A Hybrid Time-Frequency Domain Approach for Estimating Mooring Lines Dynamic Response

Abstract

It is known that, for a given short-term environmental condition, mooring lines fatigue damage assessment can be made from the tension cycles counting using a sufficiently long tension time series. This can be obtained through coupled floater-lines time domain analyses where lines are modeled with the catenary equation, leading to faster simulations but also to quasi-static line responses that do not take line dynamics into account. On the other hand, a coupled floater-lines analysis where the lines are modeled with finite elements (FE) can assess line dynamics effects since it considers dynamic amplifications of the system in the wave frequency range. Such dynamic effects can greatly impact fatigue damage calculations and should be considered. However, while more accurate, coupled FEA-based models can become very expensive in time and computer resources when the number of environmental conditions to be evaluated is high. In this context, an approximate and efficient hybrid solution was developed for the assessment of dynamic tension series, taking advantage of quasi-static coupled analyses. In the solution, it is assumed that the line dynamic response can be roughly estimated in the frequency domain from linearized tension transfer functions for the segment of interest and from motion series at the floater-line connection point, obtained with previous quasi-static analyses. The linearized tension transfer functions are previously obtained by applying unitary amplitude motions in the line axial direction at the top connection point for different excitation frequencies and also for different line pretension levels. The methodology is validated for a spread-moored FPSO installed in Brazilian deep waters. When compared to complete FEA-based dynamic analyses, it is shown that the simplified solution provides good estimates for the lines dynamic tension response and can be a powerful tool to save computer time in fatigue damage assessments.