Bayesian analysis of short term extreme mooring tension for a point absorber with mixture of gamma and generalised pareto distributions

Xu, Sheng; Soares, C. Guedes

doi:10.1016/j.apor.2021.102556

Cited by 6 publications

(4 citation statements)

References 66 publications

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“…Hsu et al [17] studied the damping and impact load of anchor chain in a shallow water environment by experimental method. Xu and Guedes Soares [18][19][20] studied the hydrodynamic response of the point absorber and the dynamic response of the mooring system through a series of regular and irregular wave model tests on the buoy wave energy converter. Subsequently, based on the model experiment results, a new Markov chain by Bayesian inference method was proposed to study the short-term limit mooring tension.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Numerical Simulation of Semitensioned Mooring Line under Taut-Slack State

Shi

Zhang

Liu

et al. 2023

Shock and Vibration

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In this paper, considering the mooring system can be taut-slack in the motion, the dynamic equations of the mooring system are derived by using the theory of large deformation. The nonlinear dynamic response of semitensioned mooring line is numerically simulated. Assuming the platform motion is known, the effect of platform on mooring line is simplified as an end-point excitation. Directly using the finite difference method for numerically solving partial differential equations of mooring line, the dynamic responses can be obtained. Then, the causes about the nonlinear state are analyzed, and the location where the taut-slack phenomenon occurs can be located by calculating the tension of mooring. The results show that the mooring line is more likely to be taut-slack under tangential excitation with the tension change, while the mooring remains taut under normal excitation. The taut-slack state of the mooring line is concentrated near the anchor point. Through the amplitude-frequency curve and bifurcation point set, it is found that the taut-slack region is accompanied by multiperiod motion. And the taut-slack phenomenon will lead to the unstable motion.

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Section: Introductionmentioning

confidence: 99%

Modeling and Numerical Simulation of Semitensioned Mooring Line under Taut-Slack State

Shi

Zhang

Liu

et al. 2023

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…For example, the peaks-over-threshold (POT) [34] and generalized Pareto distribution (GPD) estimation [35]. Regardless of the POT method or the GPD estimation, they are both sensitive to the threshold, but a relatively high threshold will increase the statistical uncertainty of estimated extreme value [36].…”

Section: Introductionmentioning

confidence: 99%

“…The Bayesian approach has been utilized to estimate the extreme value of bridges due to various loads. Sheng Xu et al [36] proposed the Bayesian method to study the shortterm extreme mooring tensions. Y.Q Ni et al applied the Bayesian approaches when evaluating the wind-resistant performance [38] and condition assessment [39].…”

Section: Introductionmentioning

confidence: 99%

“…This models the tail distribution of traffic load effect based on the POT method and FPP, which is based on the EVT for stochastic processes. Meanwhile, since the number of extreme traffic load effect values in the sample is relatively small, especially when the threshold is high [36,39], the Bayes' theorem is applied to reduce the statistical uncertainty and update the distribution model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bayesian Updates for an Extreme Value Distribution Model of Bridge Traffic Load Effect Based on SHM Data

2021

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As the distribution function of traffic load effect on bridge structures has always been unknown or very complicated, a probability model of extreme traffic load effect during service periods has not yet been perfectly predicted by the traditional extreme value theory. Here, we focus on this problem and introduce a novel method based on the bridge structural health monitoring data. The method was based on the fact that the tails of the probability distribution governed the behavior of extreme values. The generalized Pareto distribution was applied to model the tail distribution of traffic load effect using the peak-over-threshold method, while the filtered Poisson process was used to model the traffic load effect stochastic process. The parameters of the extreme value distribution of traffic load effect during a service period could be determined by theoretical derivation if the parameters of tail distribution were estimated. Moreover, Bayes’ theorem was applied to update the distribution model to reduce the statistical uncertainty. Finally, the rationality of the proposed method was applied to analyze the monitoring data of concrete-filled steel tube arch bridge suspenders. The results proved that the approach was convenient and found that the extreme value distribution type III might be more suitable as the traffic load effect probability model.

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Reliability assessment of mooring system for fish cage considering one damaged mooring line

et al. 2022

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Bayesian analysis of short term extreme mooring tension for a point absorber with mixture of gamma and generalised pareto distributions

Cited by 6 publications

References 66 publications

Modeling and Numerical Simulation of Semitensioned Mooring Line under Taut-Slack State

Modeling and Numerical Simulation of Semitensioned Mooring Line under Taut-Slack State

Bayesian Updates for an Extreme Value Distribution Model of Bridge Traffic Load Effect Based on SHM Data

Reliability assessment of mooring system for fish cage considering one damaged mooring line

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