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Both wave-frequency(WF) and low-frequency(LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system.This paper conducts a comprehensive investigation of applicable probability density functions(PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method.Short-term statistical characteristics of mooring-line tension responses are firstly investigated,in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients.Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes.Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components.A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses.Using time domain simulation as a benchmark,its accuracy is further validated using a numerical case study of a moored semi-submersible platform.
Both wave-frequency (WF) and low-frequency (LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system. This paper conducts a comprehensive investigation of applicable probability density functions (PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. short-term statistical characteristics of mooring-line tension responses are initially investigated, where the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients. Distributed distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes. Results States that that Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components. A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses. Using time domain simulation as a benchmark, its accuracy is further validated using a numerical case study of a moored semi-submersible platform.