Abstract
The intention of this work is to perform a probabilistic fatigue assessment of a mooring line due to loads associated with the station-keeping of a ship in ice. In March 2017, the company Equinor (Statoil) conducted full-scale tests by means of station-keeping trials (SKT) in drifting ice in the Bay of Bothnia. The vessel Magne Viking was employed in order to represent a supply vessel equipped with a mooring line system, and the realtime loading during the full-scale measurement was recorded. The second vessel Tor Viking was serving as an ice breaker in order to maintain the physical ice management activities with different ice-breaking schemes, i.e. square updrift pattern, round circle pattern, circular updrift pattern and linear updrift pattern. The fatigue degradation corresponding to these different patterns were investigated. The peaks and valleys of the mooring tension are determined using the min peak prominence method. For the purpose of probabilistic fatigue assessment, the Rainflow-counting algorithm is applied to estimate the mooring stress range. Fatigue assessment based both on Rainflow counting and fitted probabilistic models were performed. For the latter, the stress range distributions from the observed data of mooring loads are fitted to various probability models in order to estimate the fatigue damage. It is found that the stress ranges represented by application of the Weibull distribution for the probabilistic fatigue approach provides results of the fatigue damage most similar to the Rainflow counting approach. Among the different scenarios of Ice management schemes, the circular updrift pattern provides the lowest magnitude of the fatigue degradation.
Challenges and Strategies for a Real-Time Implementation of a Rainflow-Counting Algorithm for Fatigue Assessment of Power Modules
