Establishing statistical distributions of the response extremes is of particular importance for the design of FPSO mooring systems and the related riser design. Long term time domain simulation is the most accurate design approach to determine the extreme responses. It involves, however, coupled dynamic analysis of FPSO mooring system for a large number of sea states and consequently the task is often prohibitively time consuming. To solve this problem, an approach for the long term extreme analysis based on a metamodel in conjunction with the design of experiment methodology is proposed in the paper. In this approach, Latin Hypercube Sampling (LHS) based on the design of experiment method, is performed to select a sub-set of sea states from all sea states. Short term distributions for this sub-set of sea states are simulated and estimated. Kriging metamodel, which can map the relations between the sea states characteristics and the short term distribution parameters, is then applied. The accuracy of the metamodel is investigated. The long term response distribution of moored FPSO systems for all sea states can be predicted based on the metamodel. This approach for the long term extreme analysis of FPSO mooring systems avoids the response analysis over all sea states and can greatly improve the computational efficiency of the long term extreme analysis of FPSO mooring systems.

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