Abstract
Numerical simulation of mooring dynamics is computationally expensive, which limits its use in optimisation and control loops; data-driven system identification (SI) offers a complementary route. This work reviews the state-of-the-art of SI for mooring modelling and proposes a modular framework in which the empirical transfer function of a single mooring line is identified in the frequency domain and used, via a coordinate change, to reconstruct the global response of spread taut and semi-taut mooring configurations. The framework is assessed on a numerical wave energy converter benchmark and validated experimentally on a 1:96 reduced-scale floating offshore wind turbine with a taut-leg mooring. The identified models reproduce the dominant mooring dynamics at a fraction of the computational cost of finite-element simulations and recover physically meaningful line properties; limitations under catenary, slack-line and extreme-state regimes are explicitly discussed.