Investigation on the probabilistic distribution of mooring line tension for fatigue damage assessment

• Non-Gaussianity of the short-term mooring line tension is investigated and validated.
• Gamma distribution yields good results when fitting the short-term tension amplitudes.
• Modified Gamma distribution can well characterize the long-term tension amplitudes.
• Fatigue damage of mooring line is assessed accurately based on the Gamma distribution.

This paper is to investigate the applicable probability density functions (PDFs) for the short- and long-term mooring line tension amplitudes to be used for accurately assessing the mooring line fatigue damage with the spectral method. Statistical characteristics of the mooring line tensions were investigated, in which kurtosis and skewness were computed and compared to validate the non-normality of the line tension response. Several PDFs, including Rayleigh, GEV, and Gamma distributions, are used to express the short-term statistical distribution of the mooring line tension amplitudes. Results indicate that the Gamma distribution can give much better fitting than the Rayleigh and GEV distributions. In order to identify the long-term distribution of the tension amplitudes, the Gamma distribution is modified by bringing in a location parameter. Compared with the generally used Weibull distribution, the modified Gamma distribution can characterize the long-term PDF of the tension amplitudes much better. Moreover, the modified Gamma distribution can give much more accurate assessment of the mooring line fatigue damage than the Weibull distribution.