ABSTRACT

Spar platform, a compliant floating structure, is well suited for deep water applications like drilling, production, processing, storage and off-loading of ocean deposits. It's popularity is attributed to it's economical performance and distinguished sea keeping characteristics besides various other merits. However, the analysis of Spar-mooring system poses tedious computational problems, primarily because of the uncertainties associated with the environmental loads, structural configuration and resulting nonlinearities. Spar is modeled as rigid cylinder, provided stability and stiffness by catenary cables attached to the cylinder at fairleads and spread out horizontally. Moorings, partly lying on the sea floor, hinged to the sea bed at the far end. Their contact with sea bed is properly modeled. The mooring lines in deep water conditions contribute towards significant inertia and damping due to their longer lengths, larger sizes and heavier weights. Coupled analysis, presently adopted, employs a fully integrated spar mooring system. A finite element model consists of a rigid cylinder linked and supported by tensioned mooring lines at fairleads. Hybrid beam elements are used to model the mooring lines experiencing large deformations and tension fluctuations of random nature. Their linkage with spar cylinder is suitably modeled through connector element provided in ABAQUS. It ensures integrated coupling and structural continuity. Spar hull is modeled as an assemblage of rigid beam elements connecting its centre of gravity, riser reaction point and mooring line fairleads. Monte carlo simulation is adopted to model the long crested random sea. The implicit solver employed is based on a step-by-step iterative time domain algorithm. The solver adjusts the size of time step to achieve accuracy and stability of the solution. Hence, the convergence of the solution is computationally intensive. Power spectra for various hull motions and maximum mooring tension are plotted and analyzed. Statistical characteristics of random response histories are also obtained. The integrated coupling shows a distinguished influence on the response behavior.

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