Journal of Marine Science and Engineering (Aug 2023)

A Novel Wave Energy Equivalence Based Lumping Block Method for Efficiently Predicting the Fatigue Damage of Mooring Lines

  • Yuanzhi Guo,
  • Shuqing Wang,
  • Haiyan Guo,
  • Xiancang Song

DOI
https://doi.org/10.3390/jmse11091679
Journal volume & issue
Vol. 11, no. 9
p. 1679

Abstract

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The lumping block equivalent method (LBEM) is widely used to reduce the computational effort in the fatigue damage assessment of offshore structures, and the wave parameters of the representative sea states (RSSs) resulting from LBEM are of vital importance for the accurate prediction of offshore structures’ fatigue damage. In this study, a novel wave energy equivalence (WEE)-based LBEM is proposed to determine the wave parameters of the RSS accurately. The novelty of the proposed method is that a compact relationship between the input wave energy component and mooring lines’ fatigue damage is derived, and the modified statistical relationships between the wave parameters and spectral moments are provided by incorporating the effects of the peak enhancement factor of the input wave spectrum, the number of original sea states (OSSs) and the equivalence bandwidth of the OSSs. Based on the compact relationship, the wave energy component of the RSS can be determined from the wave energy component of the OSSs for each wave frequency from the viewpoint of the fatigue damage equivalence criterion. The wave energy distribution of the RSS can be accurately characterized with the wave energy distribution of the OSSs, and the spectral moments of the RSS can be calculated by its energy distribution directly, without any approximation. Moreover, the wave parameters of the RSS can be determined from the modified statistical relationships easily. The effectiveness of the proposed WEE LBEM is numerically investigated with a moored semi-submersible platform. Results show that the proposed WEE LBEM is robust, efficient and accurate within engineering expectations, and it outperforms the conventional LBEMs both in accuracy and robustness.

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