Long-Term Extreme Response Analysis of Marine Structures Using Inverse SORM

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Finn-Idar G. Giske ◽  
Bernt Johan Leira ◽  
Ole Øiseth
Keyword(s):  
Structural Reliability ◽  
New Method ◽  
Response Analysis ◽  
Marine Structures ◽  
Short Term ◽  
Reliability Method ◽  
Extreme Response ◽  
Improved Accuracy ◽  
Term Response

In this paper, the first-order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second-order reliability method (SORM) is used to improve the accuracy of the approximation, resulting in an inverse SORM (ISORM) approach. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve significantly improved accuracy, yet keep the number of required short-term response analyses within acceptable levels.

Long-Term Extreme Response Analysis of Marine Structures Using Inverse SORM

2017 ◽  
Author(s):  
Finn-Idar G. Giske ◽  
Bernt Johan Leira ◽  
Ole Øiseth
Keyword(s):  
Structural Reliability ◽  
New Method ◽  
Response Analysis ◽  
Marine Structures ◽  
Short Term ◽  
Reliability Method ◽  
Extreme Response ◽  
Improved Accuracy ◽  
Term Response

In this paper the first order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second order reliability method (SORM) is used to improve the accuracy of the approximation. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve improved accuracy for large return periods, yet keep the number of required short-term response analyses within acceptable levels.

Post-Katrina performance of a turret-moored floating storage and offloading unit in the Gulf of Mexico

2009 ◽  
Vol 223 (3) ◽  
pp. 391-398
Author(s):  
J J M Baar
Keyword(s):  
Gulf Of Mexico ◽  
Wind Waves ◽  
Mooring Line ◽  
Response Analysis ◽  
Strong Impact ◽  
Offshore Platforms ◽  
Short Term ◽  
Line Loads ◽  
Term Response

Conventional design of ships and offshore platforms relies on performing a short-term response analysis for metocean conditions with a 100-year return period. This approach is efficient but not necessarily conservative when compared with a comprehensive long-term response analysis that considers platform responses for storms encountered over the lifetime of the platform. Turret-moored floating production, storage and offloading systems are sensitive to non-collinear wind, waves, and current conditions. During hurricanes in the Gulf of Mexico such conditions frequently occur and, depending on the resulting weathervaning characteristics of a turret-moored tanker, they may have a strong impact on vessel motions, mooring line loads, and riser performance. In recent years some very strong hurricanes have occurred in the Gulf of Mexico, e.g. Katrina and Rita in 2005. When including these recent storm data in the long-term response analysis they have a marked effect on the extrapolated 100-year long-term responses. The post-Katrina long-term responses of a generic turret-moored floating storage and offloading unit are evaluated and compared against pre-Katrina analysis results. The results of the analysis are used to stipulate response-based design criteria which are simple short-term design sea states that can reproduce a given long-term response (e.g. roll).

Long-term extreme response analysis for semi-submersible platform mooring systems

2020 ◽  
pp. 147509022097651
Author(s):  
Yuliang Zhao ◽  
Sheng Dong
Keyword(s):  
Environmental Data ◽  
Distribution Model ◽  
Response Analysis ◽  
Accurate Assessment ◽  
Response Distribution ◽  
Short Term ◽  
Floating Structure ◽  
Extreme Response ◽  
Term Analysis

The accurate assessment of long-term extreme responses of floating-structure mooring system designs is important because of small failure probabilities caused by long-term and complex ocean conditions. The most accurate assessment would involve considering all conceivable sea states in which each sea state is regarded as a stochastic process and performing nonlinear time-domain numerical simulations of mooring systems to estimate the extreme response from a long-term analysis. This procedure would be computationally intensive because of the numerous short-term sea states involved. Here, a more feasible approach to evaluate the long-term extreme response is presented through immediate integration combined with Monte Carlo simulations. A parameter fitting procedure of the short-term extreme response distribution under irregular wave conditions is employed to solve the long-term response integration. Case studies were conducted on a semi-submersible platform using environmental data measurements of the Gulf of Mexico and a joint distribution model of the environmental parameters was considered. This approach was observed to be effective and the results were compared with those of traditional methodologies (univariate extreme value design and environmental contour methods). The differences were reflected using a reliability analysis of mooring lines, which indicated that the design standards must be stricter when using long-term analysis.

Long-Term Extreme Response of a Straight Floating Bridge Across the Bjørnafjord

2019 ◽  
Author(s):  
Finn-Idar Grøtta Giske ◽  
Arnt Fredriksen
Keyword(s):  
Computational Effort ◽  
Response Analysis ◽  
Peak Period ◽  
First Order ◽  
Environmental Models ◽  
Reliability Method ◽  
Extreme Response ◽  
Floating Bridge ◽  
The Given

Abstract In this paper, long-term extreme response analysis is performed for a straight floating bridge across the Bjørnafjord, using a recently developed inverse first-order reliability method (IFORM) approach. Full integration of the long-term extreme response formulation is also performed for comparison. Two different environmental models are estimated based on a scatter diagram of significant wave height and peak period for the given location. The IFORM method is seen to provide reasonable estimates of the long-term extreme response, at a significantly reduced computational effort.

