Session: 02-09-01 Reliability of Moorings & Risers

Submission Number: 182098

Long-Term Extreme Value Prediction of Mooring Line Tension for Floating Structures 

To address the safety and reliability of floating offshore structures, this study focuses on the mooring system and investigates the long-term extreme value prediction of mooring line tension. A time-domain numerical model of a semi-submersible floating structure is established using OpenFAST, and mooring tension response samples are obtained under irregular wave conditions. The long-term extreme mooring tension corresponding to a 100-year return period is predicted using both the full long-term analysis method and the environmental contour method. In the environmental contour approach, environmental contours are constructed based on the Rosenblatt transformation and the Nataf model, respectively. By comparing the governing sea states identified by different environmental contour construction methods and the associated extreme mooring tension responses, the influence of environmental parameter dependence modeling on long-term extreme value prediction is systematically investigated. The results indicate that, under the same 100-year return period constraint, significant differences exist in the predicted design extreme mooring tensions obtained from different environmental contour models. Furthermore, a coupling relationship is observed between the environmental contour construction method and the selected percentile level along the contour. These findings demonstrate that the choice of dependence modeling approach plays a critical role in long-term extreme value prediction. The results of this study provide useful guidance for ultimate limit state assessment and for the selection of appropriate long-term extreme value prediction methods in the design of mooring systems for floating structures.

Presenting Author: Jingcan Wang Wuhan University of Technology

Presenting Author Biography: Miss Wang Jingcan, a master's student at Wuhan University of Technology.

Authors:

Wei Chai Wuhan University of Technology
Jingcan Wang Wuhan University of Technology
Zhengbing Lu Wuhan University of Technology
Yi Zhu Wuhan University of Technology
Fanghuai Xiong Wuhan University of Technology
Zhenbo Zhang Wuhan University of Technology