Digital Twin of Polyester Mooring Lines for a Deepwater Field in Hurricane Environment Using Motion Sensors – Lessons Learned

海洋工程 系泊 领域(数学) 运动(物理) 运动传感器 计算机科学 航空航天工程 工程类 地质学 人工智能 数学 纯数学
作者
B. W. Jaeger,D.M. Lobo,L. Pereira
标识
DOI:10.4043/35174-ms
摘要

Abstract A mooring monitoring campaign has been conducted to investigate dynamic behavior in the mooring system of a deepwater Floating Production System (FPS) in a hurricane environment, to investigate the risk of polyester rope contact with the seabed, which, based on the prevailing understanding of rope characteristics and modelling, should not occur. In total 12 subsea motion sensors have been deployed in the campaign, covering 3 different locations (depths) on 1 off mooring line in each of the 4 mooring clusters. The mooring sensor data is combined with onboard vessel motion data and environmental data to feed a standalone digital twin. The purpose of the digital twin is initially to aid the understanding of the dynamic behavior and characteristics of the polyester mooring lines but could later be expanded to cover additional purposes such as operational decision support. The monitoring campaign is ongoing for the second year and the results reported here are based on data from the first hurricane season (2022-2023). Results for the first season did not include any extreme storms which means that direct seabed impact or other direct evidence of unexpected behavior in extreme conditions have not been observed. Instead, a range of results, including moderately severe sea states related to a hurricane, are used to establish and verify the digital twin, and explore sensitivities and variations in the mooring system modelling and polyester rope characteristics. Key results from this work are presented and the potential for further development is discussed.

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