Metocean Design Criteria for Pipeline On-Bottom Stability

2011 ◽  
Author(s):  
Richard Gibson
Keyword(s):  
Parametric Representation ◽  
Extreme Value Analysis ◽  
Design Criteria ◽  
Value Analysis ◽  
Reliability Method ◽  
Extreme Response ◽  
Wave Cycle ◽  
Induced Velocity ◽  
Pipeline Design ◽  
Wave Induced

This paper is concerned with a response based method for determining metocean design criteria for offshore pipelines. The method determines a set of metocean parameters that are consistent with the extreme response of the pipeline, and hence, incorporates the dependence between them implicitly. However, there are a number of challenges in its application. Firstly, the loading on a pipeline is dependent on the previous wave cycle, and hence, the drag and inertia coefficients vary within a sea-state. Secondly, along many pipeline routes the waves are depth limited and the short-term distribution of wave induced velocity and pipeline response can be difficult to define. These challenges are overcome through a number of approaches that include a parametric representation of the distribution of the response and the application of multivariate extreme value analysis. Furthermore, the sensitivity of the method to assumptions about the pipeline design is examined, and the problems with using the combined wave and current induced velocity as a proxy for the response are discussed. The method is applied to a site in the Mediterranean Sea and the results are compared to those from the application of the first order reliability method.

Extreme Response Predictions for Jack-Up Units in Second Order Stochastic Waves by FORM

2007 ◽  
Author(s):  
Jo̸rgen Juncher Jensen
Keyword(s):  
Second Order ◽  
Sea State ◽  
First Order ◽  
Reliability Method ◽  
Extreme Response ◽  
Stochastic Waves ◽  
Short Time ◽  
Wave Induced ◽  
Jack Up ◽  
Operational Time

The aim of the present paper is to advocate for a very effective stochastic procedure, based on the First Order Reliability Method (FORM), for extreme value predictions related to wave induced loads. All kinds of non-linearities can be included, as the procedure makes use of short time-domain simulations of the response in question. The procedure will be illustrated with a jack-up rig where second order stochastic waves are included in the analysis. The result is the probability of overturning as function of sea state and operational time.

scholarly journals Spatial and Seasonal Variability of Metocean Design Criteria in the Southern South China Sea From Covariate Extreme Value Analysis

2019 ◽  
Author(s):  
Vadim Anokhin ◽  
Emma Ross ◽  
David Randell ◽  
Philip Jonathan
Keyword(s):  
Wind Speed ◽  
South China Sea ◽  
South China ◽  
Upper Bound ◽  
Shape Parameter ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Design Criteria ◽  
Southern South China Sea ◽  
Value Analysis

Abstract This paper describes spatial and seasonal variability of metocean design criteria in the southern South China Sea. Non-stationary extreme value analysis was performed using the CEVA approach (Covariate Extreme Value Analysis,[1]) for a 59-year long SEAFINE hindcast of winds and waves, estimating metocean design criteria up to 10,000-year return period. Wind design criteria are mostly driven by large-scale monsoonal events; at higher return periods infrequent cyclonic events have strong influence on the tail of the extreme value distribution but confined to a limited geographical area. The CEVA analysis of waves showed much less dependence on the tropical cyclone events; the spatial metocean design criteria were smoother, mostly influenced by the monsoonal wind strength, fetch and local bathymetry. Return value estimates illustrate the strong seasonality of metocean design criteria, with boreal winter (December-February, Northeasterly monsoon) contributing most to the extremes, while April and May are the mildest months. Estimates for the ratio of 10,000/100-year return values are also presented, both for winds and waves. There is empirical evidence that the range of “typical” values of generalised Pareto shape parameter observed for Hs is different to that observed for wind speed. For this reason, an upper bound of +0.2 for generalised Pareto shape was specified for wind speed analysis, compared to 0.0 for Hs. In some cases, increase of upper bound for waves to 0.1 is justified, leading to slightly more conservative Hs values. We confirmed that the upper end point constraint was not too influential on the distributions of generalised Pareto shape parameter estimated. Nevertheless, it is apparent that specification of bounds for generalised Pareto shape is a critical, but problematic choice in metocean applications.

Extreme Value Analysis of the Response of a Turret-Moored FPSO

2010 ◽  
Author(s):  
Lui´s Volnei Sudati Sagrilo ◽  
Arvid Naess ◽  
Zhen Gao
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Distribution Model ◽  
Extreme Value Analysis ◽  
Coupled Analysis ◽  
System Response ◽  
Short Term ◽  
Utilization Factor ◽  
Value Analysis ◽  
Extreme Response

One of the standardized procedures used in the design of floating systems and their mooring and production lines is the so-called short-term design approach where the system is analyzed for some specific extreme environmental conditions. Along with this procedure, a nonlinear time-domain coupled dynamic analysis, considering the floater and its risers and mooring lines, is nowadays feasible to be employed in the design practice. One important and challenging aspect of this process is concerned with the estimation of the characteristic short-term extreme values of the system response parameters based on the sampled time-series. In this paper a common procedure used to establish these extreme values for floater system response parameters, which is based on a Weibull distribution model for the time-series peaks, is reviewed in the light of a recently proposed approach based on a general parametric model for the average conditional exceedance rate of peaks. It is shown that the former model corresponds to a particular case of the latter one. Numerical results are presented for the response parameters of a turret-moored FPSO considering a short-term coupled analysis of the whole system under an extreme environmental condition of wind, wave and current. Specifically, the extreme response of surge motion, top tension of the most loaded mooring line and DnV’s utilization factor for the most critical section of a 8″ SLWR (Steel Lazy Wave Riser) are investigated.

