As current attention of the offshore industry is drawn by developing pilot farms of Floating Wind Turbines (FWTs) in shallow-water between 50m and 100m, the application of nylon as a mooring component can provide a more cost-effective design. Indeed, nylon is a preferred candidate over polyester for FWT mooring mainly because of its lower stiffness and a corresponding capacity of reducing maximum tensions in the mooring system. However, the nonlinear behaviors of nylon ropes (e.g. load-elongation properties, fatigue characteristics, etc.) complicate the design and modeling of such structures. Although previous studies on the mechanical properties and modeling of polyester may be very good references, those can not be applied directly for nylon both on testing and modeling methods. In this study, first, an empirical expression to determine the dynamic stiffness of a nylon rope is drawn from the testing data in the literature. Secondly, a practical modeling procedure is suggested by the authors in order to cope with the numerical mooring analysis for a semi-submersible type FWT taking into account the dynamic axial stiffness of nylon ropes. Both the experimental and numerical results show that the tension amplitude has an important impact on the dynamic stiffness of nylon ropes and, as a consequence, the tension responses of mooring lines. This effect can be captured by the present modeling procedure. Finally, time domain mooring analysis for both Ultimate Limit State (ULS) and Fatigue Limit State (FLS) is performed to illustrate the advantages and conservativeness of the present approach for nylon mooring modeling.
Bio-colonisation affects the ageing of materials and the behaviour of offshore structures. Mooring systems and umbilicals belong to the family of slender bodies which are components sensitive to bio-colonisation because of a change of dynamic behaviour due to shape, roughness and mass modifications. However, this stochastic process in time and space is hard to predict. The purpose is then twofold: first, to provide a stochastic spatial model of the bio-colonisation on a mooring line; second, to show that in some defined environmental conditions, such as low wave height, low wind and current velocities, the monitoring of mooring lines tension can help to assess and reduce uncertainty on this model. Therefore, a comprehensive stochastic modelling based on mussels colonisation was carried out using on-site videotapes, experimental campaigns and expert knowledge. We studied the efficiency of a virtual sensing network using this model and a conditional entropy metric. It is first shown that the spatial model fits well with experimental data, and second that a denser medium accuracy sensor network is to be preferred to a single high accuracy fairlead sensor to reduce the uncertainty on the model parameters. It is then worth updating bio-colonisation on mooring lines during the life-time of a floating wind turbine.
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