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A methodology to calculate the fatigue damage in non-collinear wind generated sea and swell has been proposed for weather vaning turret moored FPSO’s. The methodology consists in specifying long-term distributions of sea and swell conditions by directional wave scatter diagrams of Hs and Tp and extracting the swell – and wind wave contributions by use of the Torsethaugen double-peaked wave spectra. By assuming the wind sea induced response and the swell induced response to be independent narrow banded processes, response spectra for the combined processes are established. The wave loads are calculated from a hydrodynamic analysis and a closed form approach is used to calculate the fatigue damage summation. The fatigue damage of selected side longitudinal stiffener fillet welds is calculated by using the proposed methodology for a Norwegian Sea FPSO at three different hull girder cross-sections. The relative contributions from sea and swell to the total damage are identified as well as the sea-states and headings that contribute most to the total damage. In addition, the proposed methodology is compared with the more traditional approach, assuming both wind sea and swell to come from the same direction. For the traditional approach, the corresponding resulting wave spectrum used is a single peaked type, i.e. Pierson Moskowitz.

This paper presents a method for predicting extreme roll motion on an FPSO using long-term statistics. The method consists of a long-term simulation where a database of consecutive short-term sea states with combined weather conditions, including direction and magnitude of wind, wind waves and swell waves, is used. The vessel heading in given weather conditions is simulated. For each combined sea state, the short-term roll motion maxima are calculated to form a long-term probability distribution, and the extreme roll motion, e.g. the 100-year value, can be estimated from the distribution. For an example FPSO, the results from the long-term analysis have been compared with full-scale measurements, giving a validation of the method. This paper is a shortened version of [1].