Probabilistic Analysis and Fatigue Damage Assessment of Offshore Mooring System due to Non-Gaussian Bimodal Tension Processes

• Published in: Journal of Ocean University of China 2017-08, Vol.16 (4), p.585-601
• Main Authors: Chang, Anteng, Li, Huajun, Wang, Shuqing, Du, Junfeng
• Format: Article
• Language: English
• Subjects: Accuracy; Amplitudes; Approximation; Case studies; Coefficients; Components; Computer simulation; Crack propagation; Damage assessment; Distribution; Distribution functions; Earth and Environmental Science; Earth Sciences; Fatigue failure; Gaussian process; Kurtosis; Materials fatigue; Meteorology; Mooring; Mooring systems; Normal distribution; Ocean engineering; Oceanography; Offshore; Offshore drilling rigs; Parametric methods; Probabilistic analysis; Probabilistic methods; Probability; Probability density functions; Probability theory; Semisubmersible platforms; Skewness; Spectral methods; Statistics; Stochasticity; Submersible platforms; Submersibles; Tension; Time domain analysis; 双峰; 损伤评估; 概率分析; 疲劳损伤; 系泊系统; 缆绳张力; 非线性变换; 非高斯
• ISSN: 1672-5182; 1993-5021; 1672-5174
• DOI: 10.1007/s11802-017-3365-x

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 func- tions （PDFs） of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. Short-term statisti- cal 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.