Extreme value estimation of mooring lines top tension

Abstract

It is known that the mooring system of floating platforms responds non-linearly to environmental loads. Even though the wave-frequency excitation can be assumed as a Gaussian process, the line tension generally is not due to second-order slow-drift floater motions and nonlinearities of the system itself. This work assumes the short-term line tension as a non-Gaussian ergodic process. The extreme tension is estimated based on the peaks sample of a single simulated tension time-history. A number of known probability distributions are fitted to the peaks of the time series and classic order statistics theory is applied to determine the most probable extreme line tension corresponding to a specified short-time period (3-h) in order to identify the one with best performance. The effects of major parameters in the dynamic analysis, such as simulation length and discretization level of the wave spectrum, are also investigated using several simulated tension timehistories. Furthermore, the effect of correlation between consecutive tension peaks in the extreme values estimation is investigated through the one-step Markov chain condition (using a Nataf transformation-based model for two consecutive peaks joint probability distribution) and through the ACER method. It is shown that this consideration leads to extreme value estimates that are invariably smaller than those obtained by standard order statistics. These estimates are also shown to be closer to the extreme estimates directly obtained from a sample of epochal maxima taken from several distinct numerical simulations. Numerical examples cover two study cases for mooring lines belonging to FPSO units to be installed offshore Brazil.