while simulating jacket structural response. An accurate finite element ANSYS model was used to model jacket response dynamics, subject to nonlinear hydrodynamic wave and sea current loads. Offshore structure design values are often based on univariate statistical analysis, while actually multivariate statistics is more appropriate for modeling the whole structure. This paper studies extreme stresses that are simultaneously measured/simulated at two different jacket locations. Due to less than full correlation between stresses in different critical jacket locations, application of the multivariate (or at least bivariate) extreme value theory is of practical engineering interest.

Statistics of Extreme Wind Speeds and Wave Heights by the Bivariate ACER Method

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Arvid Naess ◽  
Oleh Karpa
Keyword(s):  
Time Series ◽  
Extreme Value Distribution ◽  
Offshore Structures ◽  
Accurate Estimate ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
Extreme Value Statistics ◽  
Wind Speeds ◽  
Wave Heights

In the reliability engineering and design of offshore structures, probabilistic approaches are frequently adopted. They require the estimation of extreme quantiles of oceanographic data based on the statistical information. Due to strong correlation between such random variables as, e.g., wave heights and wind speeds (WS), application of the multivariate, or bivariate in the simplest case, extreme value theory is sometimes necessary. The paper focuses on the extension of the average conditional exceedance rate (ACER) method for prediction of extreme value statistics to the case of bivariate time series. Using the ACER method, it is possible to provide an accurate estimate of the extreme value distribution of a univariate time series. This is obtained by introducing a cascade of conditioning approximations to the true extreme value distribution. When it has been ascertained that this cascade has converged, an estimate of the extreme value distribution has been obtained. In this paper, it will be shown how the univariate ACER method can be extended in a natural way to also cover the case of bivariate data. Application of the bivariate ACER method will be demonstrated for measured coupled WS and wave height data.

Statistics of Extreme Wind Speeds and Wave Heights by the Bivariate ACER Method

2013 ◽  
Author(s):  
Arvid Naess ◽  
Oleh Karpa
Keyword(s):  
Time Series ◽  
Extreme Value Distribution ◽  
Offshore Structures ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
Extreme Value Statistics ◽  
Wind Speeds ◽  
Wave Heights ◽  
Extreme Wind Speeds

In the reliability engineering and design of offshore structures probabilistic approaches are frequently adopted. They require the estimation of extreme quantiles of oceanographic data based on the statistical information. Due to strong correlation between such random variables as e.g. wave heights and wind speeds, application of the multivariate, or bivariate in the simplest case, extreme value theory is sometimes necessary. The paper focuses on the extension of the ACER method for prediction of extreme value statistics to the case of bivariate time series. Using the ACER method it is possible to provide an estimate of the exact extreme value distribution of a univariate time series. This is obtained by introducing a cascade of conditioning approximations to the exact extreme value distribution. When this cascade has converged, an estimate of the exact distribution has been obtained. In this paper it will be shown how the univariate ACER method can be extended in a natural way to also cover the case of bivariate data. Application of the bivariate ACER method will also be demonstrated at the measured coupled wind speed and wave height data.

scholarly journals Extreme value theory in the solar wind: the role of current sheets

2019 ◽  
Vol 490 (2) ◽  
pp. 1879-1893
Author(s):  
Tiago F P Gomes ◽  
Erico L Rempel ◽  
Fernando M Ramos ◽  
Suzana S A Silva ◽  
Pablo R Muñoz
Keyword(s):  
Solar Wind ◽  
Power Spectra ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Intermittent Turbulence ◽  
Current Sheets ◽  
Developed Turbulence ◽  
The Right

ABSTRACT This article provides observational evidence for the direct relation between current sheets, multifractality and fully developed turbulence in the solar wind. In order to study the role of current sheets in extreme-value statistics in the solar wind, the use of magnetic volatility is proposed. The statistical fits of extreme events are based on the peaks-over-threshold (POT) modelling of Cluster 1 magnetic field data. The results reveal that current sheets are the main factor responsible for the behaviour of the tail of the magnetic volatility distributions. In the presence of current sheets, the distributions display a positive shape parameter, which means that the distribution is unbounded in the right tail. Thus the appearance of larger current sheets is to be expected and magnetic reconnection events are more likely to occur. The volatility analysis confirms that current sheets are responsible for the −5/3 Kolmogorov power spectra and the increase in multifractality and non-Gaussianity in solar wind statistics. In the absence of current sheets, the power spectra display a −3/2 Iroshnikov–Kraichnan law. The implications of these findings for the understanding of intermittent turbulence in the solar wind are discussed.

Wave Load Prediction on a Stationary Bergy Bit Near a Fixed Offshore Platform

2017 ◽  
Author(s):  
Dong Cheol Seo ◽  
Tanvir Sayeed ◽  
M. Hasanat Zaman ◽  
Ayhan Akinturk
Keyword(s):  
Water Level ◽  
Offshore Structures ◽  
Air Gap ◽  
Offshore Platform ◽  
Load Prediction ◽  
Wave Load ◽  
Offshore Structure ◽  
Cfd Simulations ◽  
Simulation Performance ◽  
Fixed Offshore Platform

Offshore oil and gas operations conducted in harsh environments such offshore Newfoundland may pose additional risks due to collision of smaller ice pieces and bergy bits with the offshore structures, including their topsides in the case of gravity based structures particularly in extreme waves. In this paper, CFD (Computational Fluid Dynamics) prediction for wave loads acting on a bergy bit around a fixed offshore platform is presented. Often the vertical column of a gravity based structure is designed against ice collisions, if operating in such an environment. In practices, topsides are usually protected by being placed sufficiently high from the still water level, away from the reach of the bergy bits. This vertical clearance between the still water level and the topside deck is known an air gap. Hence, the amount of the air gap planned for such an offshore structure is an important factor for the safety of the topsides at a given location. In this study a CFD method is applied to estimate the dynamic response of the bergy bit and provide a reliable air gap to reduce the potential risk of the bergy bit collision. In advance of more complex collision simulations using a free-floating ice for the airgap design, CFD analysis of wave load prediction on a stationary bergy bit is carried out and reported in this paper. In the experiments and CFD simulations, the location of the bergy bit is changed to quantify the change of wave load due to the hydrodynamic interaction between the bergy bit and the platform. Finally, the results of the CFD simulations are compared with the relevant experiment results to confirm the simulation performance prior to the free floating bergy bit simulations.