Long Term Failure Probability Calculation Method Applied to Riser Design

2008 ◽  
Author(s):  
Timothe´e Perdrizet ◽  
Daniel Averbuch
Keyword(s):  
Failure Probability ◽  
Sea State ◽  
Reliability Method ◽  
Extreme Response ◽  
Probability Calculation ◽  
Riser Design ◽  
The Mean ◽  
Time Invariant ◽  
Wave Induced

A time efficient methodology is described to evaluate the non linear extreme response of a riser connected to a FPSO subjected to wave induced loads in a stationary sea state. It is extended to cover all sea states and thus to assess the long term failure probability of the riser. The short term procedure is based on a classic time variant reliability method. It uses an approximation of the mean outcrossing rate, which is computed with the time invariant reliability method FORM (First Order Reliability Method).

On the Extreme Value Analysis of the Response of a Turret Moored FPSO

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
L. V. S. Sagrilo ◽  
A. Naess ◽  
Z. Gao
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Extreme Value Analysis ◽  
Coupled Analysis ◽  
System Response ◽  
Outer Diameter ◽  
Short Term ◽  
Utilization Factor ◽  
Value Analysis ◽  
Extreme Response

One of the standardized procedures used in the design of floating systems and their mooring and production lines is the so-called short-term design approach where the system is analyzed for some specific extreme environmental conditions. Along with this procedure, a nonlinear time-domain coupled dynamic analysis, considering the floater and its risers and mooring lines, can nowadays be incorporated as a feasible part of the design practice. One very important and challenging aspect of this process is concerned with the estimation of the characteristic short-term extreme values of the system response parameters based on the sampled time-series. In this paper a common procedure used to establish these extreme values for floater system response parameters, which is based upon a Weibull distribution model for the peaks of the time-series, is reviewed in the light of a recently proposed approach based on a general parametric model for the average conditional exceedance rate of peaks. It is shown that the former model corresponds to a particular case of the latter one. Numerical results are presented for the response parameters of a turret-moored Floating, Production, Storage and Offloading (FPSO) unit considering a short-term coupled analysis of the whole system under an extreme environmental condition of wind, wave, and current. Specifically, the extreme response of surge motion, top tension of the most loaded mooring line, and Det norske Veritas (DnV) codes utilization factor for the most critical section of an 0.20 m outer diameter SLWR (steel lazy wave riser) are investigated.

Extreme value statistics of flow-induced hydrofoil vibration and resonance

2021 ◽  
Vol 69 (1) ◽  
pp. 18-29
Author(s):  
Connor J. McCluskey ◽  
Manton J. Guers ◽  
Stephen C. Conlon
Keyword(s):  
Cyclic Loading ◽  
Maximum Load ◽  
Extreme Value ◽  
Flow Speed ◽  
Extreme Value Statistics ◽  
Extreme Value Analysis ◽  
Flow Induced Vibration ◽  
Data Set ◽  
Value Analysis ◽  
Extreme Response

Flow-induced noise and vibration produce cyclic loading on structures such as wind turbines, propellers, and vehicle control surfaces. This cyclic loading can produce fatigue damage in these structures. Additionally, large outlier loads can potentially exceed maximum design levels. Most other works have focused on the extreme value statistics of random loads, and there is limited work which considers the influence of structural resonances. The goal of this work was to study the influence of low order mode responses on extreme response statistics. To accomplish this, the flow-induced vibration response of cantilever fins forced by the wake of an upstream flow obstruction was measured in a closed-circuit water tunnel. The tunnel flow speed was increased, so the wake would excite the first bending mode. A maxima data set was determined from the measured response using the block maxima method, and the generalized extreme value (GEV) distribution was applied to each flow speed. Data were then filtered into stiffness-controlled and damping-controlled responses, and the extreme value analysis was repeated. Results indicated that the extreme response was influenced more by the damping-controlled response than the stiffness-controlled response. When excited, extreme responses from structural resonances must be considered in maximum load design.

Modeling European hot spells using extreme value analysis

2014 ◽  
Vol 58 (3) ◽  
pp. 193-207 ◽  
Author(s):  
C Photiadou ◽  
MR Jones ◽  
D Keellings ◽  
CF Dewes
Keyword(s):  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Hot Spells

scholarly journals Threshold selection in univariate extreme value analysis

Extremes ◽  
2021 ◽  
Author(s):  
Laura Fee Schneider ◽  
Andrea Krajina ◽  
Tatyana Krivobokova
Keyword(s):  
Mean Squared Error ◽  
Extreme Value ◽  
Hill Estimator ◽  
Small Samples ◽  
Extreme Value Analysis ◽  
Threshold Selection ◽  
Value Analysis ◽  
Wide Range ◽  
Asymptotic Mean Squared Error ◽  
The Hill

AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples. The second method smoothly estimates the asymptotic mean squared error of the Hill estimator and performs consistently well over a wide range of processes. Both methods are analyzed theoretically, compared to existing procedures in an extensive simulation study and applied to a dataset of financial losses, where the underlying extreme value index is assumed to vary over time.

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