Probabilistic analysis of extreme riser responses for a weather-vaning FPSO in tropical cyclones
Armstrong, C and Drobyshevksi, Y and Chin, C and Penesis, I, Probabilistic analysis of extreme riser responses for a weather-vaning FPSO in tropical cyclones, Journal of Offshore Mechanics and Arctic Engineering, 141, (2) Article 021602. ISSN 0892-7219 (2019) [Refereed Article]
The probability distributions of extreme responses of a flexible riser connected to a weather-vaning floating production storage and offloading (FPSO) are developed and investigated numerically for two tropical cyclones. Statistical properties of riser responses provide the foundation for response based analysis (RBA), a comprehensive approach for the prediction of extreme responses and design metocean conditions of offshore systems. The storm-based probabilistic analysis is applied to responses of flexible risers with the objective to develop their distributions in a storm and to determine their most probable maximum (MPM) values. An asymptotic form of the response distribution in a storm is formulated, which can be used in the random event, method of Tromans and Vandersohuren (1995, "Response Based Design Conditions in the North Sea: Application of a New Method," Offshore Technology Conference, Houston, TX, May 1–4). The methodology is illustrated by two case studies for an FPSO in cyclonic storms at a location offshore Australia. Time domain simulations are employed to predict the FPSO motions, critical riser responses, and their probability distributions. It is shown that the maximum storm responses can be reproduced by governing "equivalent" metocean intervals with increased percentiles or inflated durations. Effects of different environmental excitation upon the risers and their impact on the statistical properties of responses are discussed, providing important insights for extension toward a multistorm RBA approach. The study also discusses issues with practices such as the analysis for a 3 h design event and presents observations on the variability of several types of responses, which reveal their environmental sensitivities.