On Efficient Long-Term Extreme Response Estimation for a Moored Floating Structure

2018 ◽  
Author(s):  
HyeongUk Lim ◽  
Lance Manuel ◽  
Ying Min Low
Keyword(s):  
Wave Train ◽  
Offshore Structures ◽  
Offshore Structure ◽  
Floating Structure ◽  
Sea State ◽  
Peak Period ◽  
Frequency Wave ◽  
Extreme Response ◽  
Term Response

This study investigates the use of efficient surrogate model development with the help of polynomial chaos expansion (PCE) for the prediction of the long-term extreme surge motion of a simple moored offshore structure. The structure is subjected to first-order and second-order (difference-frequency) wave loading. Uncertainty in the long-term response results from the contrasting sea state conditions, characterized by significant wave height, Hs, and spectral peak period, Tp, and their relative likelihood of occurrence; these two variables are explicitly included in the PCE-based uncertainty quantification (UQ). In a given sea state, however, response simulations must be run for any sampled Hs and Tp; in such simulations, typically, a set of random phases (and deterministic amplitudes) define a wave train consistent with the defined sea state. These random phases for all the frequency components in the wave train introduce additional uncertainty in the simulated waves and in the response. The UQ framework treats these two sources of uncertainty — from Hs and Tp on the one hand, and the phase vector on the other — in a nested manner that is shown to efficiently yield long-term surge motion extreme predictions consistent with more expensive Monte Carlo simulations, which serve as the truth system. Success with the method suggests that similar inexpensive surrogate models may be developed for assessing the long-term response of various offshore structures.

Practical Airgap Prediction for Offshore Structures

2004 ◽  
Vol 126 (2) ◽  
pp. 147-155 ◽  
Author(s):  
Bert Sweetman
Keyword(s):  
Model Test ◽  
Offshore Structures ◽  
Value Theory ◽  
Second Order ◽  
New Method ◽  
Statistical Regression ◽  
Post Processing ◽  
Offshore Structure ◽  
First Order ◽  
Order Diffraction

Two new methods are proposed to predict airgap demand. Airgap demand is the maximum expected increase in the water surface elevation caused incident waves interacting with an offshore structure. The first new method enables inclusion of some second-order effects, though it is based on only first-order diffraction results. The method is simple enough to be practical for use as a hand-calculation in the early stages of design. Two existing methods of predicting airgap demand based on first-order diffraction are also briefly presented and results from the three methods are compared with model test results. All three methods yield results superior to those based on conventional post-processing of first-order diffraction results, and comparable to optimal post-processing of second-order diffraction results. A second new method is also presented; it combines extreme value theory with statistical regression to predict extreme airgap events using model test data. Estimates of extreme airgap events based on this method are found to be more reliable than estimates based on extreme observations from a single model test. This second new method is suitable for use in the final stages of design.

scholarly journals Weather regime dependence of extreme value statistics for summer temperature and precipitation

2008 ◽  
Vol 15 (3) ◽  
pp. 365-378 ◽  
Author(s):  
P. Yiou ◽  
K. Goubanova ◽  
Z. X. Li ◽  
M. Nogaj
Keyword(s):  
North Atlantic ◽  
Clustering Algorithm ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Climate Data ◽  
Atmospheric Variability ◽  
Weather Patterns ◽  
The North ◽  
Temperature And Precipitation

Abstract. Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation.

Slender-body expressions for the wave load on offshore structures

1995 ◽  
Vol 450 (1939) ◽  
pp. 391-416 ◽  
Keyword(s):  
Cross Sections ◽  
General Result ◽  
Offshore Structures ◽  
Slender Body ◽  
Structural Members ◽  
Wave Load ◽  
Offshore Structure ◽  
Complete Structure ◽  
Special Cases ◽  
Surface Intersections

Expressions for the wave load on an offshore structure have recently been derived by several authors, by applying the classical slender-body approach to individual structural members. This paper shows that they are all special cases of a more general result, which covers a complete structure, including the effect of non-circular member cross-sections, joints between members, and surface intersections. This more general result cannot readily be derived by the methods adopted by the earlier authors; it relies on an energy argument.

scholarly journals Extreme value theory and return time statistics for dispersing billiard maps and flows, Lozi maps and Lorenz-like maps

2011 ◽  
Vol 31 (5) ◽  
pp. 1363-1390 ◽  
Author(s):  
CHINMAYA GUPTA ◽  
MARK HOLLAND ◽  
MATTHEW NICOL
Keyword(s):  
Time Series ◽  
Hyperbolic Systems ◽  
Return Time ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Distributed Processes ◽  
Return Time Statistics ◽  
Generic Points ◽  
Lozi Maps

AbstractIn this paper we establish extreme value statistics for observations on a class of hyperbolic systems: planar dispersing billiard maps and flows, Lozi maps and Lorenz-like maps. In particular, we show that for time series arising from Hölder observations on these systems which are maximized at generic points the successive maxima of the time series are distributed according to the corresponding extreme value distributions for independent identically distributed processes. These results imply an exponential law for the hitting and return time statistics of these dynamical systems.

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.

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