Prediction of Deepwater FPSO responses using different numerical analysis methods

The limitations of existing wave basins present a significant challenge when modelling offshore deepwater systems, particularly due to the basin's relatively shallow depth. Numerical simulation thus becomes valuable in predicting its behaviour during operation at sea. The coupled dynamic analys...

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Bibliographic Details
Main Authors: Guan, M., Osman, M., Ng, C.Y.
Format: Article
Published: EDP Sciences 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047728459&doi=10.1051%2fe3sconf%2f20183402032&partnerID=40&md5=734403c19ab756e10eefe09c05895ce2
http://eprints.utp.edu.my/21679/
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Summary:The limitations of existing wave basins present a significant challenge when modelling offshore deepwater systems, particularly due to the basin's relatively shallow depth. Numerical simulation thus becomes valuable in predicting its behaviour during operation at sea. The coupled dynamic analysis is preferred over the traditional quasi-static method, as the former enables the inclusion of damping and added mass properties of the complete mooring line system, which becomes increasingly prominent at greater water depths. This paper investigates the motions and mooring line tensions of a turret moored Floating Production Storage Offloading (FPSO) platform using three numerical models, i.e. a dynamic system, quasi-static system and linear spring system subjected to unidirectional random wave condition. Analysis is carried out using a commercial software AQWA. The first two numerical models utilise a complete system of the same setup and configuration, while the linear spring system substitutes the mooring lines with equivalent linear springs and attempts to match the total mooring line restoring forces with that of the coupled dynamic analysis. The study demonstrates the significance of coupled dynamic analysis on the responses of an FPSO in deepwater. The numerical model of the FPSO is validated against the results of a published work. © The Authors, published by EDP Sciences, 2018.