Long-Term Extreme Response and Reliability of a Vessel Rolling in Random Beam Seas

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Wei Chai ◽  
Arvid Naess ◽  
Bernt J. Leira
Keyword(s):  
Nonlinear Effects ◽  
Reliability Evaluation ◽  
Roll Motion ◽  
Response Analysis ◽  
Linear Filter ◽  
Beam Seas ◽  
Random Seas ◽  
Extreme Response ◽  
Nonlinear Roll Motion

In this paper, the long-term extreme response of a vessel rolling in random beam seas and the associated reliability evaluation are addressed. The long-term response analysis is based on the upcrossing rates of the roll motion under different sea states. Generally, for nonlinear roll motion in random seas, the high-level roll response is sensitive and closely related to the nonlinear effects associated with the restoring and damping terms. Therefore, assessing the corresponding statistics of the random roll motion with low probability levels is difficult and time-consuming. In this work, the Markov theory is introduced in order to tackle this problem. Specifically, for the dead ship condition, the random roll excitation moment is approximated as a filtered white noise process by applying a second-order linear filter and an efficient four-dimensional (4D) path integration (PI) technique is applied in order to calculate the response statistics. Furthermore, the reliability evaluation is based on the well-known Poisson estimate as well as on the upcrossing rate calculated by the 4D PI method. The long-term analysis and reliability evaluation of the nonlinear roll motion in random seas, which consider the variation of the sea states could be a valuable reference for ship stability research.

Long-Term Extreme Response of a Vessel Rolling in Random Seas

2016 ◽  
Author(s):  
Wei Chai ◽  
Arvid Naess ◽  
Bernt J. Leira
Keyword(s):  
Nonlinear Effects ◽  
Roll Motion ◽  
Response Analysis ◽  
Linear Filter ◽  
Beam Seas ◽  
Random Seas ◽  
Extreme Response ◽  
High Level ◽  
Nonlinear Roll Motion

In this paper, the long-term extreme response of a vessel rolling in random beam seas is addressed. The long-term response analysis is based on the upcrossing rates of the roll motion under different sea states. However, the nonlinear effects associated with the restoring and damping terms have a significant influence on the high-level response, assessing the corresponding statistics, such as the upcrossing rate, with low probability levels is difficult and time-consuming. In this work, the Markov theory is introduced in order to tackle this problem. Specifically, the random roll excitation moment is approximated as a filtered white noise process by applying a linear filter technique and an efficient four-dimensional (4D) path integration (PI) procedure is applied in order to calculate the response statistics. The long-term analysis of nonlinear roll motion in random seas that takes into considerations of the response statistics obtained by the 4D PI method as well as the variation of the sea states could be a valuable reference for ship stability research.

Joint Distribution of Environmental Condition at Five European Offshore Sites for Design of Combined Wind and Wave Energy Devices

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Lin Li ◽  
Zhen Gao ◽  
Torgeir Moan
Keyword(s):  
Renewable Energy ◽  
Wave Energy ◽  
Environmental Data ◽  
Offshore Wind ◽  
Response Analysis ◽  
Energy Devices ◽  
Joint Distributions ◽  
Wave Parameters ◽  
Extreme Response

The design of wind turbines requires information about joint data for wind and wave conditions. Moreover, combining offshore wind and wave energy facilities is a potential way to reduce the cost of offshore wind farms. To design combined offshore renewable energy concepts, it is important to choose sites where both wind and wave energy resources are substantial. This paper deals with joint environmental data for five European offshore sites which serve as basis for the analysis and comparison of combined renewable energy concepts developed in the EU FP7 project—MARINA Platform. The five sites cover both shallow and deep water, with three sites facing the Atlantic Ocean and two sites in the North Sea. The long-term joint distributions of wind and wave parameters are presented for these sites. Simultaneous hourly mean wind and wave hindcast data from 2001 to 2010 are used as a database. The joint distributions are modeled by fitting analytical distributions to the hindcast data. The long-term joint distributions can be used to estimate the wind and wave power output from each combined concept and to estimate the fatigue lifetime of the structure. The marginal distributions of wind and wave parameters are also provided. Based on the joint distributions, contour surfaces are established for combined wind and wave parameters for which the probability of exceedance corresponds to a return period of 50 years. The design points on the 50-year contour surfaces are suggested for extreme response analysis of combined concepts.

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.

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.

scholarly journals Long-term extreme response analysis of a long-span pontoon bridge

2018 ◽  
Vol 58 ◽  
pp. 154-171 ◽  
Author(s):  
Finn-Idar Grøtta Giske ◽  
Knut Andreas Kvåle ◽  
Bernt Johan Leira ◽  
Ole Øiseth
Keyword(s):  
Response Analysis ◽  
Long Span ◽  
Extreme Response

scholarly journals Extended Environmental Contour Methods for Long-Term Extreme Response Analysis of Offshore Wind Turbines1

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Xiaolu Chen ◽  
Zhiyu Jiang ◽  
Qinyuan Li ◽  
Ye Li ◽  
Nianxin Ren
Keyword(s):  
Turbulence Intensity ◽  
Offshore Structures ◽  
Offshore Wind ◽  
Contour Method ◽  
Offshore Wind Turbine ◽  
Response Analysis ◽  
Modified Method ◽  
Extreme Response ◽  
Wind Turbulence

Abstract Environmental contour method is an efficient method for predicting the long-term extreme response of offshore structures. The traditional environmental contour is obtained using the joint distribution of mean wind speed, significant wave height, and spectral peak period. To improve the accuracy of traditional environmental contour method, a modified method was proposed considering the non-monotonic aerodynamic behavior of offshore wind turbines. Still, the modified method assumes constant wind turbulence intensity. In this paper, we extend the existing environmental contour methods by considering the wind turbulence intensity as a stochastic variable. The 50-year extreme responses of a monopile-based offshore wind turbine are compared using the extended environmental contour methods and the full long-term method. It is found that both the environmental contour method and the modified environmental contour method, with the wind turbulence intensity included as an individual variable, give more accurate predictions compared with those without. Using the full long-term method as a benchmark, this extended approach could reduce the nonconservatism of the environmental contour method and conservatism of the modified environmental contour method. This approach is effective under wind-dominated or combined wind-wave loading conditions, but may not be as important for wave-dominated conditions.

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