Estimating Long-Term Distributions of Extreme Response of a Catenary Riser

2011 ◽  
Author(s):  
Elizabeth Passano ◽  
Philippe Mainc¸on
Keyword(s):  
Nonlinear Response ◽  
Unbiased Estimation ◽  
Reliable Estimate ◽  
Response Distribution ◽  
Short Term ◽  
Response Predictors ◽  
Extreme Response ◽  
Nonlinear Simulations ◽  
Term Response

The purpose of this paper is to present a method for efficient and unbiased estimation of the long-term extreme response distribution of a catenary riser. In this approach a computationally inexpensive, nonlinear response predictor is used to estimate the response in all sea states, thus allowing selection of relevant sea states and intervals within sea states for detailed, nonlinear finite element simulations. This method requires significantly less simulation time than the conventional approach with extensive nonlinear simulations of many sea states. The method is applied to a catenary riser case. In an earlier study (Passano and Larsen, OMAE 2006), a strong relation was found between the prescribed vertical motions at the top and the axial force and bending moment near the touch down area. This relation was then used to limit simulations to intervals where the largest maxima values were expected. This gave an estimate of the upper part or tail of the extreme response in the selected sea states. In a later study (Passano and Larsen, OMAE 2007), nonlinear response predictors based on the prescribed vertical motions were established. These were used to estimate the short-term extreme response distribution directly. In the case study of this paper three long-term response distributions are compared: 1) A distribution established directly from the predicted short-term response distributions. 2) A distribution based on response simulated in the relevant time intervals of the relevant sea states. 3) A distribution obtained from extensive nonlinear simulations of the sea states in the scatter diagram. It is found that distribution 2) provides a fast and reliable estimate of 3). This allows a significant reduction in analysis work.

Environmental Contour Lines for Design Purposes: Why and When?

2004 ◽  
Author(s):  
Sverre Haver ◽  
Gudmund Kleiven
Keyword(s):  
Time Domain ◽  
Exceedance Probability ◽  
Response Analysis ◽  
Short Term ◽  
Structural Problems ◽  
Contour Lines ◽  
Convenient Approach ◽  
Probabilistic Structure ◽  
Term Response

Methods of prediction of structural loads corresponding to a required target annual exceedance probability are reviewed. Particular attention is given to utilization of environmental contour lines for such a purpose. This approach is based on using short term methods for predicting adequate estimates of the q-probability response. The environmental contour line approach is a very convenient approach if complicated structural problems are considered. For such problems one will often have to involve numerical time domain analyses or model tests to reveal the short term probabilistic structure of the response maxima, making a full long term response analysis impossible for most practical problems.

On the Long-Term Reliability Analysis of a Point Absorber Wave Energy Converter

2017 ◽  
Author(s):  
Jarred Canning ◽  
Phong Nguyen ◽  
Lance Manuel ◽  
Ryan G. Coe
Keyword(s):  
Wave Energy ◽  
Reference Model ◽  
Wave Energy Converter ◽  
Environmental Data ◽  
Energy Converter ◽  
Short Term ◽  
Point Absorber ◽  
Extreme Response ◽  
Term Response

Of interest in this study is the long-term response and performance of a two-body wave point absorber (“Reference Model 3”), which serves as a wave energy converter (WEC). In a previous study, the short-term uncertainty in this device’s response was studied for an extreme sea state. We now focus on the assessment of the long-term response of the device where we consider all possible sea states at a site of interest. We demonstrate how simulation tools may be used to evaluate the long-term response and consider key performance parameters of the WEC device, which are the heave and surge forces on the power take-off system and the power take-off extension. We employ environmental data at a designated deployment site in Northern California. Metocean information is generated using approximately 15 years of data from this site (National Data Buoy Center site no. 46022). For various sea states, a selected significant wave height and peak period are chosen to describe representative conditions. Then, using a public-domain simulation tool (Wave Energy Converter Simulator or WEC-Sim), we generate various short-term time-domain response measure for these sea states. Distribution fits to extreme response statistics are generated, for each bin that represents a cluster of sea states, using the open-source toolbox, WDRT (WEC Design Response Toolbox). Long-term distributions for each response variable of interest are estimated by weighting short-term distributions by the likelihood of the sea states; from these distributions, the 50-year response can be derived. The 50-year response is also estimated using an approximate but more efficient inverse reliability approach. Comparisons are made between the two approaches.

scholarly journals Novel robust time series analysis for long-term and short-term prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Okamura ◽  
Yutaka Osada ◽  
Shota Nishijima ◽  
Shinto Eguchi
Keyword(s):  
Robust Regression ◽  
Simulated Data ◽  
New Method ◽  
Short Term ◽  
Least Absolute Deviations ◽  
Term Prediction ◽  
Regression Approach ◽  
Short Term Prediction ◽  
Long Term Prediction

AbstractNonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner–recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.

Unfolding the case of returnees: How the European Union and its member States are addressing the return of foreign fighters and their families

2021 ◽  
pp. 1-23
Author(s):  
Carlota Rigotti ◽  
Júlia Zomignani Barboza
Keyword(s):  
European Union ◽  
Perceived Threat ◽  
The European Union ◽  
Security Threat ◽  
Short Term ◽  
Member States ◽  
Foreign Fighters ◽  
Term Response

Abstract The return of foreign fighters and their families to the European Union has mostly been considered a security threat by member States, which consequently adopt repressive measures aimed at providing an immediate, short-term response to this perceived threat. In addition to this strong-arm approach, reintegration strategies have also been used to prevent returnees from falling back into terrorism and to break down barriers of hostility between citizens in the long term. Amidst these different strategies, this paper seeks to identify which methods are most desirable for handling returnees.

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