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FPSO (Floating Production, Storage and Offloading) or FLNG (Floating Liquefied Natural Gas) vessels produce and store crude oil or liquified natural gas before being transported by ST (Shuttle Tanker). Robust prediction of excessive mooring and hawser stresses being crucial for structural design and operational safety. Offloading activities may result in excessive hawser or mooring line tensions, impacting environmental and operational safety. Current study employed ANSYS-AQWA software to simulate vessels dynamics, subjected to wind-wave hydrodynamic loads, given realistic in-situ environmental conditions. State-of-the-art multi-dimensional risk assessment methodology, presented in this work being based on direct MC (Monte Carlo) simulations, however, it is equally applicable to measured data. Advocated methodology effectively utilizes underlying dataset, offering accurate failure/damage risk assessment. Current study aims to benchmark recently developed multivariate Gaidai risk assessment approach, allowing for the straightforward yet efficient prediction of failure and damage risks for nonlinear multi-dimensional dynamic offshore/naval system as a whole. Primary benefit of the proposed methodology lies in its multi-dimensionality, as it can encompass virtually infinite number of system's dimensions/components, each having its distinct physical dimension. In contrast, traditional reliability methods are usually limited to a maximum of two-dimensional systems. Novel deconvolution extrapolation scheme offers additional advantage, being non-parametrical by its nature, as opposed to existing parametric extrapolation techniques.
Gaidai et al. (Mon,) studied this question.